Analyzing nonstationary financial time series via hilbert-huang transform (HHT)
Huang, Norden E. (Inventor)
2008-01-01
An apparatus, computer program product and method of analyzing non-stationary time varying phenomena. A representation of a non-stationary time varying phenomenon is recursively sifted using Empirical Mode Decomposition (EMD) to extract intrinsic mode functions (IMFs). The representation is filtered to extract intrinsic trends by combining a number of IMFs. The intrinsic trend is inherent in the data and identifies an IMF indicating the variability of the phenomena. The trend also may be used to detrend the data.
Local normalization: Uncovering correlations in non-stationary financial time series
Schäfer, Rudi; Guhr, Thomas
2010-09-01
The measurement of correlations between financial time series is of vital importance for risk management. In this paper we address an estimation error that stems from the non-stationarity of the time series. We put forward a method to rid the time series of local trends and variable volatility, while preserving cross-correlations. We test this method in a Monte Carlo simulation, and apply it to empirical data for the S&P 500 stocks.
Tóth, B.; Lillo, F.; Farmer, J. D.
2010-11-01
We introduce an algorithm for the segmentation of a class of regime switching processes. The segmentation algorithm is a non parametric statistical method able to identify the regimes (patches) of a time series. The process is composed of consecutive patches of variable length. In each patch the process is described by a stationary compound Poisson process, i.e. a Poisson process where each count is associated with a fluctuating signal. The parameters of the process are different in each patch and therefore the time series is non-stationary. Our method is a generalization of the algorithm introduced by Bernaola-Galván, et al. [Phys. Rev. Lett. 87, 168105 (2001)]. We show that the new algorithm outperforms the original one for regime switching models of compound Poisson processes. As an application we use the algorithm to segment the time series of the inventory of market members of the London Stock Exchange and we observe that our method finds almost three times more patches than the original one.
Robust Forecasting of Non-Stationary Time Series
Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.
2010-01-01
This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable
Dynamic Factor Analysis of Nonstationary Multivariate Time Series.
Molenaar, Peter C. M.; And Others
1992-01-01
The dynamic factor model proposed by P. C. Molenaar (1985) is exhibited, and a dynamic nonstationary factor model (DNFM) is constructed with latent factor series that have time-varying mean functions. The use of a DNFM is illustrated using data from a television viewing habits study. (SLD)
Compounding approach for univariate time series with nonstationary variances
Schäfer, Rudi; Barkhofen, Sonja; Guhr, Thomas; Stöckmann, Hans-Jürgen; Kuhl, Ulrich
2015-12-01
A defining feature of nonstationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for long time horizons, however, averages over the time-dependent variances. To model the long-term statistical behavior, we compound the local distribution with the distribution of its parameters. Here, we consider two concrete, but diverse, examples of such nonstationary systems: the turbulent air flow of a fan and a time series of foreign exchange rates. Our main focus is to empirically determine the appropriate parameter distribution for the compounding approach. To this end, we extract the relevant time scales by decomposing the time signals into windows and determine the distribution function of the thus obtained local variances.
Robust Forecasting of Non-Stationary Time Series
Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.
2010-01-01
This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable forecasts in the presence of outliers, non-linearity, and heteroscedasticity. In the absence of outliers, the forecasts are only slightly less precise than those based on a localized Least Squares estima...
Deviations from uniform power law scaling in nonstationary time series
Viswanathan, G. M.; Peng, C. K.; Stanley, H. E.; Goldberger, A. L.
1997-01-01
A classic problem in physics is the analysis of highly nonstationary time series that typically exhibit long-range correlations. Here we test the hypothesis that the scaling properties of the dynamics of healthy physiological systems are more stable than those of pathological systems by studying beat-to-beat fluctuations in the human heart rate. We develop techniques based on the Fano factor and Allan factor functions, as well as on detrended fluctuation analysis, for quantifying deviations from uniform power-law scaling in nonstationary time series. By analyzing extremely long data sets of up to N = 10(5) beats for 11 healthy subjects, we find that the fluctuations in the heart rate scale approximately uniformly over several temporal orders of magnitude. By contrast, we find that in data sets of comparable length for 14 subjects with heart disease, the fluctuations grow erratically, indicating a loss of scaling stability.
Trend analysis using non-stationary time series clustering based on the finite element method
Gorji Sefidmazgi, M.; Sayemuzzaman, M.; Homaifar, A.; Jha, M. K.; Liess, S.
2014-01-01
In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods ...
Correlation, Regression, and Cointegration of Nonstationary Economic Time Series
DEFF Research Database (Denmark)
Johansen, Søren
), and Phillips (1986) found the limit distributions. We propose to distinguish between empirical and population correlation coefficients and show in a bivariate autoregressive model for nonstationary variables that the empirical correlation and regression coefficients do not converge to the relevant population...... values, due to the trending nature of the data. We conclude by giving a simple cointegration analysis of two interests. The analysis illustrates that much more insight can be gained about the dynamic behavior of the nonstationary variables then simply by calculating a correlation coefficient......Yule (1926) introduced the concept of spurious or nonsense correlation, and showed by simulation that for some nonstationary processes, that the empirical correlations seem not to converge in probability even if the processes were independent. This was later discussed by Granger and Newbold (1974...
Correlation, regression, and cointegration of nonstationary economic time series
DEFF Research Database (Denmark)
Johansen, Søren
Yule (1926) introduced the concept of spurious or nonsense correlation, and showed by simulation that for some nonstationary processes, that the empirical correlations seem not to converge in probability even if the processes were independent. This was later discussed by Granger and Newbold (1974......), and Phillips (1986) found the limit distributions. We propose to distinguish between empirical and population correlation coeffients and show in a bivariate autoregressive model for nonstationary variables that the empirical correlation and regression coe¢ cients do not converge to the relevant population...
Yoon, Heonjun; Kim, Miso; Park, Choon-Su; Youn, Byeng D.
2018-01-01
Piezoelectric vibration energy harvesting (PVEH) has received much attention as a potential solution that could ultimately realize self-powered wireless sensor networks. Since most ambient vibrations in nature are inherently random and nonstationary, the output performances of PVEH devices also randomly change with time. However, little attention has been paid to investigating the randomly time-varying electroelastic behaviors of PVEH systems both analytically and experimentally. The objective of this study is thus to make a step forward towards a deep understanding of the time-varying performances of PVEH devices under nonstationary random vibrations. Two typical cases of nonstationary random vibration signals are considered: (1) randomly-varying amplitude (amplitude modulation; AM) and (2) randomly-varying amplitude with randomly-varying instantaneous frequency (amplitude and frequency modulation; AM-FM). In both cases, this study pursues well-balanced correlations of analytical predictions and experimental observations to deduce the relationships between the time-varying output performances of the PVEH device and two primary input parameters, such as a central frequency and an external electrical resistance. We introduce three correlation metrics to quantitatively compare analytical prediction and experimental observation, including the normalized root mean square error, the correlation coefficient, and the weighted integrated factor. Analytical predictions are in an excellent agreement with experimental observations both mechanically and electrically. This study provides insightful guidelines for designing PVEH devices to reliably generate electric power under nonstationary random vibrations.
Production planning of a perishable product with lead time and non-stationary demand
Pauls-Worm, K.G.J.; Haijema, R.; Hendrix, E.M.T.; Rossi, R.; Vorst, van der J.G.A.J.
2012-01-01
We study a production planning problem for a perishable product with a fixed lifetime, under a service-level constraint. The product has a non-stationary stochastic demand. Food supply chains of fresh products like cheese and several crop products, are characterised by long lead times due to
System identification through nonstationary data using Time-Frequency Blind Source Separation
Guo, Yanlin; Kareem, Ahsan
2016-06-01
Classical output-only system identification (SI) methods are based on the assumption of stationarity of the system response. However, measured response of buildings and bridges is usually non-stationary due to strong winds (e.g. typhoon, and thunder storm etc.), earthquakes and time-varying vehicle motions. Accordingly, the response data may have time-varying frequency contents and/or overlapping of modal frequencies due to non-stationary colored excitation. This renders traditional methods problematic for modal separation and identification. To address these challenges, a new SI technique based on Time-Frequency Blind Source Separation (TFBSS) is proposed. By selectively utilizing "effective" information in local regions of the time-frequency plane, where only one mode contributes to energy, the proposed technique can successfully identify mode shapes and recover modal responses from the non-stationary response where the traditional SI methods often encounter difficulties. This technique can also handle response with closely spaced modes which is a well-known challenge for the identification of large-scale structures. Based on the separated modal responses, frequency and damping can be easily identified using SI methods based on a single degree of freedom (SDOF) system. In addition to the exclusive advantage of handling non-stationary data and closely spaced modes, the proposed technique also benefits from the absence of the end effects and low sensitivity to noise in modal separation. The efficacy of the proposed technique is demonstrated using several simulation based studies, and compared to the popular Second-Order Blind Identification (SOBI) scheme. It is also noted that even some non-stationary response data can be analyzed by the stationary method SOBI. This paper also delineates non-stationary cases where SOBI and the proposed scheme perform comparably and highlights cases where the proposed approach is more advantageous. Finally, the performance of the
Self-organising mixture autoregressive model for non-stationary time series modelling.
Ni, He; Yin, Hujun
2008-12-01
Modelling non-stationary time series has been a difficult task for both parametric and nonparametric methods. One promising solution is to combine the flexibility of nonparametric models with the simplicity of parametric models. In this paper, the self-organising mixture autoregressive (SOMAR) network is adopted as a such mixture model. It breaks time series into underlying segments and at the same time fits local linear regressive models to the clusters of segments. In such a way, a global non-stationary time series is represented by a dynamic set of local linear regressive models. Neural gas is used for a more flexible structure of the mixture model. Furthermore, a new similarity measure has been introduced in the self-organising network to better quantify the similarity of time series segments. The network can be used naturally in modelling and forecasting non-stationary time series. Experiments on artificial, benchmark time series (e.g. Mackey-Glass) and real-world data (e.g. numbers of sunspots and Forex rates) are presented and the results show that the proposed SOMAR network is effective and superior to other similar approaches.
The Fourier decomposition method for nonlinear and non-stationary time series analysis.
Singh, Pushpendra; Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik
2017-03-01
for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of 'Fourier intrinsic band functions' (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time-frequency-energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms.
Segmentation of Nonstationary Time Series with Geometric Clustering
DEFF Research Database (Denmark)
Bocharov, Alexei; Thiesson, Bo
2013-01-01
We introduce a non-parametric method for segmentation in regimeswitching time-series models. The approach is based on spectral clustering of target-regressor tuples and derives a switching regression tree, where regime switches are modeled by oblique splits. Such models can be learned efficiently...... from data, where clustering is used to propose one single split candidate at each split level. We use the class of ART time series models to serve as illustration, but because of the non-parametric nature of our segmentation approach, it readily generalizes to a wide range of time-series models that go...
Financial time series prediction using spiking neural networks.
Reid, David; Hussain, Abir Jaafar; Tawfik, Hissam
2014-01-01
In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two "traditional", rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments.
Trend analysis using non-stationary time series clustering based on the finite element method
Gorji Sefidmazgi, M.; Sayemuzzaman, M.; Homaifar, A.; Jha, M. K.; Liess, S.
2014-05-01
In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods that can analyze multidimensional time series. One important attribute of this method is that it is not dependent on any statistical assumption and does not need local stationarity in the time series. In this paper, it is shown how the FEM-clustering method can be used to locate change points in the trend of temperature time series from in situ observations. This method is applied to the temperature time series of North Carolina (NC) and the results represent region-specific climate variability despite higher frequency harmonics in climatic time series. Next, we investigated the relationship between the climatic indices with the clusters/trends detected based on this clustering method. It appears that the natural variability of climate change in NC during 1950-2009 can be explained mostly by AMO and solar activity.
Identification of the structure parameters using short-time non-stationary stochastic excitation
Jarczewska, Kamila; Koszela, Piotr; Śniady, PaweŁ; Korzec, Aleksandra
2011-07-01
In this paper, we propose an approach to the flexural stiffness or eigenvalue frequency identification of a linear structure using a non-stationary stochastic excitation process. The idea of the proposed approach lies within time domain input-output methods. The proposed method is based on transforming the dynamical problem into a static one by integrating the input and the output signals. The output signal is the structure reaction, i.e. structure displacements due to the short-time, irregular load of random type. The systems with single and multiple degrees of freedom, as well as continuous systems are considered.
Noise Reduction for Nonlinear Nonstationary Time Series Data using Averaging Intrinsic Mode Function
Directory of Open Access Journals (Sweden)
Christofer Toumazou
2013-07-01
Full Text Available A novel noise filtering algorithm based on averaging Intrinsic Mode Function (aIMF, which is a derivation of Empirical Mode Decomposition (EMD, is proposed to remove white-Gaussian noise of foreign currency exchange rates that are nonlinear nonstationary times series signals. Noise patterns with different amplitudes and frequencies were randomly mixed into the five exchange rates. A number of filters, namely; Extended Kalman Filter (EKF, Wavelet Transform (WT, Particle Filter (PF and the averaging Intrinsic Mode Function (aIMF algorithm were used to compare filtering and smoothing performance. The aIMF algorithm demonstrated high noise reduction among the performance of these filters.
Kwasniok, Frank
2013-11-01
A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.
Time-frequency representation of a highly nonstationary signal via the modified Wigner distribution
Zoladz, T. F.; Jones, J. H.; Jong, J.
1992-01-01
A new signal analysis technique called the modified Wigner distribution (MWD) is presented. The new signal processing tool has been very successful in determining time frequency representations of highly non-stationary multicomponent signals in both simulations and trials involving actual Space Shuttle Main Engine (SSME) high frequency data. The MWD departs from the classic Wigner distribution (WD) in that it effectively eliminates the cross coupling among positive frequency components in a multiple component signal. This attribute of the MWD, which prevents the generation of 'phantom' spectral peaks, will undoubtedly increase the utility of the WD for real world signal analysis applications which more often than not involve multicomponent signals.
An Integrated Real-Time Beamforming and Postfiltering System for Nonstationary Noise Environments
Directory of Open Access Journals (Sweden)
Gannot Sharon
2003-01-01
Full Text Available We present a novel approach for real-time multichannel speech enhancement in environments of nonstationary noise and time-varying acoustical transfer functions (ATFs. The proposed system integrates adaptive beamforming, ATF identification, soft signal detection, and multichannel postfiltering. The noise canceller branch of the beamformer and the ATF identification are adaptively updated online, based on hypothesis test results. The noise canceller is updated only during stationary noise frames, and the ATF identification is carried out only when desired source components have been detected. The hypothesis testing is based on the nonstationarity of the signals and the transient power ratio between the beamformer primary output and its reference noise signals. Following the beamforming and the hypothesis testing, estimates for the signal presence probability and for the noise power spectral density are derived. Subsequently, an optimal spectral gain function that minimizes the mean square error of the log-spectral amplitude (LSA is applied. Experimental results demonstrate the usefulness of the proposed system in nonstationary noise environments.
Time-dependent scaling patterns in high frequency financial data
Nava, Noemi; Di Matteo, Tiziana; Aste, Tomaso
2016-10-01
We measure the influence of different time-scales on the intraday dynamics of financial markets. This is obtained by decomposing financial time series into simple oscillations associated with distinct time-scales. We propose two new time-varying measures of complexity: 1) an amplitude scaling exponent and 2) an entropy-like measure. We apply these measures to intraday, 30-second sampled prices of various stock market indices. Our results reveal intraday trends where different time-horizons contribute with variable relative amplitudes over the course of the trading day. Our findings indicate that the time series we analysed have a non-stationary multifractal nature with predominantly persistent behaviour at the middle of the trading session and anti-persistent behaviour at the opening and at the closing of the session. We demonstrate that these patterns are statistically significant, robust, reproducible and characteristic of each stock market. We argue that any modelling, analytics or trading strategy must take into account these non-stationary intraday scaling patterns.
Medina, Daniel C; Findley, Sally E; Guindo, Boubacar; Doumbia, Seydou
2007-11-21
Much of the developing world, particularly sub-Saharan Africa, exhibits high levels of morbidity and mortality associated with diarrhea, acute respiratory infection, and malaria. With the increasing awareness that the aforementioned infectious diseases impose an enormous burden on developing countries, public health programs therein could benefit from parsimonious general-purpose forecasting methods to enhance infectious disease intervention. Unfortunately, these disease time-series often i) suffer from non-stationarity; ii) exhibit large inter-annual plus seasonal fluctuations; and, iii) require disease-specific tailoring of forecasting methods. In this longitudinal retrospective (01/1996-06/2004) investigation, diarrhea, acute respiratory infection of the lower tract, and malaria consultation time-series are fitted with a general-purpose econometric method, namely the multiplicative Holt-Winters, to produce contemporaneous on-line forecasts for the district of Niono, Mali. This method accommodates seasonal, as well as inter-annual, fluctuations and produces reasonably accurate median 2- and 3-month horizon forecasts for these non-stationary time-series, i.e., 92% of the 24 time-series forecasts generated (2 forecast horizons, 3 diseases, and 4 age categories = 24 time-series forecasts) have mean absolute percentage errors circa 25%. The multiplicative Holt-Winters forecasting method: i) performs well across diseases with dramatically distinct transmission modes and hence it is a strong general-purpose forecasting method candidate for non-stationary epidemiological time-series; ii) obliquely captures prior non-linear interactions between climate and the aforementioned disease dynamics thus, obviating the need for more complex disease-specific climate-based parametric forecasting methods in the district of Niono; furthermore, iii) readily decomposes time-series into seasonal components thereby potentially assisting with programming of public health interventions
Real-Time Emulation of Nonstationary Channels in Safety-Relevant Vehicular Scenarios
Directory of Open Access Journals (Sweden)
Golsa Ghiaasi
2018-01-01
Full Text Available This paper proposes and discusses the architecture for a real-time vehicular channel emulator capable of reproducing the input/output behavior of nonstationary time-variant radio propagation channels in safety-relevant vehicular scenarios. The vehicular channel emulator architecture aims at a hardware implementation which requires minimal hardware complexity for emulating channels with the varying delay-Doppler characteristics of safety-relevant vehicular scenarios. The varying delay-Doppler characteristics require real-time updates to the multipath propagation model for each local stationarity region. The vehicular channel emulator is used for benchmarking the packet error performance of commercial off-the-shelf (COTS vehicular IEEE 802.11p modems and a fully software-defined radio-based IEEE 802.11p modem stack. The packet error ratio (PER estimated from temporal averaging over a single virtual drive and the packet error probability (PEP estimated from ensemble averaging over repeated virtual drives are evaluated and compared for the same vehicular scenario. The proposed architecture is realized as a virtual instrument on National Instruments™ LabVIEW. The National Instrument universal software radio peripheral with reconfigurable input-output (USRP-Rio 2953R is used as the software-defined radio platform for implementation; however, the results and considerations reported are of general purpose and can be applied to other platforms. Finally, we discuss the PER performance of the modem for two categories of vehicular channel models: a vehicular nonstationary channel model derived for urban single lane street crossing scenario of the DRIVEWAY’09 measurement campaign and the stationary ETSI models.
Efficient Transfer Entropy Analysis of Non-Stationary Neural Time Series
Vicente, Raul; Díaz-Pernas, Francisco J.; Wibral, Michael
2014-01-01
Information theory allows us to investigate information processing in neural systems in terms of information transfer, storage and modification. Especially the measure of information transfer, transfer entropy, has seen a dramatic surge of interest in neuroscience. Estimating transfer entropy from two processes requires the observation of multiple realizations of these processes to estimate associated probability density functions. To obtain these necessary observations, available estimators typically assume stationarity of processes to allow pooling of observations over time. This assumption however, is a major obstacle to the application of these estimators in neuroscience as observed processes are often non-stationary. As a solution, Gomez-Herrero and colleagues theoretically showed that the stationarity assumption may be avoided by estimating transfer entropy from an ensemble of realizations. Such an ensemble of realizations is often readily available in neuroscience experiments in the form of experimental trials. Thus, in this work we combine the ensemble method with a recently proposed transfer entropy estimator to make transfer entropy estimation applicable to non-stationary time series. We present an efficient implementation of the approach that is suitable for the increased computational demand of the ensemble method's practical application. In particular, we use a massively parallel implementation for a graphics processing unit to handle the computationally most heavy aspects of the ensemble method for transfer entropy estimation. We test the performance and robustness of our implementation on data from numerical simulations of stochastic processes. We also demonstrate the applicability of the ensemble method to magnetoencephalographic data. While we mainly evaluate the proposed method for neuroscience data, we expect it to be applicable in a variety of fields that are concerned with the analysis of information transfer in complex biological, social, and
Faes, Luca; Zhao, He; Chon, Ki H; Nollo, Giandomenico
2009-03-01
We propose a method to extend to time-varying (TV) systems the procedure for generating typical surrogate time series, in order to test the presence of nonlinear dynamics in potentially nonstationary signals. The method is based on fitting a TV autoregressive (AR) model to the original series and then regressing the model coefficients with random replacements of the model residuals to generate TV AR surrogate series. The proposed surrogate series were used in combination with a TV sample entropy (SE) discriminating statistic to assess nonlinearity in both simulated and experimental time series, in comparison with traditional time-invariant (TIV) surrogates combined with the TIV SE discriminating statistic. Analysis of simulated time series showed that using TIV surrogates, linear nonstationary time series may be erroneously regarded as nonlinear and weak TV nonlinearities may remain unrevealed, while the use of TV AR surrogates markedly increases the probability of a correct interpretation. Application to short (500 beats) heart rate variability (HRV) time series recorded at rest (R), after head-up tilt (T), and during paced breathing (PB) showed: 1) modifications of the SE statistic that were well interpretable with the known cardiovascular physiology; 2) significant contribution of nonlinear dynamics to HRV in all conditions, with significant increase during PB at 0.2 Hz respiration rate; and 3) a disagreement between TV AR surrogates and TIV surrogates in about a quarter of the series, suggesting that nonstationarity may affect HRV recordings and bias the outcome of the traditional surrogate-based nonlinearity test.
Woźniak, M.; Smołka, M.; Cortes, Adriano Mauricio; Paszyński, M.; Schaefer, R.
2016-01-01
We study the features of a new mixed integration scheme dedicated to solving the non-stationary variational problems. The scheme is composed of the FEM approximation with respect to the space variable coupled with a 3-leveled time integration scheme
International Nuclear Information System (INIS)
Li, C.; Su, W.; Fang, C.; Zhong, S. J.; Wang, L.
2014-01-01
We present a study of the waiting time distributions (WTDs) of solar energetic particle (SEP) events observed with the spacecraft WIND and GOES. The WTDs of both solar electron events (SEEs) and solar proton events (SPEs) display a power-law tail of ∼Δt –γ . The SEEs display a broken power-law WTD. The power-law index is γ 1 = 0.99 for the short waiting times (<70 hr) and γ 2 = 1.92 for large waiting times (>100 hr). The break of the WTD of SEEs is probably due to the modulation of the corotating interaction regions. The power-law index, γ ∼ 1.82, is derived for the WTD of the SPEs which is consistent with the WTD of type II radio bursts, indicating a close relationship between the shock wave and the production of energetic protons. The WTDs of SEP events can be modeled with a non-stationary Poisson process, which was proposed to understand the waiting time statistics of solar flares. We generalize the method and find that, if the SEP event rate λ = 1/Δt varies as the time distribution of event rate f(λ) = Aλ –α exp (– βλ), the time-dependent Poisson distribution can produce a power-law tail WTD of ∼Δt α –3 , where 0 ≤ α < 2
Clustering of financial time series
D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo
2013-05-01
This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.
Blind Separation of Nonstationary Sources Based on Spatial Time-Frequency Distributions
Directory of Open Access Journals (Sweden)
Zhang Yimin
2006-01-01
Full Text Available Blind source separation (BSS based on spatial time-frequency distributions (STFDs provides improved performance over blind source separation methods based on second-order statistics, when dealing with signals that are localized in the time-frequency (t-f domain. In this paper, we propose the use of STFD matrices for both whitening and recovery of the mixing matrix, which are two stages commonly required in many BSS methods, to provide robust BSS performance to noise. In addition, a simple method is proposed to select the auto- and cross-term regions of time-frequency distribution (TFD. To further improve the BSS performance, t-f grouping techniques are introduced to reduce the number of signals under consideration, and to allow the receiver array to separate more sources than the number of array sensors, provided that the sources have disjoint t-f signatures. With the use of one or more techniques proposed in this paper, improved performance of blind separation of nonstationary signals can be achieved.
International Nuclear Information System (INIS)
Liu, Yangqing; Tan, Yi; Xie, Huiqiao; Wang, Wenhao; Gao, Zhe
2014-01-01
An improved Hilbert-Huang transform method is developed to the time-frequency analysis of non-stationary signals in tokamak plasmas. Maximal overlap discrete wavelet packet transform rather than wavelet packet transform is proposed as a preprocessor to decompose a signal into various narrow-band components. Then, a correlation coefficient based selection method is utilized to eliminate the irrelevant intrinsic mode functions obtained from empirical mode decomposition of those narrow-band components. Subsequently, a time varying vector autoregressive moving average model instead of Hilbert spectral analysis is performed to compute the Hilbert spectrum, i.e., a three-dimensional time-frequency distribution of the signal. The feasibility and effectiveness of the improved Hilbert-Huang transform method is demonstrated by analyzing a non-stationary simulated signal and actual experimental signals in fusion plasmas
Bi, Chuan-Xing; Geng, Lin; Zhang, Xiao-Zheng
2016-05-01
In the sound field with multiple non-stationary sources, the measured pressure is the sum of the pressures generated by all sources, and thus cannot be used directly for studying the vibration and sound radiation characteristics of every source alone. This paper proposes a separation model based on the interpolated time-domain equivalent source method (ITDESM) to separate the pressure field belonging to every source from the non-stationary multi-source sound field. In the proposed method, ITDESM is first extended to establish the relationship between the mixed time-dependent pressure and all the equivalent sources distributed on every source with known location and geometry information, and all the equivalent source strengths at each time step are solved by an iterative solving process; then, the corresponding equivalent source strengths of one interested source are used to calculate the pressure field generated by that source alone. Numerical simulation of two baffled circular pistons demonstrates that the proposed method can be effective in separating the non-stationary pressure generated by every source alone in both time and space domains. An experiment with two speakers in a semi-anechoic chamber further evidences the effectiveness of the proposed method.
Information retrieval for nonstationary data records
Su, M. Y.
1971-01-01
A review and a critical discussion are made on the existing methods for analysis of nonstationary time series, and a new algorithm for splitting nonstationary time series, is applied to the analysis of sunspot data.
A Non-Stationary 1981–2012 AVHRR NDVI3g Time Series
Directory of Open Access Journals (Sweden)
Jorge E. Pinzon
2014-07-01
Full Text Available The NDVI3g time series is an improved 8-km normalized difference vegetation index (NDVI data set produced from Advanced Very High Resolution Radiometer (AVHRR instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of ± 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.
A Non-Stationary 1981-2012 AVHRR NDVI(sub 3g) Time Series
Pinzon, Jorge E.; Tucker, Compton J.
2014-01-01
The NDVI(sub 3g) time series is an improved 8-km normalized difference vegetation index (NDVI) data set produced from Advanced Very High Resolution Radiometer (AVHRR) instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA) and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of plus or minus 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.
Parametric modelling of nonstationary platform deck motions
Digital Repository Service at National Institute of Oceanography (India)
Mandal, S.
with fast Fourier transform spectra and show good agreement. However, the higher order maximum entropy model can be used for better representation of nonstationary motions. This method also reduces long time series of nonstationary offshore data into a few...
A Seasonal Time-Series Model Based on Gene Expression Programming for Predicting Financial Distress
Directory of Open Access Journals (Sweden)
Ching-Hsue Cheng
2018-01-01
Full Text Available The issue of financial distress prediction plays an important and challenging research topic in the financial field. Currently, there have been many methods for predicting firm bankruptcy and financial crisis, including the artificial intelligence and the traditional statistical methods, and the past studies have shown that the prediction result of the artificial intelligence method is better than the traditional statistical method. Financial statements are quarterly reports; hence, the financial crisis of companies is seasonal time-series data, and the attribute data affecting the financial distress of companies is nonlinear and nonstationary time-series data with fluctuations. Therefore, this study employed the nonlinear attribute selection method to build a nonlinear financial distress prediction model: that is, this paper proposed a novel seasonal time-series gene expression programming model for predicting the financial distress of companies. The proposed model has several advantages including the following: (i the proposed model is different from the previous models lacking the concept of time series; (ii the proposed integrated attribute selection method can find the core attributes and reduce high dimensional data; and (iii the proposed model can generate the rules and mathematical formulas of financial distress for providing references to the investors and decision makers. The result shows that the proposed method is better than the listing classifiers under three criteria; hence, the proposed model has competitive advantages in predicting the financial distress of companies.
A Seasonal Time-Series Model Based on Gene Expression Programming for Predicting Financial Distress
2018-01-01
The issue of financial distress prediction plays an important and challenging research topic in the financial field. Currently, there have been many methods for predicting firm bankruptcy and financial crisis, including the artificial intelligence and the traditional statistical methods, and the past studies have shown that the prediction result of the artificial intelligence method is better than the traditional statistical method. Financial statements are quarterly reports; hence, the financial crisis of companies is seasonal time-series data, and the attribute data affecting the financial distress of companies is nonlinear and nonstationary time-series data with fluctuations. Therefore, this study employed the nonlinear attribute selection method to build a nonlinear financial distress prediction model: that is, this paper proposed a novel seasonal time-series gene expression programming model for predicting the financial distress of companies. The proposed model has several advantages including the following: (i) the proposed model is different from the previous models lacking the concept of time series; (ii) the proposed integrated attribute selection method can find the core attributes and reduce high dimensional data; and (iii) the proposed model can generate the rules and mathematical formulas of financial distress for providing references to the investors and decision makers. The result shows that the proposed method is better than the listing classifiers under three criteria; hence, the proposed model has competitive advantages in predicting the financial distress of companies. PMID:29765399
A Seasonal Time-Series Model Based on Gene Expression Programming for Predicting Financial Distress.
Cheng, Ching-Hsue; Chan, Chia-Pang; Yang, Jun-He
2018-01-01
The issue of financial distress prediction plays an important and challenging research topic in the financial field. Currently, there have been many methods for predicting firm bankruptcy and financial crisis, including the artificial intelligence and the traditional statistical methods, and the past studies have shown that the prediction result of the artificial intelligence method is better than the traditional statistical method. Financial statements are quarterly reports; hence, the financial crisis of companies is seasonal time-series data, and the attribute data affecting the financial distress of companies is nonlinear and nonstationary time-series data with fluctuations. Therefore, this study employed the nonlinear attribute selection method to build a nonlinear financial distress prediction model: that is, this paper proposed a novel seasonal time-series gene expression programming model for predicting the financial distress of companies. The proposed model has several advantages including the following: (i) the proposed model is different from the previous models lacking the concept of time series; (ii) the proposed integrated attribute selection method can find the core attributes and reduce high dimensional data; and (iii) the proposed model can generate the rules and mathematical formulas of financial distress for providing references to the investors and decision makers. The result shows that the proposed method is better than the listing classifiers under three criteria; hence, the proposed model has competitive advantages in predicting the financial distress of companies.
Frontiers in Time Series and Financial Econometrics
Ling, S.; McAleer, M.J.; Tong, H.
2015-01-01
__Abstract__ Two of the fastest growing frontiers in econometrics and quantitative finance are time series and financial econometrics. Significant theoretical contributions to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time series analysis. The purpose of this special issue of the journal on “Frontiers in Time Series and Financial Econometrics” is to highlight several areas of research by leading academics in which novel methods have contrib...
The role of initial values in nonstationary fractional time series models
DEFF Research Database (Denmark)
Johansen, Søren; Nielsen, Morten Ørregaard
We consider the nonstationary fractional model $\\Delta^{d}X_{t}=\\varepsilon _{t}$ with $\\varepsilon_{t}$ i.i.d.$(0,\\sigma^{2})$ and $d>1/2$. We derive an analytical expression for the main term of the asymptotic bias of the maximum likelihood estimator of $d$ conditional on initial values, and we...... discuss the role of the initial values for the bias. The results are partially extended to other fractional models, and three different applications of the theoretical results are given....
A New Method for Non-linear and Non-stationary Time Series Analysis:
The Hilbert Spectral Analysis
CERN. Geneva
2000-01-01
A new method for analysing non-linear and non-stationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero crossing and extreme, and also having symmetric envelopes defined by the local maximal and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to non-linear and non-stationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. Classical non-l...
Hammouda, Imen; Mihoubi, Daoued
2017-12-01
This work deals with a numerical study of the response of a porcelain slab when subjected to convective drying in stationary and non-stationary conditions. The used model describes heat, mass, and momentum transfers is applied to an unsaturated viscoelastic medium described by a Maxwell model. The numerical code allows us to determine the effect of the surrounding air temperature on drying kinetics and on mechanical stress intensities. Von Mises stresses are analysed in order to foresee an eventual damage that may occur during drying. Simulation results for several temperatures in the range of [30 °C, 90 °C] shows that for the temperature from 30 °C to 60 °C, Von Mises stresses are always lower than the yield strength. But above 70 °C, Von Mises stresses are higher than the ultimate strength, and consequently there is a risk of crack at the end of the constant drying rate period. The idea proposed in this work is to integrate a reducing temperature phase when the predicted Von Mises stress intensity exceeds the admissible stress. Simulation results shows that a non-stationary convective drying (90-60 °C) allows us to optimize costs and quality by reducing the drying time and maintaining Von Mises stress values under the admissible stress.
Real-time reservoir operation considering non-stationary inflow prediction
Zhao, J.; Xu, W.; Cai, X.; Wang, Z.
2011-12-01
Stationarity of inflow has been a basic assumption for reservoir operation rule design, which is now facing challenges due to climate change and human interferences. This paper proposes a modeling framework to incorporate non-stationary inflow prediction for optimizing the hedging operation rule of large reservoirs with multiple-year flow regulation capacity. A multi-stage optimization model is formulated and a solution algorithm based on the optimality conditions is developed to incorporate non-stationary annual inflow prediction through a rolling, dynamic framework that updates the prediction from period to period and adopt the updated prediction in reservoir operation decision. The prediction model is ARIMA(4,1,0), in which parameter 4 stands for the order of autoregressive, 1 represents a linear trend, and 0 is the order of moving average. The modeling framework and solution algorithm is applied to the Miyun reservoir in China, determining a yearly operating schedule during the period from 1996 to 2009, during which there was a significant declining trend of reservoir inflow. Different operation policy scenarios are modeled, including standard operation policy (SOP, matching the current demand as much as possible), hedging rule (i.e., leaving a certain amount of water for future to avoid large risk of water deficit) with forecast from ARIMA (HR-1), hedging (HR) with perfect forecast (HR-2 ). Compared to the results of these scenarios to that of the actual reservoir operation (AO), the utility of the reservoir operation under HR-1 is 3.0% lower than HR-2, but 3.7% higher than the AO and 14.4% higher than SOP. Note that the utility under AO is 10.3% higher than that under SOP, which shows that a certain level of hedging under some inflow prediction or forecast was used in the real-world operation. Moreover, the impacts of discount rate and forecast uncertainty level on the operation will be discussed.
Woźniak, M.
2016-06-02
We study the features of a new mixed integration scheme dedicated to solving the non-stationary variational problems. The scheme is composed of the FEM approximation with respect to the space variable coupled with a 3-leveled time integration scheme with a linearized right-hand side operator. It was applied in solving the Cahn-Hilliard parabolic equation with a nonlinear, fourth-order elliptic part. The second order of the approximation along the time variable was proven. Moreover, the good scalability of the software based on this scheme was confirmed during simulations. We verify the proposed time integration scheme by monitoring the Ginzburg-Landau free energy. The numerical simulations are performed by using a parallel multi-frontal direct solver executed over STAMPEDE Linux cluster. Its scalability was compared to the results of the three direct solvers, including MUMPS, SuperLU and PaSTiX.
Forootan, Ehsan; Kusche, Jürgen
2016-04-01
Geodetic/geophysical observations, such as the time series of global terrestrial water storage change or sea level and temperature change, represent samples of physical processes and therefore contain information about complex physical interactionswith many inherent time scales. Extracting relevant information from these samples, for example quantifying the seasonality of a physical process or its variability due to large-scale ocean-atmosphere interactions, is not possible by rendering simple time series approaches. In the last decades, decomposition techniques have found increasing interest for extracting patterns from geophysical observations. Traditionally, principal component analysis (PCA) and more recently independent component analysis (ICA) are common techniques to extract statistical orthogonal (uncorrelated) and independent modes that represent the maximum variance of observations, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the auto-covariance matrix or diagonalizing higher (than two)-order statistical tensors from centered time series. However, the stationary assumption is obviously not justifiable for many geophysical and climate variables even after removing cyclic components e.g., the seasonal cycles. In this paper, we present a new decomposition method, the complex independent component analysis (CICA, Forootan, PhD-2014), which can be applied to extract to non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA (Forootan and Kusche, JoG-2012), where we (i) define a new complex data set using a Hilbert transformation. The complex time series contain the observed values in their real part, and the temporal rate of variability in their imaginary part. (ii) An ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex data set in (i
International Nuclear Information System (INIS)
Kuznetsov, Yu.N.; Kalinin, E.I.; Naumov, M.A.
1980-01-01
The effect of variability of heat duty on the characteristics of heat exchange in ring channels and rod bundles is investigated with analytical methods. The plotting of calculation formulae for non-stationary heat exchange in an annular channel at a jump of heat duty is carried out on the basis of the method of the effect function. The formulae obtained permit to accomplish technical calculations of the processes of non-stationary heat exchange in annular channels in the case of any alterations of thermal duty in time, at any moment of time, for any channel cross section (including the entrance heat section) in a wide range of geometric and regime parameters of the turbulent current of a coolant. According to preliminary estimates, calculation results differ from the results oi a numerical solution less than 5%. The approach considered permits to transfer the data on the non-stationary heat exchange in annular channels in the case of changing the heat duty in time, in the case of a non-stationary heat exchange in longitudinally flown not very dense and infinite rod bundles
Nonstationary quantum mechanics
International Nuclear Information System (INIS)
Todorov, N.S.
1981-01-01
It is shown that the nonstationary Schroedinger equation does not satisfy a well-known adiabatical principle in thermodynamics. A ''renormalization procedure'' based on the possible existence of a time-irreversible basic evolution equation is proposed with the help of which one comes to agreement in a variety of specific cases of an adiabatic inclusion of a perturbing potential. The ideology of the present article rests essentially on the ideology of the preceding articles, in particular article I. (author)
Forecasting Cryptocurrencies Financial Time Series
Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco
2018-01-01
This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely on Dynamic Model Averaging to combine a large set of univariate Dynamic Linear Models and several multivariate Vector Autoregressive models with different forms of time variation. We find statistical si...
Forecasting Cryptocurrencies Financial Time Series
DEFF Research Database (Denmark)
Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco
2018-01-01
This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely...
Time averaging, ageing and delay analysis of financial time series
Cherstvy, Andrey G.; Vinod, Deepak; Aghion, Erez; Chechkin, Aleksei V.; Metzler, Ralf
2017-06-01
We introduce three strategies for the analysis of financial time series based on time averaged observables. These comprise the time averaged mean squared displacement (MSD) as well as the ageing and delay time methods for varying fractions of the financial time series. We explore these concepts via statistical analysis of historic time series for several Dow Jones Industrial indices for the period from the 1960s to 2015. Remarkably, we discover a simple universal law for the delay time averaged MSD. The observed features of the financial time series dynamics agree well with our analytical results for the time averaged measurables for geometric Brownian motion, underlying the famed Black-Scholes-Merton model. The concepts we promote here are shown to be useful for financial data analysis and enable one to unveil new universal features of stock market dynamics.
Melkonian, D; Korner, A; Meares, R; Bahramali, H
2012-10-01
A novel method of the time-frequency analysis of non-stationary heart rate variability (HRV) is developed which introduces the fragmentary spectrum as a measure that brings together the frequency content, timing and duration of HRV segments. The fragmentary spectrum is calculated by the similar basis function algorithm. This numerical tool of the time to frequency and frequency to time Fourier transformations accepts both uniform and non-uniform sampling intervals, and is applicable to signal segments of arbitrary length. Once the fragmentary spectrum is calculated, the inverse transform recovers the original signal and reveals accuracy of spectral estimates. Numerical experiments show that discontinuities at the boundaries of the succession of inter-beat intervals can cause unacceptable distortions of the spectral estimates. We have developed a measure that we call the "RR deltagram" as a form of the HRV data that minimises spectral errors. The analysis of the experimental HRV data from real-life and controlled breathing conditions suggests transient oscillatory components as functionally meaningful elements of highly complex and irregular patterns of HRV. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Yubo Wang
2017-06-01
Full Text Available It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC. In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976 ratio and outperforms existing methods such as short-time Fourier transfrom (STFT, continuous Wavelet transform (CWT and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.
Wang, Yubo; Veluvolu, Kalyana C
2017-06-14
It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC). In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976) ratio and outperforms existing methods such as short-time Fourier transfrom (STFT), continuous Wavelet transform (CWT) and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.
International Nuclear Information System (INIS)
Liu, Jie
2015-01-01
This Ph. D. work is motivated by the possibility of monitoring the conditions of components of energy systems for their extended and safe use, under proper practice of operation and adequate policies of maintenance. The aim is to develop a Support Vector Regression (SVR)-based framework for predicting time series data under stationary/nonstationary environmental and operational conditions. Single SVR and SVR-based ensemble approaches are developed to tackle the prediction problem based on both small and large datasets. Strategies are proposed for adaptively updating the single SVR and SVR-based ensemble models in the existence of pattern drifts. Comparisons with other online learning approaches for kernel-based modelling are provided with reference to time series data from a critical component in Nuclear Power Plants (NPPs) provided by Electricite de France (EDF). The results show that the proposed approaches achieve comparable prediction results, considering the Mean Squared Error (MSE) and Mean Relative Error (MRE), in much less computation time. Furthermore, by analyzing the geometrical meaning of the Feature Vector Selection (FVS) method proposed in the literature, a novel geometrically interpretable kernel method, named Reduced Rank Kernel Ridge Regression-II (RRKRR-II), is proposed to describe the linear relations between a predicted value and the predicted values of the Feature Vectors (FVs) selected by FVS. Comparisons with several kernel methods on a number of public datasets prove the good prediction accuracy and the easy-of-tuning of the hyper-parameters of RRKRR-II. (author)
Martinez, Josue G.; Bohn, Kirsten M.; Carroll, Raymond J.; Morris, Jeffrey S.
2013-01-01
We describe a new approach to analyze chirp syllables of free-tailed bats from two regions of Texas in which they are predominant: Austin and College Station. Our goal is to characterize any systematic regional differences in the mating chirps and assess whether individual bats have signature chirps. The data are analyzed by modeling spectrograms of the chirps as responses in a Bayesian functional mixed model. Given the variable chirp lengths, we compute the spectrograms on a relative time scale interpretable as the relative chirp position, using a variable window overlap based on chirp length. We use 2D wavelet transforms to capture correlation within the spectrogram in our modeling and obtain adaptive regularization of the estimates and inference for the regions-specific spectrograms. Our model includes random effect spectrograms at the bat level to account for correlation among chirps from the same bat, and to assess relative variability in chirp spectrograms within and between bats. The modeling of spectrograms using functional mixed models is a general approach for the analysis of replicated nonstationary time series, such as our acoustical signals, to relate aspects of the signals to various predictors, while accounting for between-signal structure. This can be done on raw spectrograms when all signals are of the same length, and can be done using spectrograms defined on a relative time scale for signals of variable length in settings where the idea of defining correspondence across signals based on relative position is sensible.
Martinez, Josue G.
2013-06-01
We describe a new approach to analyze chirp syllables of free-tailed bats from two regions of Texas in which they are predominant: Austin and College Station. Our goal is to characterize any systematic regional differences in the mating chirps and assess whether individual bats have signature chirps. The data are analyzed by modeling spectrograms of the chirps as responses in a Bayesian functional mixed model. Given the variable chirp lengths, we compute the spectrograms on a relative time scale interpretable as the relative chirp position, using a variable window overlap based on chirp length. We use 2D wavelet transforms to capture correlation within the spectrogram in our modeling and obtain adaptive regularization of the estimates and inference for the regions-specific spectrograms. Our model includes random effect spectrograms at the bat level to account for correlation among chirps from the same bat, and to assess relative variability in chirp spectrograms within and between bats. The modeling of spectrograms using functional mixed models is a general approach for the analysis of replicated nonstationary time series, such as our acoustical signals, to relate aspects of the signals to various predictors, while accounting for between-signal structure. This can be done on raw spectrograms when all signals are of the same length, and can be done using spectrograms defined on a relative time scale for signals of variable length in settings where the idea of defining correspondence across signals based on relative position is sensible.
Precarious Learning and Labour in Financialized Times
Directory of Open Access Journals (Sweden)
Jamie Magnusson
2013-07-01
Full Text Available Our current globalized economic regimes of financialized capital have systematically altered relations of learning and labour through the dynamics of precarity, debt, and the political economy of new wars. The risks of these regimes are absorbed unevenly across transnational landscapes, creating cartographies of violence and dispossession, particularly among youth, indigenous, working class, and racialized women. Presently there is surprisingly little discussion on the relevance of financialization for adult educators. Transnational resistances organizing against neoliberal restructuring, austerity policies, and debt crises are emerging at the same time that massive investments are being made into homeland security and the carceral state. This paper opens up discussion on the implications of financialized times for educators, and develops an analytic framework for examining how these global realities are best addressed at local sites of adult and higher education.
Shi, Wei; Xia, Jun
2017-02-01
Water quality risk management is a global hot research linkage with the sustainable water resource development. Ammonium nitrogen (NH 3 -N) and permanganate index (COD Mn ) as the focus indicators in Huai River Basin, are selected to reveal their joint transition laws based on Markov theory. The time-varying moments model with either time or land cover index as explanatory variables is applied to build the time-varying marginal distributions of water quality time series. Time-varying copula model, which takes the non-stationarity in the marginal distribution and/or the time variation in dependence structure between water quality series into consideration, is constructed to describe a bivariate frequency analysis for NH 3 -N and COD Mn series at the same monitoring gauge. The larger first-order Markov joint transition probability indicates water quality state Class V w , Class IV and Class III will occur easily in the water body of Bengbu Sluice. Both marginal distribution and copula models are nonstationary, and the explanatory variable time yields better performance than land cover index in describing the non-stationarities in the marginal distributions. In modelling the dependence structure changes, time-varying copula has a better fitting performance than the copula with the constant or the time-trend dependence parameter. The largest synchronous encounter risk probability of NH 3 -N and COD Mn simultaneously reaching Class V is 50.61%, while the asynchronous encounter risk probability is largest when NH 3 -N and COD Mn is inferior to class V and class IV water quality standards, respectively.
Enhanced tunneling through nonstationary barriers
International Nuclear Information System (INIS)
Palomares-Baez, J. P.; Rodriguez-Lopez, J. L.; Ivlev, B.
2007-01-01
Quantum tunneling through a nonstationary barrier is studied analytically and by a direct numerical solution of Schroedinger equation. Both methods are in agreement and say that the main features of the phenomenon can be described in terms of classical trajectories which are solutions of Newton's equation in complex time. The probability of tunneling is governed by analytical properties of a time-dependent perturbation and the classical trajectory in the plane of complex time. Some preliminary numerical calculations of Euclidean resonance (an easy penetration through a classical nonstationary barrier due to an underbarrier interference) are presented
Analyzing Developmental Processes on an Individual Level Using Nonstationary Time Series Modeling
Molenaar, Peter C. M.; Sinclair, Katerina O.; Rovine, Michael J.; Ram, Nilam; Corneal, Sherry E.
2009-01-01
Individuals change over time, often in complex ways. Generally, studies of change over time have combined individuals into groups for analysis, which is inappropriate in most, if not all, studies of development. The authors explain how to identify appropriate levels of analysis (individual vs. group) and demonstrate how to estimate changes in…
DEFF Research Database (Denmark)
Vincent, Claire Louise; Giebel, Gregor; Pinson, Pierre
2010-01-01
a 4-yr time series of 10-min wind speed observations. An adaptive spectral analysis method called the Hilbert–Huang transform is chosen for the analysis, because the nonstationarity of time series of wind speed observations means that they are not well described by a global spectral analysis method...... such as the Fourier transform. The Hilbert–Huang transform is a local method based on a nonparametric and empirical decomposition of the data followed by calculation of instantaneous amplitudes and frequencies using the Hilbert transform. The Hilbert–Huang transformed 4-yr time series is averaged and summarized...
Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.
Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis
2018-01-01
Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.
Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene
2015-06-01
When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.
D1.4 -- Short Report on Models That Incorporate Non-stationary Time Variant Effects
DEFF Research Database (Denmark)
Lostanlen, Yves; Pedersen, Troels; Steinboeck, Gerhard
-to-indoor environments are presented. Furthermore, the impact of human activity on the time variation of the radio channel is investigated and first simulation results are presented. Movement models, which include realistic interaction between nodes, are part of current research activities....
Measuring multiscaling in financial time-series
International Nuclear Information System (INIS)
Buonocore, R.J.; Aste, T.; Di Matteo, T.
2016-01-01
We discuss the origin of multiscaling in financial time-series and investigate how to best quantify it. Our methodology consists in separating the different sources of measured multifractality by analyzing the multi/uni-scaling behavior of synthetic time-series with known properties. We use the results from the synthetic time-series to interpret the measure of multifractality of real log-returns time-series. The main finding is that the aggregation horizon of the returns can introduce a strong bias effect on the measure of multifractality. This effect can become especially important when returns distributions have power law tails with exponents in the range (2, 5). We discuss the right aggregation horizon to mitigate this bias.
Financial Times Global Pharmaceutical & Biotechnology Conference 2009.
Scattereggia, Jennifer
2010-01-01
The Financial Times Global Pharmaceutical & Biotechnology conference, held in London, included topics covering the current and future challenges confronting the pharma and biotech industry, and presented possible solutions to those challenges. This conference report highlights selected presentations on the industry challenges for big pharma companies, diversification as a solution to industry problems, overcoming challenges with collaborations and M&As, and the role of emerging markets in the pharma industry. Other subjects discussed included the expected impact of personalized medicine on the industry, the entry of big pharma into the generics market and the problems that are confronting the small pharma and biotech industry.
Wavelet analysis for nonstationary signals
International Nuclear Information System (INIS)
Penha, Rosani Maria Libardi da
1999-01-01
Mechanical vibration signals play an important role in anomalies identification resulting of equipment malfunctioning. Traditionally, Fourier spectral analysis is used where the signals are assumed to be stationary. However, occasional transient impulses and start-up process are examples of nonstationary signals that can be found in mechanical vibrations. These signals can provide important information about the equipment condition, as early fault detection. The Fourier analysis can not adequately be applied to nonstationary signals because the results provide data about the frequency composition averaged over the duration of the signal. In this work, two methods for nonstationary signal analysis are used: Short Time Fourier Transform (STFT) and wavelet transform. The STFT is a method of adapting Fourier spectral analysis for nonstationary application to time-frequency domain. To have a unique resolution throughout the entire time-frequency domain is its main limitation. The wavelet transform is a new analysis technique suitable to nonstationary signals, which handles the STFT drawbacks, providing multi-resolution frequency analysis and time localization in a unique time-scale graphic. The multiple frequency resolutions are obtained by scaling (dilatation/compression) the wavelet function. A comparison of the conventional Fourier transform, STFT and wavelet transform is made applying these techniques to: simulated signals, arrangement rotor rig vibration signal and rotate machine vibration signal Hanning window was used to STFT analysis. Daubechies and harmonic wavelets were used to continuos, discrete and multi-resolution wavelet analysis. The results show the Fourier analysis was not able to detect changes in the signal frequencies or discontinuities. The STFT analysis detected the changes in the signal frequencies, but with time-frequency resolution problems. The wavelet continuos and discrete transform demonstrated to be a high efficient tool to detect
On the non-stationarity of financial time series: impact on optimal portfolio selection
International Nuclear Information System (INIS)
Livan, Giacomo; Inoue, Jun-ichi; Scalas, Enrico
2012-01-01
We investigate the possible drawbacks of employing the standard Pearson estimator to measure correlation coefficients between financial stocks in the presence of non-stationary behavior, and we provide empirical evidence against the well-established common knowledge that using longer price time series provides better, more accurate, correlation estimates. Then, we investigate the possible consequences of instabilities in empirical correlation coefficient measurements on optimal portfolio selection. We rely on previously published works which provide a framework allowing us to take into account possible risk underestimations due to the non-optimality of the portfolio weights being used in order to distinguish such non-optimality effects from risk underestimations genuinely due to non-stationarities. We interpret such results in terms of instabilities in some spectral properties of portfolio correlation matrices. (paper)
Frontiers in Time Series and Financial Econometrics : An overview
S. Ling (Shiqing); M.J. McAleer (Michael); H. Tong (Howell)
2015-01-01
markdownabstract__Abstract__ Two of the fastest growing frontiers in econometrics and quantitative finance are time series and financial econometrics. Significant theoretical contributions to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time
Frontiers in Time Series and Financial Econometrics: An Overview
S. Ling (Shiqing); M.J. McAleer (Michael); H. Tong (Howell)
2015-01-01
markdownabstract__Abstract__ Two of the fastest growing frontiers in econometrics and quantitative finance are time series and financial econometrics. Significant theoretical contributions to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time
Directory of Open Access Journals (Sweden)
S. P. Arunachalam
2018-01-01
Full Text Available Analysis of biomedical signals can yield invaluable information for prognosis, diagnosis, therapy evaluation, risk assessment, and disease prevention which is often recorded as short time series data that challenges existing complexity classification algorithms such as Shannon entropy (SE and other techniques. The purpose of this study was to improve previously developed multiscale entropy (MSE technique by incorporating nearest-neighbor moving-average kernel, which can be used for analysis of nonlinear and non-stationary short time series physiological data. The approach was tested for robustness with respect to noise analysis using simulated sinusoidal and ECG waveforms. Feasibility of MSE to discriminate between normal sinus rhythm (NSR and atrial fibrillation (AF was tested on a single-lead ECG. In addition, the MSE algorithm was applied to identify pivot points of rotors that were induced in ex vivo isolated rabbit hearts. The improved MSE technique robustly estimated the complexity of the signal compared to that of SE with various noises, discriminated NSR and AF on single-lead ECG, and precisely identified the pivot points of ex vivo rotors by providing better contrast between the rotor core and the peripheral region. The improved MSE technique can provide efficient complexity analysis of variety of nonlinear and nonstationary short-time biomedical signals.
Vaughan, Adam; Bohac, Stanislav V
2015-10-01
Fuel efficient Homogeneous Charge Compression Ignition (HCCI) engine combustion timing predictions must contend with non-linear chemistry, non-linear physics, period doubling bifurcation(s), turbulent mixing, model parameters that can drift day-to-day, and air-fuel mixture state information that cannot typically be resolved on a cycle-to-cycle basis, especially during transients. In previous work, an abstract cycle-to-cycle mapping function coupled with ϵ-Support Vector Regression was shown to predict experimentally observed cycle-to-cycle combustion timing over a wide range of engine conditions, despite some of the aforementioned difficulties. The main limitation of the previous approach was that a partially acasual randomly sampled training dataset was used to train proof of concept offline predictions. The objective of this paper is to address this limitation by proposing a new online adaptive Extreme Learning Machine (ELM) extension named Weighted Ring-ELM. This extension enables fully causal combustion timing predictions at randomly chosen engine set points, and is shown to achieve results that are as good as or better than the previous offline method. The broader objective of this approach is to enable a new class of real-time model predictive control strategies for high variability HCCI and, ultimately, to bring HCCI's low engine-out NOx and reduced CO2 emissions to production engines. Copyright © 2015 Elsevier Ltd. All rights reserved.
Nonstationary quantum mechanics
International Nuclear Information System (INIS)
Todorov, N.S.
1981-01-01
Some peculiarities of the results of nonstationary perturbation theory in the presence of a degenerate continuous energy spectrum are considered. Their relevance to the ideology of the preceding articles in this series is discussed. (author)
The Time Value of Money in Financial Management
Directory of Open Access Journals (Sweden)
Munteanu Irena
2017-01-01
Full Text Available The Time Value of Money is a important concept in financial management. The Time Value of Money (TVM includes the concepts of future value and discounted value. It is mandatory for a financial professional to know and operate the specific techniques of TVM. Within the present article we present the basic notions and illustrate their application in the field of investment projects. The case studies presented are valuable for an efficient financial management.
The Human Side of Financial Hard Times
Breneman, David W.
2009-01-01
The current downturn has the potential to be more severe and longer lasting than the recessions of the 1970s, '80s, '90s, and early 2000s. By now, rivers of ink have been spilled documenting the financial and economic crisis afflicting the United States and much of the globe. While numerous articles have examined the impact on higher-education…
Precarious Learning and Labour in Financialized Times
Magnusson, Jamie
2013-01-01
Our current globalized economic regimes of financialized capital have systematically altered relations of learning and labour through the dynamics of precarity, debt, and the political economy of new wars. The risks of these regimes are absorbed unevenly across transnational landscapes, creating cartographies of violence and dispossession,…
Institutional Management of Core Facilities during Challenging Financial Times
Haley, Rand
2011-01-01
The economic downturn is likely to have lasting effects on institutions of higher education, prioritizing proactive institutional leadership and planning. Although by design, core research facilities are more efficient and effective than supporting individual pieces of research equipment, cores can have significant underlying financial requirements and challenges. This paper explores several possible institutional approaches to managing core facilities during challenging financial times.
Institutional management of core facilities during challenging financial times.
Haley, Rand
2011-12-01
The economic downturn is likely to have lasting effects on institutions of higher education, prioritizing proactive institutional leadership and planning. Although by design, core research facilities are more efficient and effective than supporting individual pieces of research equipment, cores can have significant underlying financial requirements and challenges. This paper explores several possible institutional approaches to managing core facilities during challenging financial times.
Sparse Bayesian Learning for Nonstationary Data Sources
Fujimaki, Ryohei; Yairi, Takehisa; Machida, Kazuo
This paper proposes an online Sparse Bayesian Learning (SBL) algorithm for modeling nonstationary data sources. Although most learning algorithms implicitly assume that a data source does not change over time (stationary), one in the real world usually does due to such various factors as dynamically changing environments, device degradation, sudden failures, etc (nonstationary). The proposed algorithm can be made useable for stationary online SBL by setting time decay parameters to zero, and as such it can be interpreted as a single unified framework for online SBL for use with stationary and nonstationary data sources. Tests both on four types of benchmark problems and on actual stock price data have shown it to perform well.
Multiple Time Series Ising Model for Financial Market Simulations
International Nuclear Information System (INIS)
Takaishi, Tetsuya
2015-01-01
In this paper we propose an Ising model which simulates multiple financial time series. Our model introduces the interaction which couples to spins of other systems. Simulations from our model show that time series exhibit the volatility clustering that is often observed in the real financial markets. Furthermore we also find non-zero cross correlations between the volatilities from our model. Thus our model can simulate stock markets where volatilities of stocks are mutually correlated
Zhou, Peng; Peng, Zhike; Chen, Shiqian; Yang, Yang; Zhang, Wenming
2018-06-01
With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time-frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.
The future of financial reporting 2009 : a time of global financial crisis.
Jones, M.; Slack, R.E.
2009-01-01
A discussion paper based on the British Accounting Association Financial Accounting and Reporting Special Interest Group (FARSIG) Colloquium, 9 January 2009. The theme of the future of financial reporting at a time of global crisis was very topical. The papers and discussion, well captured in this summary, set out the main thoughts at that point, both on the role of accounting in the crisis and the impact of the crisis on accounting. The factors which provoked a crisis on that scale and t...
Directory of Open Access Journals (Sweden)
Charles Onyutha
2017-10-01
Full Text Available Some of the problems in drought assessments are that: analyses tend to focus on coarse temporal scales, many of the methods yield skewed indices, a few terminologies are ambiguously used, and analyses comprise an implicit assumption that the observations come from a stationary process. To solve these problems, this paper introduces non-stationary frequency analyses of quantiles. How to use non-parametric rescaling to obtain robust indices that are not (or minimally skewed is also introduced. To avoid ambiguity, some concepts on, e.g., incidence, extremity, etc., were revisited through shift from monthly to daily time scale. Demonstrations on the introduced methods were made using daily flow and precipitation insufficiency (precipitation minus potential evapotranspiration from the Blue Nile basin in Africa. Results show that, when a significant trend exists in extreme events, stationarity-based quantiles can be far different from those when non-stationarity is considered. The introduced non-parametric indices were found to closely agree with the well-known standardized precipitation evapotranspiration indices in many aspects but skewness. Apart from revisiting some concepts, the advantages of the use of fine instead of coarse time scales in drought assessment were given. The links for obtaining freely downloadable tools on how to implement the introduced methods were provided.
Financial times: Competing temporalities in the age of finance capitalism
Directory of Open Access Journals (Sweden)
Christian Kloeckner
2018-05-01
Full Text Available This special issue explores how finance deploys time, structures the future, and interacts with actors and institutions that sometimes function according to very different temporal regimes. Finance capitalism’s logic of recurrence, repetitive cycles, and successive ruptures has long been with us, but the essays in this special issue are particularly interested in how recent decades of intensified financialization have restructured temporal experience. They interrogate the production and dissemination of agency in an age of acceleration, risk, and uncertainty, asking how the temporality inscribed in financial transactions emerges from and simultaneously shapes individual and social practice. Topics covered range from the logic of finance and foundational concepts of financial theory to the intersection between objective structures and social practice, the role of literature, and finally questions of social insecurity, political action, and the possibility of resistance within a context of competing temporalities. In this introduction, the editors delineate some fundamental concepts and questions for our financial times.
Professional Development in Tough Financial Times
Gandel, Paul B.; Golden, Cynthia
2004-01-01
The authors asked a diverse cross-section of their colleagues how they were addressing professional development in tight economic times, when they are all being asked to work more effectively across organizational boundaries. While the survey was informal and not scientific, the authors found that many organizations have maintained strong…
Effect of long construction times on utility financial requirements
International Nuclear Information System (INIS)
Francis, J.M.
1981-01-01
It is well-known that long construction times significantly increase the cost of an individual nuclear plant. Long construction times, however, are not confined to either a single plant or a single utility. Rather, they apparently occur in almost all nuclear plants currently under construction. The total financial requirement to complete the 82 nuclear plants currently under construction was assessed. The analysis was performed assuming a construction time of ten years in one case, and six years in another. It was found that decreasing the construction time from ten to six years will reduce the financial requirements of the utility industry by $89 billion
Production, staff, working time and financial planning
Directory of Open Access Journals (Sweden)
Orlando Boiteux
2009-07-01
Full Text Available Aggregate planning can be a tool for coordinating the tactical decisions belonging to some functional areas of a company. This potential has been limited due to methodological and technical reasons, but nowadays it is possible to solve very sophisticated models integrating, with a high level of detail, a great number of decisions of several functional areas and that permit to include new management schemes. In this paper, a production, staff, working time and cash management model is introduced.
Multivariate time series analysis with R and financial applications
Tsay, Ruey S
2013-01-01
Since the publication of his first book, Analysis of Financial Time Series, Ruey Tsay has become one of the most influential and prominent experts on the topic of time series. Different from the traditional and oftentimes complex approach to multivariate (MV) time series, this sequel book emphasizes structural specification, which results in simplified parsimonious VARMA modeling and, hence, eases comprehension. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-worl
Financial time series analysis based on information categorization method
Tian, Qiang; Shang, Pengjian; Feng, Guochen
2014-12-01
The paper mainly applies the information categorization method to analyze the financial time series. The method is used to examine the similarity of different sequences by calculating the distances between them. We apply this method to quantify the similarity of different stock markets. And we report the results of similarity in US and Chinese stock markets in periods 1991-1998 (before the Asian currency crisis), 1999-2006 (after the Asian currency crisis and before the global financial crisis), and 2007-2013 (during and after global financial crisis) by using this method. The results show the difference of similarity between different stock markets in different time periods and the similarity of the two stock markets become larger after these two crises. Also we acquire the results of similarity of 10 stock indices in three areas; it means the method can distinguish different areas' markets from the phylogenetic trees. The results show that we can get satisfactory information from financial markets by this method. The information categorization method can not only be used in physiologic time series, but also in financial time series.
Parameterizing unconditional skewness in models for financial time series
DEFF Research Database (Denmark)
He, Changli; Silvennoinen, Annastiina; Teräsvirta, Timo
In this paper we consider the third-moment structure of a class of time series models. It is often argued that the marginal distribution of financial time series such as returns is skewed. Therefore it is of importance to know what properties a model should possess if it is to accommodate...
Theory of earthquakes interevent times applied to financial markets
Jagielski, Maciej; Kutner, Ryszard; Sornette, Didier
2017-10-01
We analyze the probability density function (PDF) of waiting times between financial loss exceedances. The empirical PDFs are fitted with the self-excited Hawkes conditional Poisson process with a long power law memory kernel. The Hawkes process is the simplest extension of the Poisson process that takes into account how past events influence the occurrence of future events. By analyzing the empirical data for 15 different financial assets, we show that the formalism of the Hawkes process used for earthquakes can successfully model the PDF of interevent times between successive market losses.
Financial Toxicity of Cancer Care: It's Time to Intervene.
Zafar, S Yousuf
2016-05-01
Evidence suggests that a considerably large proportion of cancer patients are affected by treatment-related financial harm. As medical debt grows for some with cancer, the downstream effects can be catastrophic, with a recent study suggesting a link between extreme financial distress and worse mortality. At least three factors might explain the relationship between extreme financial distress and greater risk of mortality: 1) overall poorer well-being, 2) impaired health-related quality of life, and 3) sub-par quality of care. While research has described the financial harm associated with cancer treatment, little has been done to effectively intervene on the problem. Long-term solutions must focus on policy changes to reduce unsustainable drug prices and promote innovative insurance models. In the mean time, patients continue to struggle with high out-of-pocket costs. For more immediate solutions, we should look to the oncologist and patient. Oncologists should focus on the value of care delivered, encourage patient engagement on the topic of costs, and be better educated on financial resources available to patients. For their part, patients need improved cost-related health literacy so they are aware of potential costs and resources, and research should focus on how patients define high-value care. With a growing list of financial side effects induced by cancer treatment, the time has come to intervene on the "financial toxicity" of cancer care. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Nonstationary oscillations in gyrotrons revisited
International Nuclear Information System (INIS)
Dumbrajs, O.; Kalis, H.
2015-01-01
Development of gyrotrons requires careful understanding of different regimes of gyrotron oscillations. It is known that in the planes of the generalized gyrotron variables: cyclotron resonance mismatch and dimensionless current or cyclotron resonance mismatch and dimensionless interaction length complicated alternating sequences of regions of stationary, periodic, automodulation, and chaotic oscillations exist. In the past, these regions were investigated on the supposition that the transit time of electrons through the interaction space is much shorter than the cavity decay time. This assumption is valid for short and/or high diffraction quality resonators. However, in the case of long and/or low diffraction quality resonators, which are often utilized, this assumption is no longer valid. In such a case, a different mathematical formalism has to be used for studying nonstationary oscillations. One example of such a formalism is described in the present paper
International Nuclear Information System (INIS)
Nikitin, N. V.; Sotnikov, V.P.; Toms, K. S.
2015-01-01
A radically new class of Bell inequalities in Wigner’s form was obtained on the basis of Kolmorov’s axiomatization of probability theory and the hypothesis of locality. These inequalities take explicitly into account the dependence on time (time-dependent Bell inequalities in Wigner’s form). By using these inequalities, one can propose a means for experimentally testing Bohr’ complementarity principle in the relativistic region. The inequalities in question open broad possibilities for studying correlations of nonrelativistic and relativistic quantum systems in external fields. The violation of the time-dependent inequalities in quantum mechanics was studied by considering the behavior of a pair of anticorrelated spins in a constant external magnetic field and oscillations of neutral pseudoscalar mesons. The decay of a pseudoscalar particle to a fermion–antifermion pair is considered within quantum field theory. In order to test experimentally the inequalities proposed in the present study, it is not necessary to perform dedicated noninvasive measurements required in the Leggett–Garg approach, for example
Energy Technology Data Exchange (ETDEWEB)
Nikitin, N. V., E-mail: nnikit@mail.cern.ch; Sotnikov, V.P., E-mail: sotnikov@physics.msu.ru [Moscow State University, Faculty of Physics (Russian Federation); Toms, K. S., E-mail: ktoms@mail.cern.ch [The University of New Mexico, Department of Physics and Astronomy (United States)
2015-10-15
A radically new class of Bell inequalities in Wigner’s form was obtained on the basis of Kolmorov’s axiomatization of probability theory and the hypothesis of locality. These inequalities take explicitly into account the dependence on time (time-dependent Bell inequalities in Wigner’s form). By using these inequalities, one can propose a means for experimentally testing Bohr’ complementarity principle in the relativistic region. The inequalities in question open broad possibilities for studying correlations of nonrelativistic and relativistic quantum systems in external fields. The violation of the time-dependent inequalities in quantum mechanics was studied by considering the behavior of a pair of anticorrelated spins in a constant external magnetic field and oscillations of neutral pseudoscalar mesons. The decay of a pseudoscalar particle to a fermion–antifermion pair is considered within quantum field theory. In order to test experimentally the inequalities proposed in the present study, it is not necessary to perform dedicated noninvasive measurements required in the Leggett–Garg approach, for example.
A Hybrid Joint Moment Ratio Test for Financial Time Series
P.A. Groenendijk (Patrick); A. Lucas (André); C.G. de Vries (Casper)
1998-01-01
textabstractWe advocate the use of absolute moment ratio statistics in conjunction with standard variance ratio statistics in order to disentangle linear dependence, non-linear dependence, and leptokurtosis in financial time series. Both statistics are computed for multiple return horizons
Orović, Irena; Stanković, Srdjan; Amin, Moeness
2013-05-01
A modified robust two-dimensional compressive sensing algorithm for reconstruction of sparse time-frequency representation (TFR) is proposed. The ambiguity function domain is assumed to be the domain of observations. The two-dimensional Fourier bases are used to linearly relate the observations to the sparse TFR, in lieu of the Wigner distribution. We assume that a set of available samples in the ambiguity domain is heavily corrupted by an impulsive type of noise. Consequently, the problem of sparse TFR reconstruction cannot be tackled using standard compressive sensing optimization algorithms. We introduce a two-dimensional L-statistics based modification into the transform domain representation. It provides suitable initial conditions that will produce efficient convergence of the reconstruction algorithm. This approach applies sorting and weighting operations to discard an expected amount of samples corrupted by noise. The remaining samples serve as observations used in sparse reconstruction of the time-frequency signal representation. The efficiency of the proposed approach is demonstrated on numerical examples that comprise both cases of monocomponent and multicomponent signals.
From discrete-time models to continuous-time, asynchronous modeling of financial markets
Boer, Katalin; Kaymak, Uzay; Spiering, Jaap
2007-01-01
Most agent-based simulation models of financial markets are discrete-time in nature. In this paper, we investigate to what degree such models are extensible to continuous-time, asynchronous modeling of financial markets. We study the behavior of a learning market maker in a market with information
From Discrete-Time Models to Continuous-Time, Asynchronous Models of Financial Markets
K. Boer-Sorban (Katalin); U. Kaymak (Uzay); J. Spiering (Jaap)
2006-01-01
textabstractMost agent-based simulation models of financial markets are discrete-time in nature. In this paper, we investigate to what degree such models are extensible to continuous-time, asynchronous modelling of financial markets. We study the behaviour of a learning market maker in a market with
FINANCIAL STABILITY OF BANKS IN TIMES OF CRISIS
Directory of Open Access Journals (Sweden)
Svetlana Lanets
2015-11-01
Full Text Available This paper is aimed at drawing attention to the current situation and further development of the banking sector in Russia. In particular, it seeks to discuss ways to improve the financial stability of banks. The article looks at the banking system, describes the important role of banks in the economy of the country and establishes correlation between stability of banks and socioeconomic development of the country. It is underlined that the stability of banks is one of the key factors in economic growth. The article analyzes how the banking system has settled after the financial crisis. The focus of the article is on the characteristics of the current financial crisis, compares it to the previous ones and describes the impact of the crisis to the banks. In particular, in the frame of this publication we present the analysis of the features of crisis impact on regional banks and the possibility of losing them in near future. This paper emphasizes the impact of the banking system on the country's economy and demonstrates the importance of financial stability of the banks. Moreover the article underlines a set of financial – economic/bank – government approaches to the issue of improving financial stability in the contemporary financial crisis. The paper summarizes the government role in the time of modern financial crisis and describes the existing strategies of the state. At the same time article shows the dual role of the government activities in preventing to put the finance sector under such stress as on the one hand it helps banks to increase the capitalization of banks while on the other hand it introduces Basel 3 principles, which reduce capital. The study is based on the methods of analysis, comparison, statistical data and theoretical generalization. The scientific and theoretical part of the survey is based on the official statistics and data from the Central Bank. We believe that the issue of bank’s stability, especially in this
Nonstationary quantum mechanics. 5. Nonstationary quantum models of scattering
Energy Technology Data Exchange (ETDEWEB)
Todorov, N S [Low Temperature Department of the Institute of Solid State Physics of the Bulgarian Academy of Sciences, Sofia
1981-05-01
Some peculiarities of the results of nonstationary perturbation theory in the presence of a degenerate continuous energy spectrum are considered. Their relevance to the ideology of the preceding articles in this series is discussed.
Nonstationary quantum mechanics v. nonstationary quantum models of scattering
Energy Technology Data Exchange (ETDEWEB)
Todorov, N S
1981-05-01
Some pecularities of the results of nonstationary pertubation theory in the presence of a degenerate continuous energy spectrum are considered. Their relevance to the ideology of the preceding articles in this series is discussed.
Hazard function theory for nonstationary natural hazards
Read, L.; Vogel, R. M.
2015-12-01
Studies from the natural hazards literature indicate that many natural processes, including wind speeds, landslides, wildfires, precipitation, streamflow and earthquakes, show evidence of nonstationary behavior such as trends in magnitudes through time. Traditional probabilistic analysis of natural hazards based on partial duration series (PDS) generally assumes stationarity in the magnitudes and arrivals of events, i.e. that the probability of exceedance is constant through time. Given evidence of trends and the consequent expected growth in devastating impacts from natural hazards across the world, new methods are needed to characterize their probabilistic behavior. The field of hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series (x) with its failure time series (t), enabling computation of corresponding average return periods and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose PDS magnitudes are assumed to follow the widely applied Poisson-GP model. We derive a 2-parameter Generalized Pareto hazard model and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. Our theoretical analysis linking hazard event series x, with corresponding failure time series t, should have application to a wide class of natural hazards.
Modelling Time-Varying Volatility in Financial Returns
DEFF Research Database (Denmark)
Amado, Cristina; Laakkonen, Helinä
2014-01-01
The “unusually uncertain” phase in the global financial markets has inspired many researchers to study the effects of ambiguity (or “Knightian uncertainty”) on the decisions made by investors and their implications for the capital markets. We contribute to this literature by using a modified...... version of the time-varying GARCH model of Amado and Teräsvirta (2013) to analyze whether the increasing uncertainty has caused excess volatility in the US and European government bond markets. In our model, volatility is multiplicatively decomposed into two time-varying conditional components: the first...... being captured by a stable GARCH(1,1) process and the second driven by the level of uncertainty in the financial market....
Financial Time Series Prediction Using Elman Recurrent Random Neural Networks
Directory of Open Access Journals (Sweden)
Jie Wang
2016-01-01
(ERNN, the empirical results show that the proposed neural network displays the best performance among these neural networks in financial time series forecasting. Further, the empirical research is performed in testing the predictive effects of SSE, TWSE, KOSPI, and Nikkei225 with the established model, and the corresponding statistical comparisons of the above market indices are also exhibited. The experimental results show that this approach gives good performance in predicting the values from the stock market indices.
Modeling financial time series with S-plus
Zivot, Eric
2003-01-01
The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics This is the first book to show the power of S-PLUS for the analysis of time series data It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department at the University of Washington, and is co-director of the nascent Professional Master's Program in Computational Finance He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the He...
International Nuclear Information System (INIS)
Lin, Chang Sheng; Chiang, Dar Yun
2012-01-01
Modal identification is considered from response data of structural system under nonstationary ambient vibration. In a previous paper, we showed that by assuming the ambient excitation to be nonstationary white noise in the form of a product model, the nonstationary response signals can be converted into free-vibration data via the correlation technique. In the present paper, if the ambient excitation can be modeled as a nonstationary white noise in the form of a product model, then the nonstationary cross random decrement signatures of structural response evaluated at any fixed time instant are shown theoretically to be proportional to the nonstationary cross-correlation functions. The practical problem of insufficient data samples available for evaluating nonstationary random decrement signatures can be approximately resolved by first extracting the amplitude-modulating function from the response and then transforming the nonstationary responses into stationary ones. Modal-parameter identification can then be performed using the Ibrahim time-domain technique, which is effective at identifying closely spaced modes. The theory proposed can be further extended by using the filtering concept to cover the case of nonstationary color excitations. Numerical simulations confirm the validity of the proposed method for identification of modal parameters from nonstationary ambient response data
Multiscale Symbolic Phase Transfer Entropy in Financial Time Series Classification
Zhang, Ningning; Lin, Aijing; Shang, Pengjian
We address the challenge of classifying financial time series via a newly proposed multiscale symbolic phase transfer entropy (MSPTE). Using MSPTE method, we succeed to quantify the strength and direction of information flow between financial systems and classify financial time series, which are the stock indices from Europe, America and China during the period from 2006 to 2016 and the stocks of banking, aviation industry and pharmacy during the period from 2007 to 2016, simultaneously. The MSPTE analysis shows that the value of symbolic phase transfer entropy (SPTE) among stocks decreases with the increasing scale factor. It is demonstrated that MSPTE method can well divide stocks into groups by areas and industries. In addition, it can be concluded that the MSPTE analysis quantify the similarity among the stock markets. The symbolic phase transfer entropy (SPTE) between the two stocks from the same area is far less than the SPTE between stocks from different areas. The results also indicate that four stocks from America and Europe have relatively high degree of similarity and the stocks of banking and pharmaceutical industry have higher similarity for CA. It is worth mentioning that the pharmaceutical industry has weaker particular market mechanism than banking and aviation industry.
Topological data analysis of financial time series: Landscapes of crashes
Gidea, Marian; Katz, Yuri
2018-02-01
We explore the evolution of daily returns of four major US stock market indices during the technology crash of 2000, and the financial crisis of 2007-2009. Our methodology is based on topological data analysis (TDA). We use persistence homology to detect and quantify topological patterns that appear in multidimensional time series. Using a sliding window, we extract time-dependent point cloud data sets, to which we associate a topological space. We detect transient loops that appear in this space, and we measure their persistence. This is encoded in real-valued functions referred to as a 'persistence landscapes'. We quantify the temporal changes in persistence landscapes via their Lp-norms. We test this procedure on multidimensional time series generated by various non-linear and non-equilibrium models. We find that, in the vicinity of financial meltdowns, the Lp-norms exhibit strong growth prior to the primary peak, which ascends during a crash. Remarkably, the average spectral density at low frequencies of the time series of Lp-norms of the persistence landscapes demonstrates a strong rising trend for 250 trading days prior to either dotcom crash on 03/10/2000, or to the Lehman bankruptcy on 09/15/2008. Our study suggests that TDA provides a new type of econometric analysis, which complements the standard statistical measures. The method can be used to detect early warning signals of imminent market crashes. We believe that this approach can be used beyond the analysis of financial time series presented here.
EU trade in the time of financial crisis
Directory of Open Access Journals (Sweden)
Fojtíková, L.
2010-12-01
Full Text Available The paper is focused on the European Union (EU trade and trade policy in the time of global financial and economic crisis. The analysis of the EU exports and imports points out that the financial crisis has had a negative impact on the intra as well as on the extra-EU trade in the period 2007-2009, but differences among the EU member states have existed. Although the EU tries to support trade development in the world and remove barriers to trade, some protectionist tendencies were recorded in the time of the economic crisis. The last part of the paper gives emphasis to the EU trade policy and some trade measures which have been taken in the EU and its member states to support trade development or vice versa, to protect domestic industries. The results of the analysis show that, although some protectionist tendencies have been recorded both in extra and intra-EU trade, trade relations which are provided among member states are of significant importance all the time.
Investigating Gender Differences under Time Pressure in Financial Risk Taking.
Xie, Zhixin; Page, Lionel; Hardy, Ben
2017-01-01
There is a significant gender imbalance on financial trading floors. This motivated us to investigate gender differences in financial risk taking under pressure. We used a well-established approach from behavior economics to analyze a series of risky monetary choices by male and female participants with and without time pressure. We also used second to fourth digit ratio (2D:4D) and face width-to-height ratio (fWHR) as correlates of pre-natal exposure to testosterone. We constructed a structural model and estimated the participants' risk attitudes and probability perceptions via maximum likelihood estimation under both expected utility (EU) and rank-dependent utility (RDU) models. In line with existing research, we found that male participants are less risk averse and that the gender gap in risk attitudes increases under moderate time pressure. We found that female participants with lower 2D:4D ratios and higher fWHR are less risk averse in RDU estimates. Males with lower 2D:4D ratios were less risk averse in EU estimations, but more risk averse using RDU estimates. We also observe that men whose ratios indicate a greater prenatal exposure to testosterone exhibit a greater optimism and overestimation of small probabilities of success.
Financial and Time Burdens for Medical Students Interviewing for Residency.
Callaway, Paul; Melhado, Trisha; Walling, Anne; Groskurth, Jordan
2017-02-01
Interviewing for residency positions is increasingly stressful for students and challenging for programs. Little information is available about the costs and time invested by students in interviewing or about the key factors in decisions to accept interview offers. Our objective was to assess the time and financial costs of residency interviewing for an entire class at a regional campus and explore factors influencing student decisions to accept interviews. We used a 14-item survey administered electronically immediately following National Resident Matching Program results. The response rate was 75% (49 of 65 students). About half interviewed in primary care specialties. Thirty students (63%) applied to 20 or more programs, and 91% were offered multiple interviews out of state. Seventy percent limited interviews by time and cost. Other important factors included personal "fit," program reputation, and the quality of residents. About 50% of the students spent more than 20 days and $1,000-$5,000 interviewing; 29% reported spending over $5,000. Students used multiple funding sources, predominantly loans and savings. Primary care applicants applied to fewer out-of-state programs, reported fewer interview days and lower expenses, but received more financial support from programs. Students invested considerable time and resources in interviewing, and these factors significantly influenced their decisions about accepting interviews. The other major factors in interview decisions concerned personal comfort with the program, especially the residents. The costs and time reported in this study could be greater than other schools due to the regional campus location or lower due to the high proportion of students interviewing in primary care.
Financial Time Series Forecasting Using Directed-Weighted Chunking SVMs
Directory of Open Access Journals (Sweden)
Yongming Cai
2014-01-01
Full Text Available Support vector machines (SVMs are a promising alternative to traditional regression estimation approaches. But, when dealing with massive-scale data set, there exist many problems, such as the long training time and excessive demand of memory space. So, the SVMs algorithm is not suitable to deal with financial time series data. In order to solve these problems, directed-weighted chunking SVMs algorithm is proposed. In this algorithm, the whole training data set is split into several chunks, and then the support vectors are obtained on each subset. Furthermore, the weighted support vector regressions are calculated to obtain the forecast model on the new working data set. Our directed-weighted chunking algorithm provides a new method of support vectors decomposing and combining according to the importance of chunks, which can improve the operation speed without reducing prediction accuracy. Finally, IBM stock daily close prices data are used to verify the validity of the proposed algorithm.
Photorefraction in crystals with nonstationary photovoltaic current
International Nuclear Information System (INIS)
Volk, T.R.; Astaf'ev, S.B.; Razumovskij, N.V.
1995-01-01
Effect of photovoltaic current nonstationary components, conditioned by nonstationary character of photovoltaic centers, on photorefractive properties of LiNbO 3 crystals is considered. Analytic expressions describing nonstationary photovoltaic current effect on kinetics of recording and optical erasure of photorefraction are obtained. A possibility of nonstationary photovoltaic current occurrence in crystals with multilevel charge transfer circuit is considered. Recording light pulse duration effect on photorefraction in LiNbO 3 is discussed. 25 refs., 8 figs
Financial time series analysis based on effective phase transfer entropy
Yang, Pengbo; Shang, Pengjian; Lin, Aijing
2017-02-01
Transfer entropy is a powerful technique which is able to quantify the impact of one dynamic system on another system. In this paper, we propose the effective phase transfer entropy method based on the transfer entropy method. We use simulated data to test the performance of this method, and the experimental results confirm that the proposed approach is capable of detecting the information transfer between the systems. We also explore the relationship between effective phase transfer entropy and some variables, such as data size, coupling strength and noise. The effective phase transfer entropy is positively correlated with the data size and the coupling strength. Even in the presence of a large amount of noise, it can detect the information transfer between systems, and it is very robust to noise. Moreover, this measure is indeed able to accurately estimate the information flow between systems compared with phase transfer entropy. In order to reflect the application of this method in practice, we apply this method to financial time series and gain new insight into the interactions between systems. It is demonstrated that the effective phase transfer entropy can be used to detect some economic fluctuations in the financial market. To summarize, the effective phase transfer entropy method is a very efficient tool to estimate the information flow between systems.
Wavelet transform approach for fitting financial time series data
Ahmed, Amel Abdoullah; Ismail, Mohd Tahir
2015-10-01
This study investigates a newly developed technique; a combined wavelet filtering and VEC model, to study the dynamic relationship among financial time series. Wavelet filter has been used to annihilate noise data in daily data set of NASDAQ stock market of US, and three stock markets of Middle East and North Africa (MENA) region, namely, Egypt, Jordan, and Istanbul. The data covered is from 6/29/2001 to 5/5/2009. After that, the returns of generated series by wavelet filter and original series are analyzed by cointegration test and VEC model. The results show that the cointegration test affirms the existence of cointegration between the studied series, and there is a long-term relationship between the US, stock markets and MENA stock markets. A comparison between the proposed model and traditional model demonstrates that, the proposed model (DWT with VEC model) outperforms traditional model (VEC model) to fit the financial stock markets series well, and shows real information about these relationships among the stock markets.
Nonstationary statistical theory for multipactor
International Nuclear Information System (INIS)
Anza, S.; Vicente, C.; Gil, J.; Boria, V. E.; Gimeno, B.; Raboso, D.
2010-01-01
This work presents a new and general approach to the real dynamics of the multipactor process: the nonstationary statistical multipactor theory. The nonstationary theory removes the stationarity assumption of the classical theory and, as a consequence, it is able to adequately model electron exponential growth as well as absorption processes, above and below the multipactor breakdown level. In addition, it considers both double-surface and single-surface interactions constituting a full framework for nonresonant polyphase multipactor analysis. This work formulates the new theory and validates it with numerical and experimental results with excellent agreement.
Non-stationary compositions of Anosov diffeomorphisms
International Nuclear Information System (INIS)
Stenlund, Mikko
2011-01-01
Motivated by non-equilibrium phenomena in nature, we study dynamical systems whose time-evolution is determined by non-stationary compositions of chaotic maps. The constituent maps are topologically transitive Anosov diffeomorphisms on a two-dimensional compact Riemannian manifold, which are allowed to change with time—slowly, but in a rather arbitrary fashion. In particular, such systems admit no invariant measure. By constructing a coupling, we prove that any two sufficiently regular distributions of the initial state converge exponentially with time. Thus, a system of this kind loses memory of its statistical history rapidly
Fermat principle for a nonstationary medium.
Voronovich, A G; Godin, O A
2003-07-25
One possible formulation of a variational principle of the Fermat type for systems with time-dependent parameters is suggested. In a stationary case, it reduces to the Mopertui-Lagrange least-action principle. A class of Hamiltonians (dispersion relations) is indicated, for which the variational principle reduces to the Fermat principle in a general nonstationary case. Hamiltonians that are homogeneous functions of momenta are in this category. For the important case of nondispersive waves (corresponding to Hamiltonians being homogeneous function of momenta order 1) the Fermat principle fully determines the geometry of the rays. Equations relating the variation of signal frequency with the rate of change of propagation time are established.
The psychophysiology of real-time financial risk processing.
Lo, Andrew W; Repin, Dmitry V
2002-04-01
A longstanding controversy in economics and finance is whether financial markets are governed by rational forces or by emotional responses. We study the importance of emotion in the decision-making process of professional securities traders by measuring their physiological characteristics (e.g., skin conductance, blood volume pulse, etc.) during live trading sessions while simultaneously capturing real-time prices from which market events can be detected. In a sample of 10 traders, we find statistically significant differences in mean electrodermal responses during transient market events relative to no-event control periods, and statistically significant mean changes in cardiovascular variables during periods of heightened market volatility relative to normal-volatility control periods. We also observe significant differences in these physiological responses across the 10 traders that may be systematically related to the traders' levels of experience.
Correlation filtering in financial time series (Invited Paper)
Aste, T.; Di Matteo, Tiziana; Tumminello, M.; Mantegna, R. N.
2005-05-01
We apply a method to filter relevant information from the correlation coefficient matrix by extracting a network of relevant interactions. This method succeeds to generate networks with the same hierarchical structure of the Minimum Spanning Tree but containing a larger amount of links resulting in a richer network topology allowing loops and cliques. In Tumminello et al.,1 we have shown that this method, applied to a financial portfolio of 100 stocks in the USA equity markets, is pretty efficient in filtering relevant information about the clustering of the system and its hierarchical structure both on the whole system and within each cluster. In particular, we have found that triangular loops and 4 element cliques have important and significant relations with the market structure and properties. Here we apply this filtering procedure to the analysis of correlation in two different kind of interest rate time series (16 Eurodollars and 34 US interest rates).
Hazard function theory for nonstationary natural hazards
Read, Laura K.; Vogel, Richard M.
2016-04-01
Impact from natural hazards is a shared global problem that causes tremendous loss of life and property, economic cost, and damage to the environment. Increasingly, many natural processes show evidence of nonstationary behavior including wind speeds, landslides, wildfires, precipitation, streamflow, sea levels, and earthquakes. Traditional probabilistic analysis of natural hazards based on peaks over threshold (POT) generally assumes stationarity in the magnitudes and arrivals of events, i.e., that the probability of exceedance of some critical event is constant through time. Given increasing evidence of trends in natural hazards, new methods are needed to characterize their probabilistic behavior. The well-developed field of hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series (X) with its failure time series (T), enabling computation of corresponding average return periods, risk, and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose POT magnitudes are assumed to follow the widely applied generalized Pareto model. We derive the hazard function for this case and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. Our theoretical analysis linking hazard random variable X with corresponding failure time series T should have application to a wide class of natural hazards with opportunities for future extensions.
Watanabe, Hayafumi; Sano, Yukie; Takayasu, Hideki; Takayasu, Misako
2016-11-01
To elucidate the nontrivial empirical statistical properties of fluctuations of a typical nonsteady time series representing the appearance of words in blogs, we investigated approximately 3×10^{9} Japanese blog articles over a period of six years and analyze some corresponding mathematical models. First, we introduce a solvable nonsteady extension of the random diffusion model, which can be deduced by modeling the behavior of heterogeneous random bloggers. Next, we deduce theoretical expressions for both the temporal and ensemble fluctuation scalings of this model, and demonstrate that these expressions can reproduce all empirical scalings over eight orders of magnitude. Furthermore, we show that the model can reproduce other statistical properties of time series representing the appearance of words in blogs, such as functional forms of the probability density and correlations in the total number of blogs. As an application, we quantify the abnormality of special nationwide events by measuring the fluctuation scalings of 1771 basic adjectives.
Wavelet-Based Methodology for Evolutionary Spectra Estimation of Nonstationary Typhoon Processes
Directory of Open Access Journals (Sweden)
Guang-Dong Zhou
2015-01-01
Full Text Available Closed-form expressions are proposed to estimate the evolutionary power spectral density (EPSD of nonstationary typhoon processes by employing the wavelet transform. Relying on the definition of the EPSD and the concept of the wavelet transform, wavelet coefficients of a nonstationary typhoon process at a certain time instant are interpreted as the Fourier transform of a new nonstationary oscillatory process, whose modulating function is equal to the modulating function of the nonstationary typhoon process multiplied by the wavelet function in time domain. Then, the EPSD of nonstationary typhoon processes is deduced in a closed form and is formulated as a weighted sum of the squared moduli of time-dependent wavelet functions. The weighted coefficients are frequency-dependent functions defined by the wavelet coefficients of the nonstationary typhoon process and the overlapping area of two shifted wavelets. Compared with the EPSD, defined by a sum of the squared moduli of the wavelets in frequency domain in literature, this paper provides an EPSD estimation method in time domain. The theoretical results are verified by uniformly modulated nonstationary typhoon processes and non-uniformly modulated nonstationary typhoon processes.
Directory of Open Access Journals (Sweden)
QIAN HU
2017-12-01
Full Text Available The economic crisis presented unprecedented challenges to nonprofit organizations to sustain their services. In this study, we examined both financial and management factors that influence the financial performance of nonprofit organizations during times of economic stress. In particular, we investigated whether strategic planning and plan implementation, revenue diversification, and board involvement help nonprofit organizations deal with financial uncertainty and strengthen financial performance. Despite the negative impacts that the economic downturn had on nonprofit organizations, we found that the implementation of strategic plans can help nonprofit organizations reduce financial vulnerability. Our findings call attention to key management factors that influence the financial performance of nonprofit organizations.
Financial Intermediation and the Nigerian Economy: A Time Series ...
African Journals Online (AJOL)
... and cointegration analysis based on Engle Granger cointegration theory and error correction methodology, we tested both short and long run relationships between financial intermediation and economic growth in Nigeria. The result revealed that a long–run relationship exists between financial intermediation and growth ...
Latino Associate Degree Completion: Effects of Financial Aid over Time
Gross, Jacob P. K.; Zerquera, Desiree; Inge, Brittany; Berry, Matthew
2014-01-01
Lack of financial resources to pay for postsecondary education--perceived and actual--has been cited as a barrier to student access and persistence, particularly for Latino students. This study investigates the following question: "To what extent does financial aid affect the educational attainment of Latinos enrolled in Associate's degree…
Linear and nonlinear dynamic systems in financial time series prediction
Directory of Open Access Journals (Sweden)
Salim Lahmiri
2012-10-01
Full Text Available Autoregressive moving average (ARMA process and dynamic neural networks namely the nonlinear autoregressive moving average with exogenous inputs (NARX are compared by evaluating their ability to predict financial time series; for instance the S&P500 returns. Two classes of ARMA are considered. The first one is the standard ARMA model which is a linear static system. The second one uses Kalman filter (KF to estimate and predict ARMA coefficients. This model is a linear dynamic system. The forecasting ability of each system is evaluated by means of mean absolute error (MAE and mean absolute deviation (MAD statistics. Simulation results indicate that the ARMA-KF system performs better than the standard ARMA alone. Thus, introducing dynamics into the ARMA process improves the forecasting accuracy. In addition, the ARMA-KF outperformed the NARX. This result may suggest that the linear component found in the S&P500 return series is more dominant than the nonlinear part. In sum, we conclude that introducing dynamics into the ARMA process provides an effective system for S&P500 time series prediction.
Correlation of financial markets in times of crisis
Sandoval, Leonidas; Franca, Italo De Paula
2012-01-01
Using the eigenvalues and eigenvectors of correlations matrices of some of the main financial market indices in the world, we show that high volatility of markets is directly linked with strong correlations between them. This means that markets tend to behave as one during great crashes. In order to do so, we investigate financial market crises that occurred in the years 1987 (Black Monday), 1998 (Russian crisis), 2001 (Burst of the dot-com bubble and September 11), and 2008 (Subprime Mortgage Crisis), which mark some of the largest downturns of financial markets in the last three decades.
Non-stationary flow of hydraulic oil in long pipe
Directory of Open Access Journals (Sweden)
Hružík Lumír
2014-03-01
Full Text Available The paper deals with experimental evaluation and numerical simulation of non-stationary flow of hydraulic oil in a long hydraulic line. Non-stationary flow is caused by a quick closing of valves at the beginning and the end of the pipe. Time dependence of pressure is measured by means of pressure sensors at the beginning and the end of the pipe. A mathematical model of a given circuit is created using Matlab SimHydraulics software. The long line is simulated by means of segmented pipe. The simulation is verified by experiment.
A Hybrid Joint Moment Ratio Test for Financial Time Series
Groenendijk, Patrick A.; Lucas, André; Vries, de Casper G.
1998-01-01
We advocate the use of absolute moment ratio statistics in conjunctionwith standard variance ratio statistics in order to disentangle lineardependence, non-linear dependence, and leptokurtosis in financial timeseries. Both statistics are computed for multiple return horizonssimultaneously, and the
Wavelet Correlation Coefficient of 'strongly correlated' financial time series
Razdan, Ashok
2003-01-01
In this paper we use wavelet concepts to show that correlation coefficient between two financial data's is not constant but varies with scale from high correlation value to strongly anti-correlation value This studies is important because correlation coefficient is used to quantify degree of independence between two variables. In econophysics correlation coefficient forms important input to evolve hierarchial tree and minimum spanning tree of financial data.
Portfolio Diversification with Commodities in Times of Financialization
Directory of Open Access Journals (Sweden)
Adam Zaremba
2015-03-01
Full Text Available The study concentrates on the benefits of passive commodity investments in the context of the phenomenon of financialization. The research investigates the implications of increase in the correlation coefficients between equity and commodity investments for investors in financial markets. The paper is composed of several parts. First, the attributes of commodity investments and their benefits in the portfolio optimization are explored. Second, the phenomenon of the financialization is described and the research hypothesis is developed. Next, an empirical analysis is performed. I simulate the mean-variance spanning tests to examine the benefits of commodity investments before and after accounting for the impact of financialization. I proceed separate analysis for pre- and post-financialization period. The empirical research is based on asset classes’ returns and other related variables from years 1991-2012. The performed investigations indicate that the market financialization may have significant implications for commodity investors. Due to increase in correlation coefficients, the inclusion of the commodity futures in the traditional stock-bond portfolio appears to be no longer reasonable.
Mallak, Saed
1996-01-01
Ankara : Department of Mathematics and Institute of Engineering and Sciences of Bilkent University, 1996. Thesis (Master's) -- Bilkent University, 1996. Includes bibliographical references leaves leaf 29 In thi.s work, we studierl the Ergodicilv of Non-Stationary .Markov chains. We gave several e.xainples with different cases. We proved that given a sec[uence of Markov chains such that the limit of this sec|uence is an Ergodic Markov chain, then the limit of the combination ...
International Nuclear Information System (INIS)
Chen, Shih-Hung; Chen, Liu
2013-01-01
The nonstationary oscillation of the gyrotron backward wave oscillator (gyro-BWO) with cylindrical interaction structure was studied utilizing both steady-state analyses and time-dependent simulations. Comparisons of the numerical results reveal that the gyro-BWO becomes nonstationary when the trailing field structure completely forms due to the dephasing energetic electrons. The backward propagation of radiated waves with a lower resonant frequency from the trailing field structure interferes with the main internal feedback loop, thereby inducing the nonstationary oscillation of the gyro-BWO. The nonstationary gyro-BWO exhibits the same spectral pattern of modulated oscillations with a constant frequency separation between the central frequency and sidebands throughout the whole system. The frequency separation is found to be scaled with the square root of the maximum field amplitude, thus further demonstrating that the nonstationary oscillation of the gyro-BWO is associated with the beam-wave resonance detuning
Long Memory of Financial Time Series and Hidden Markov Models with Time-Varying Parameters
DEFF Research Database (Denmark)
Nystrup, Peter; Madsen, Henrik; Lindström, Erik
2016-01-01
Hidden Markov models are often used to model daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time-varying behavior have not been thoroughly examined. This paper presents an adaptive...... to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step density forecasts. Finally, it is shown that the forecasting performance of the estimated models can be further improved using local smoothing to forecast the parameter variations....
A Phase Vocoder Based on Nonstationary Gabor Frames
DEFF Research Database (Denmark)
Ottosen, Emil Solsbæk; Dörfler, Monika
2017-01-01
We propose a new algorithm for time stretching music signals based on the theory of nonstationary Gabor frames (NSGFs). The algorithm extends the techniques of the classical phase vocoder (PV) by incorporating adaptive timefrequency (TF) representations and adaptive phase locking. The adaptive TF...
Cointegration and Econometric Analysis of Non-Stationary Data in ...
African Journals Online (AJOL)
This is in conformity with the philosophy underlying the cointegration theory. Therefore, ignoring cointegration in non-stationary time series variables could lead to misspecification of the underlying process in the determination of corporate income tax in Nigeria. Thus, the study conclude that cointegration is greatly enhanced ...
Ludescher, Josef; Bunde, Armin
2014-12-01
We consider representative financial records (stocks and indices) on time scales between one minute and one day, as well as historical monthly data sets, and show that the distribution P(Q)(r) of the interoccurrence times r between losses below a negative threshold -Q, for fixed mean interoccurrence times R(Q) in multiples of the corresponding time resolutions, can be described on all time scales by the same q exponentials, P(Q)(r)∝1/{[1+(q-1)βr](1/(q-1))}. We propose that the asset- and time-scale-independent analytic form of P(Q)(r) can be regarded as an additional stylized fact of the financial markets and represents a nontrivial test for market models. We analyze the distribution P(Q)(r) as well as the autocorrelation C(Q)(s) of the interoccurrence times for three market models: (i) multiplicative random cascades, (ii) multifractal random walks, and (iii) the generalized autoregressive conditional heteroskedasticity [GARCH(1,1)] model. We find that only one of the considered models, the multifractal random walk model, approximately reproduces the q-exponential form of P(Q)(r) and the power-law decay of C(Q)(s).
Ludescher, Josef; Bunde, Armin
2014-12-01
We consider representative financial records (stocks and indices) on time scales between one minute and one day, as well as historical monthly data sets, and show that the distribution PQ(r ) of the interoccurrence times r between losses below a negative threshold -Q , for fixed mean interoccurrence times RQ in multiples of the corresponding time resolutions, can be described on all time scales by the same q exponentials, PQ(r ) ∝1 /{[1+(q -1 ) β r ] 1 /(q -1 )} . We propose that the asset- and time-scale-independent analytic form of PQ(r ) can be regarded as an additional stylized fact of the financial markets and represents a nontrivial test for market models. We analyze the distribution PQ(r ) as well as the autocorrelation CQ(s ) of the interoccurrence times for three market models: (i) multiplicative random cascades, (ii) multifractal random walks, and (iii) the generalized autoregressive conditional heteroskedasticity [GARCH(1,1)] model. We find that only one of the considered models, the multifractal random walk model, approximately reproduces the q -exponential form of PQ(r ) and the power-law decay of CQ(s ) .
Dynamics and control of a financial system with time-delayed feedbacks
International Nuclear Information System (INIS)
Chen, W.-C.
2008-01-01
Complex behaviors in a financial system with time-delayed feedbacks are discussed in this study via numerical modeling. The system shows complex dynamics such as periodic, quasi-periodic, and chaotic behaviors. Both period doubling and inverse period doubling routes were found in this system. This paper also shows that the attractor merging crisis is a fundamental feature of nonlinear financial systems with time-delayed feedbacks. Control of the deterministic chaos in the financial system can be realized using Pyragas feedbacks
Czech Academy of Sciences Publication Activity Database
Baxa, Jaromír; Horváth, R.; Vašíček, B.
2013-01-01
Roč. 9, č. 1 (2013), s. 117-138 ISSN 1572-3089 Institutional support: RVO:67985556 Keywords : Financial stress * Time-varying parameter model * Endogenous regressors Subject RIV: AH - Economics Impact factor: 2.932, year: 2013 http://library.utia.cas.cz/separaty/2013/E/baxa-0395375.pdf
Nonstationary Hydrological Frequency Analysis: Theoretical Methods and Application Challenges
Xiong, L.
2014-12-01
Because of its great implications in the design and operation of hydraulic structures under changing environments (either climate change or anthropogenic changes), nonstationary hydrological frequency analysis has become so important and essential. Two important achievements have been made in methods. Without adhering to the consistency assumption in the traditional hydrological frequency analysis, the time-varying probability distribution of any hydrological variable can be established by linking the distribution parameters to some covariates such as time or physical variables with the help of some powerful tools like the Generalized Additive Model of Location, Scale and Shape (GAMLSS). With the help of copulas, the multivariate nonstationary hydrological frequency analysis has also become feasible. However, applications of the nonstationary hydrological frequency formula to the design and operation of hydraulic structures for coping with the impacts of changing environments in practice is still faced with many challenges. First, the nonstationary hydrological frequency formulae with time as covariate could only be extrapolated for a very short time period beyond the latest observation time, because such kind of formulae is not physically constrained and the extrapolated outcomes could be unrealistic. There are two physically reasonable methods that can be used for changing environments, one is to directly link the quantiles or the distribution parameters to some measureable physical factors, and the other is to use the derived probability distributions based on hydrological processes. However, both methods are with a certain degree of uncertainty. For the design and operation of hydraulic structures under changing environments, it is recommended that design results of both stationary and nonstationary methods be presented together and compared with each other, to help us understand the potential risks of each method.
Long memory of financial time series and hidden Markov models with time-varying parameters
DEFF Research Database (Denmark)
Nystrup, Peter; Madsen, Henrik; Lindström, Erik
Hidden Markov models are often used to capture stylized facts of daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time-varying behavior for the ability to reproduce the stylized...... facts have not been thoroughly examined. This paper presents an adaptive estimation approach that allows for the parameters of the estimated models to be time-varying. It is shown that a two-state Gaussian hidden Markov model with time-varying parameters is able to reproduce the long memory of squared...... daily returns that was previously believed to be the most difficult fact to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step predictions....
Learning for Nonstationary Dirichlet Processes
Czech Academy of Sciences Publication Activity Database
Quinn, A.; Kárný, Miroslav
2007-01-01
Roč. 21, č. 10 (2007), s. 827-855 ISSN 0890-6327 R&D Projects: GA AV ČR 1ET100750401 Grant - others:MŠk ČR(CZ) 2C06001 Program:2C Institutional research plan: CEZ:AV0Z10750506 Keywords : Nestacionární procesy * učení * Dirichletovy procesy * zapomínání Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.776, year: 2007 http://library.utia.cas.cz/separaty/2007/as/karny- learning for nonstationary dirichlet processes.pdf
Strategic Decision Making in Times of Global Financial Crisis
Gawlik, Remigiusz
2009-01-01
The presented paper is a brief presentation of findings based on research lead on a group of small and medium businesses. The study has been made in conditions of global financial crisis and its effects, such as fall of production volumes in numerous companies. A number of indexes describing the actual economic situation and short – term prospects of discussed businesses has been presented to their medium- and high level executives in order to point out those most useful when taking strategic...
Dynamics of macroeconomic and financial variables in different time horizons
Kim Karlsson, Hyunjoo
2012-01-01
This dissertation consists of an introductory chapter and four papers dealing with financial issues of open economies, which can be in two broad categorizations: 1) exchange rate movements and 2) stock market interdependence. The first paper covers how the exchange rate changes affect the prices of internationally traded goods. With the variables (the price of exports in exporters’ currency and the exchange rate, both of which are in logarithmic form) being cointegrated, a model with both lon...
Shadow Banking – Developments in Times of Financial Crisis
Directory of Open Access Journals (Sweden)
Bogdan Munteanu
2016-01-01
The paper considers the following entities and activities, without limitation to or completenessof viewpoints: finance companies, asset backed financial instruments, structured investments,financing vehicles, money market funds, asset managers, credit hedge funds and venture capital,providing characteristics of shadow banking and their economic functions relative to the classicbanking system, as they pose a systemic risk due to asymmetric information and gaps created inmatching liquidity tenures with duration, by using synthetic leverage finance.
Cappell, M S; Spray, D C; Bennett, M V
1988-06-28
Protractor muscles in the gastropod mollusc Navanax inermis exhibit typical spontaneous miniature end plate potentials with mean amplitude 1.71 +/- 1.19 (standard deviation) mV. The evoked end plate potential is quantized, with a quantum equal to the miniature end plate potential amplitude. When their rate is stationary, occurrence of miniature end plate potentials is a random, Poisson process. When non-stationary, spontaneous miniature end plate potential occurrence is a non-stationary Poisson process, a Poisson process with the mean frequency changing with time. This extends the random Poisson model for miniature end plate potentials to the frequently observed non-stationary occurrence. Reported deviations from a Poisson process can sometimes be accounted for by the non-stationary Poisson process and more complex models, such as clustered release, are not always needed.
Testing for Co-integration in Vector Autoregressions with Non-Stationary Volatility
DEFF Research Database (Denmark)
Cavaliere, Guiseppe; Rahbæk, Anders; Taylor, A.M. Robert
Many key macro-economic and financial variables are characterised by permanent changes in unconditional volatility. In this paper we analyse vector autoregressions with non-stationary (unconditional) volatility of a very general form, which includes single and multiple volatility breaks as special...
Modelling conditional heteroscedasticity in nonstationary series
Cizek, P.; Cizek, P.; Härdle, W.K.; Weron, R.
2011-01-01
A vast amount of econometrical and statistical research deals with modeling financial time series and their volatility, which measures the dispersion of a series at a point in time (i.e., conditional variance). Although financial markets have been experiencing many shorter and longer periods of
National Research Council Canada - National Science Library
Zissimopoulos, Julie
2001-01-01
Using the Health and Retirement Study, this research investigates whether an adult child substitutes financial transfers to an elderly parent for time transfers as the cost of his or her time increases...
Self-adaptive change detection in streaming data with non-stationary distribution
Zhang, Xiangliang; Wang, Wei
2010-01-01
Non-stationary distribution, in which the data distribution evolves over time, is a common issue in many application fields, e.g., intrusion detection and grid computing. Detecting the changes in massive streaming data with a non
Small College Guide to Financial Health: Weathering Turbulent Times [with CD-ROM
Townsley, Michael K.
2009-01-01
In this timely book, financial consultant and experienced college administrator Mike Townsley examines the financial and strategic resources that private colleges and universities must have in place to withstand the storm. Small college presidents, CFOs, planners, chief academic officers, and board members all have a hand on the tiller and will…
Multiscale multifractal multiproperty analysis of financial time series based on Rényi entropy
Yujun, Yang; Jianping, Li; Yimei, Yang
This paper introduces a multiscale multifractal multiproperty analysis based on Rényi entropy (3MPAR) method to analyze short-range and long-range characteristics of financial time series, and then applies this method to the five time series of five properties in four stock indices. Combining the two analysis techniques of Rényi entropy and multifractal detrended fluctuation analysis (MFDFA), the 3MPAR method focuses on the curves of Rényi entropy and generalized Hurst exponent of five properties of four stock time series, which allows us to study more universal and subtle fluctuation characteristics of financial time series. By analyzing the curves of the Rényi entropy and the profiles of the logarithm distribution of MFDFA of five properties of four stock indices, the 3MPAR method shows some fluctuation characteristics of the financial time series and the stock markets. Then, it also shows a richer information of the financial time series by comparing the profile of five properties of four stock indices. In this paper, we not only focus on the multifractality of time series but also the fluctuation characteristics of the financial time series and subtle differences in the time series of different properties. We find that financial time series is far more complex than reported in some research works using one property of time series.
Comparison of transfer entropy methods for financial time series
He, Jiayi; Shang, Pengjian
2017-09-01
There is a certain relationship between the global financial markets, which creates an interactive network of global finance. Transfer entropy, a measurement for information transfer, offered a good way to analyse the relationship. In this paper, we analysed the relationship between 9 stock indices from the U.S., Europe and China (from 1995 to 2015) by using transfer entropy (TE), effective transfer entropy (ETE), Rényi transfer entropy (RTE) and effective Rényi transfer entropy (ERTE). We compared the four methods in the sense of the effectiveness for identification of the relationship between stock markets. In this paper, two kinds of information flows are given. One reveals that the U.S. took the leading position when in terms of lagged-current cases, but when it comes to the same date, China is the most influential. And ERTE could provide superior results.
Financial Times oil and gas international year book 1994
International Nuclear Information System (INIS)
Williams, Julian
1993-01-01
The greater part of this book aims to provide narrative, production and financial details of major oil and gas companies, both upstream and downstream, across the world. Smaller sections give details on major oil and gas brokers and traders, and on the principal oil and gas associations. These sections are arranged alphabetically by company name. A geographical index towards the end of the book enables the user to identify upstream companies exploring for or producing oil and gas in particular areas. The company index includes every company mentioned in the book and includes all subsidiary and related companies to the major companies. Four introductory tables give data on world petroleum production, oil refining, tanker tonnage and oil consumption. (Author)
Network simulation of nonstationary ionic transport through liquid junctions
International Nuclear Information System (INIS)
Castilla, J.; Horno, J.
1993-01-01
Nonstationary ionic transport across the liquid junctions has been studied using Network Thermodynamics. A network model for the time-dependent Nernst-Plack-Poisson system of equation is proposed. With this network model and the electrical circuit simulation program PSPICE, the concentrations, charge density, and electrical potentials, at short times, have been simulated for the binary system NaCl/NaCl. (Author) 13 refs
A quantile-based Time at Risk: A new approach for assessing risk in financial markets
Bolgorian, Meysam; Raei, Reza
2013-11-01
In this paper, we provide a new measure for evaluation of risk in financial markets. This measure is based on the return interval of critical events in financial markets or other investment situations. Our main goal was to devise a model like Value at Risk (VaR). As VaR, for a given financial asset, probability level and time horizon, gives a critical value such that the likelihood of loss on the asset over the time horizon exceeds this value is equal to the given probability level, our concept of Time at Risk (TaR), using a probability distribution function of return intervals, provides a critical time such that the probability that the return interval of a critical event exceeds this time equals the given probability level. As an empirical application, we applied our model to data from the Tehran Stock Exchange Price Index (TEPIX) as a financial asset (market portfolio) and reported the results.
Comparison of nonstationary generalized logistic models based on Monte Carlo simulation
Directory of Open Access Journals (Sweden)
S. Kim
2015-06-01
Full Text Available Recently, the evidences of climate change have been observed in hydrologic data such as rainfall and flow data. The time-dependent characteristics of statistics in hydrologic data are widely defined as nonstationarity. Therefore, various nonstationary GEV and generalized Pareto models have been suggested for frequency analysis of nonstationary annual maximum and POT (peak-over-threshold data, respectively. However, the alternative models are required for nonstatinoary frequency analysis because of analyzing the complex characteristics of nonstationary data based on climate change. This study proposed the nonstationary generalized logistic model including time-dependent parameters. The parameters of proposed model are estimated using the method of maximum likelihood based on the Newton-Raphson method. In addition, the proposed model is compared by Monte Carlo simulation to investigate the characteristics of models and applicability.
Talking Time, Seeing Time: The Importance of Attending to Time in Financial Mathematics
Pournara, Craig
2015-01-01
Through analysing a critical incident where a small group of pre-service secondary mathematics teachers work together on an annuities problem, we gain insight into the ways in which students make use of timelines and attend to time in their talk. Drawing on Lave and Wenger's notion of transparency, I argue that it was only when time became visible…
The heterogeneity in financial and time burden of caregiving to children with chronic conditions.
Zan, Hua; Scharff, Robert L
2015-03-01
We examine the financial and time burdens associated with caring for children with chronic conditions, focusing on disparities across types of conditions. Using linked data from the 2003 to 2006 National Health Interview Survey and 2004-2008 Medical Expenditure Panel Survey, we created measures of financial burden (out-of-pocket healthcare costs, the ratio of out-of-pocket healthcare costs to family income, healthcare costs paid by insurance, and total healthcare costs) and time burden (missed school time due to illness or injury and the number of doctor visits) associated with 14 groups of children's chronic conditions. We used the two-part model to assess the effect of condition on financial burden and finite mixture/latent class model to analyze the time burden of caregiving. Controlling for the influences of other socio-demographic characteristics on caregiving burden, children with chronic conditions have higher financial and time burdens relative to caregiving burdens for healthy children. Levels of financial burden and burden sharing between families and insurance system also vary by type of condition. For example, children with pervasive developmental disorder or heart disease have a relatively low financial burden for families, while imposing a high cost on the insurance system. In contrast, vision difficulties are associated with a high financial burden for families relative to the costs borne by others. With respect to time burden, conditions such as cerebral palsy and heart disease impose a low time burden, while conditions such as pervasive developmental disorder are associated with a high time burden. This study demonstrates that differences exist in caregiving burden for children by type of chronic condition. Each condition has a unique profile of time and financial cost burden for families and the insurance system. These results have implications for policymakers and for families' savings and employment decisions.
ECONOMETRIC APPROACH OF HETEROSKEDASTICITY ON FINANCIAL TIME SERIES IN A GENERAL FRAMEWORK
Directory of Open Access Journals (Sweden)
FELICIA RAMONA BIRĂU
2012-12-01
Full Text Available The aim of this paper is to provide an overview of the diagnostic tests for detecting heteroskedasticity on financial time series. In financial econometrics, heteroskedasticity is generally associated with cross sectional data but can also be identified modeling time series data. The presence of heteroscedasticity in financial time series can be caused by certain specific factors, like a model misspecification, inadequate data transformation or as a result of certain outliers. Heteroskedasticity arise when the homoskedasticity assumption is violated. Testing for the presence of heteroskedasticity in financial time is performed by applying diagnostic test, such as : Breusch-Pagan LM test, White’s test, Glesjer LM test, Harvey-Godfrey LM test, Park LM test and Goldfeld-Quand test.
The impact of financial and nonfinancial incentives on business-unit outcomes over time.
Peterson, Suzanne J; Luthans, Fred
2006-01-01
Unlike previous behavior management research, this study used a quasi-experimental, control group design to examine the impact of financial and nonfinancial incentives on business-unit (21 stores in a fast-food franchise corporation) outcomes (profit, customer service, and employee turnover) over time. The results showed that both types of incentives had a significant impact on all measured outcomes. The financial incentive initially had a greater effect on all 3 outcomes, but over time, the financial and nonfinancial incentives had an equally significant impact except in terms of employee turnover. (c) 2006 APA, all rights reserved.
Inferential framework for non-stationary dynamics: theory and applications
International Nuclear Information System (INIS)
Duggento, Andrea; Luchinsky, Dmitri G; McClintock, Peter V E; Smelyanskiy, Vadim N
2009-01-01
An extended Bayesian inference framework is presented, aiming to infer time-varying parameters in non-stationary nonlinear stochastic dynamical systems. The convergence of the method is discussed. The performance of the technique is studied using, as an example, signal reconstruction for a system of neurons modeled by FitzHugh–Nagumo oscillators: it is applied to reconstruction of the model parameters and elements of the measurement matrix, as well as to inference of the time-varying parameters of the non-stationary system. It is shown that the proposed approach is able to reconstruct unmeasured (hidden) variables of the system, to determine the model parameters, to detect stepwise changes of control parameters for each oscillator and to track the continuous evolution of the control parameters in the adiabatic limit
Loss energy states of nonstationary quantum systems
International Nuclear Information System (INIS)
Dodonov, V.V.; Man'ko, V.I.
1978-01-01
The concept of loss energy states is introduced. The loss energy states of the quantum harmonic damping oscillator are considered in detail. The method of constructing the loss energy states for general multidimensional quadratic nonstationary quantum systems is briefly discussed
A Generalized Framework for Non-Stationary Extreme Value Analysis
Ragno, E.; Cheng, L.; Sadegh, M.; AghaKouchak, A.
2017-12-01
Empirical trends in climate variables including precipitation, temperature, snow-water equivalent at regional to continental scales are evidence of changes in climate over time. The evolving climate conditions and human activity-related factors such as urbanization and population growth can exert further changes in weather and climate extremes. As a result, the scientific community faces an increasing demand for updated appraisal of the time-varying climate extremes. The purpose of this study is to offer a robust and flexible statistical tool for non-stationary extreme value analysis which can better characterize the severity and likelihood of extreme climatic variables. This is critical to ensure a more resilient environment in a changing climate. Following the positive feedback on the first version of Non-Stationary Extreme Value Analysis (NEVA) Toolbox by Cheng at al. 2014, we present an improved version, i.e. NEVA2.0. The upgraded version herein builds upon a newly-developed hybrid evolution Markov Chain Monte Carlo (MCMC) approach for numerical parameters estimation and uncertainty assessment. This addition leads to a more robust uncertainty estimates of return levels, return periods, and risks of climatic extremes under both stationary and non-stationary assumptions. Moreover, NEVA2.0 is flexible in incorporating any user-specified covariate other than the default time-covariate (e.g., CO2 emissions, large scale climatic oscillation patterns). The new feature will allow users to examine non-stationarity of extremes induced by physical conditions that underlie the extreme events (e.g. antecedent soil moisture deficit, large-scale climatic teleconnections, urbanization). In addition, the new version offers an option to generate stationary and/or non-stationary rainfall Intensity - Duration - Frequency (IDF) curves that are widely used for risk assessment and infrastructure design. Finally, a Graphical User Interface (GUI) of the package is provided, making NEVA
Do First Time House Buyers Receive Financial Transfers from Their Parents?
DEFF Research Database (Denmark)
Kolodziejczyk, Christophe; Leth-Petersen, Søren
2013-01-01
Using Danish longitudinal data with information about wealth for a sample of first-time house buyers and their parents, we test whether there are direct financial transfers from parents to children in connection with the house purchase, or in connection with unemployment spells occurring just after...... the purchase, when children typically hold few liquid assets. First, we document that child and parent financial resources are correlated. Then, we introduce conditioning variables and exploit the panel aspect of the data to also condition on fixed unobserved factors, which arguably govern preferences and....../or productivity. We find no evidence of direct financial transfers....
Study on statistical analysis of nonlinear and nonstationary reactor noises
International Nuclear Information System (INIS)
Hayashi, Koji
1993-03-01
For the purpose of identification of nonlinear mechanism and diagnosis of nuclear reactor systems, analysis methods for nonlinear reactor noise have been studied. By adding newly developed approximate response function to GMDH, a conventional nonlinear identification method, a useful method for nonlinear spectral analysis and identification of nonlinear mechanism has been established. Measurement experiment and analysis were performed on the reactor power oscillation observed in the NSRR installed at the JAERI and the cause of the instability was clarified. Furthermore, the analysis and data recording methods for nonstationary noise have been studied. By improving the time resolution of instantaneous autoregressive spectrum, a method for monitoring and diagnosis of operational status of nuclear reactor has been established. A preprocessing system for recording of nonstationary reactor noise was developed and its usability was demonstrated through a measurement experiment. (author) 139 refs
A Novel Simulation Model for Nonstationary Rice Fading Channels
Directory of Open Access Journals (Sweden)
Kaili Jiang
2018-01-01
Full Text Available In this paper, we propose a new simulator for nonstationary Rice fading channels under nonisotropic scattering scenarios, as well as the improved computation method of simulation parameters. The new simulator can also be applied on generating Rayleigh fading channels by adjusting parameters. The proposed simulator takes into account the smooth transition of fading phases between the adjacent channel states. The time-variant statistical properties of the proposed simulator, that is, the probability density functions (PDFs of envelope and phase, autocorrelation function (ACF, and Doppler power spectrum density (DPSD, are also analyzed and derived. Simulation results have demonstrated that our proposed simulator provides good approximation on the statistical properties with the corresponding theoretical ones, which indicates its usefulness for the performance evaluation and validation of the wireless communication systems under nonstationary and nonisotropic scenarios.
Thin viscoelastic disc subjected to radial non-stationary loading
Directory of Open Access Journals (Sweden)
Adámek V.
2010-07-01
Full Text Available The investigation of non-stationary wave phenomena in isotropic viscoelastic solids using analytical approaches is the aim of this paper. Concretely, the problem of a thin homogeneous disc subjected to radial pressure load nonzero on the part of its rim is solved. The external excitation is described by the Heaviside function in time, so the nonstationary state of stress is induced in the disc. Dissipative material behaviour of solid studied is represented by the discrete material model of standard linear viscoelastic solid in the Zener configuration. After the derivation of motion equations final form, the method of integral transforms in combination with the Fourier method is used for finding the problem solution. The solving process results in the derivation of integral transforms of radial and circumferential displacement components. Finally, the type of derived functions singularities and possible methods for their inverse Laplace transform are mentioned.
Fang, Wen; Wang, Jun
2013-09-01
We develop a financial market model using an Ising spin system on a Sierpinski carpet lattice that breaks the equal status of each spin. To study the fluctuation behavior of the financial model, we present numerical research based on Monte Carlo simulation in conjunction with the statistical analysis and multifractal analysis of the financial time series. We extract the multifractal spectra by selecting various lattice size values of the Sierpinski carpet, and the inverse temperature of the Ising dynamic system. We also investigate the statistical fluctuation behavior, the time-varying volatility clustering, and the multifractality of returns for the indices SSE, SZSE, DJIA, IXIC, S&P500, HSI, N225, and for the simulation data derived from the Ising model on the Sierpinski carpet lattice. A numerical study of the model’s dynamical properties reveals that this financial model reproduces important features of the empirical data.
Does Financial Development Reduce CO2 Emissions in Malaysian Economy? A Time Series Analysis
Shahbaz, Muhammad; Solarin, Sakiru Adebola; Mahmood, Haider
2012-01-01
This study deals with the question whether financial development reduces CO2 emissions or not in case of Malaysia. For this purpose, we apply the bounds testing approach to cointegration for long run relations between the variables. The study uses annual time series data over the period 1971-2008. Ng-Perron stationarity test is applied to test the unit root properties of the series. Our results validate the presence of cointegration between CO2 emissions, financial development, energy co...
Influence of the Time Scale on the Construction of Financial Networks
Emmert-Streib, Frank; Dehmer, Matthias
2010-01-01
BACKGROUND: In this paper we investigate the definition and formation of financial networks. Specifically, we study the influence of the time scale on their construction. METHODOLOGY/PRINCIPAL FINDINGS: For our analysis we use correlation-based networks obtained from the daily closing prices of stock market data. More precisely, we use the stocks that currently comprise the Dow Jones Industrial Average (DJIA) and estimate financial networks where nodes correspond to stocks and edges correspon...
Modeling Financial Time Series Based on a Market Microstructure Model with Leverage Effect
Yanhui Xi; Hui Peng; Yemei Qin
2016-01-01
The basic market microstructure model specifies that the price/return innovation and the volatility innovation are independent Gaussian white noise processes. However, the financial leverage effect has been found to be statistically significant in many financial time series. In this paper, a novel market microstructure model with leverage effects is proposed. The model specification assumed a negative correlation in the errors between the price/return innovation and the volatility innovation....
Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting
Zhang, Ningning; Lin, Aijing; Shang, Pengjian
2017-07-01
In this paper, we propose a new two-stage methodology that combines the ensemble empirical mode decomposition (EEMD) with multidimensional k-nearest neighbor model (MKNN) in order to forecast the closing price and high price of the stocks simultaneously. The modified algorithm of k-nearest neighbors (KNN) has an increasingly wide application in the prediction of all fields. Empirical mode decomposition (EMD) decomposes a nonlinear and non-stationary signal into a series of intrinsic mode functions (IMFs), however, it cannot reveal characteristic information of the signal with much accuracy as a result of mode mixing. So ensemble empirical mode decomposition (EEMD), an improved method of EMD, is presented to resolve the weaknesses of EMD by adding white noise to the original data. With EEMD, the components with true physical meaning can be extracted from the time series. Utilizing the advantage of EEMD and MKNN, the new proposed ensemble empirical mode decomposition combined with multidimensional k-nearest neighbor model (EEMD-MKNN) has high predictive precision for short-term forecasting. Moreover, we extend this methodology to the case of two-dimensions to forecast the closing price and high price of the four stocks (NAS, S&P500, DJI and STI stock indices) at the same time. The results indicate that the proposed EEMD-MKNN model has a higher forecast precision than EMD-KNN, KNN method and ARIMA.
International Nuclear Information System (INIS)
Frank, T.D.
2006-01-01
First-order approximations of time-dependent solutions are determined for stochastic systems perturbed by time-delayed feedback forces. To this end, the theory of delay Fokker-Planck equations is applied in combination with Bayes' theorem. Applications to a time-delayed Ornstein-Uhlenbeck process and the geometric Brownian walk of financial physics are discussed
Financial Burden Associated with Time to Return to Work After Living Kidney Donation.
Larson, Dawn B; Wiseman, Jennifer F; Vock, David; Bergund, Danielle M; Roman, Ashley; Ibrahim, Hassan Nimer; Matas, Arthur J
2018-05-25
Many living kidney donors undertake a significant financial burden in order to donate. We studied the association between time to return to work and reported financial burden. Kidney donors, who donated from 2/2005 - through 12/2015 (n=1012) were surveyed 6 months postdonation, and asked about occupation; time to return to work; and financial burden (on a 10-point Likert scale). Of 856 donors working for pay, 629 (73%) responded. After adjusting for donor characteristics, increased length of time to return to work was a significant predictor of financial burden (pfinancial burden for each week away from work (p=0.003). Older age at donation and nondirected (vs directed) donation were associated with significantly decreased financial burden. These observations provide additional information to better inform donor candidates, and further emphasize the need to develop policies so that living kidney donation can be financially neutral. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Estimation of Hurst Exponent for the Financial Time Series
Kumar, J.; Manchanda, P.
2009-07-01
Till recently statistical methods and Fourier analysis were employed to study fluctuations in stock markets in general and Indian stock market in particular. However current trend is to apply the concepts of wavelet methodology and Hurst exponent, see for example the work of Manchanda, J. Kumar and Siddiqi, Journal of the Frankline Institute 144 (2007), 613-636 and paper of Cajueiro and B. M. Tabak. Cajueiro and Tabak, Physica A, 2003, have checked the efficiency of emerging markets by computing Hurst component over a time window of 4 years of data. Our goal in the present paper is to understand the dynamics of the Indian stock market. We look for the persistency in the stock market through Hurst exponent and fractal dimension of time series data of BSE 100 and NIFTY 50.
Characteristics of the transmission of autoregressive sub-patterns in financial time series
Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong
2014-09-01
There are many types of autoregressive patterns in financial time series, and they form a transmission process. Here, we define autoregressive patterns quantitatively through an econometrical regression model. We present a computational algorithm that sets the autoregressive patterns as nodes and transmissions between patterns as edges, and then converts the transmission process of autoregressive patterns in a time series into a network. We utilised daily Shanghai (securities) composite index time series to study the transmission characteristics of autoregressive patterns. We found statistically significant evidence that the financial market is not random and that there are similar characteristics between parts and whole time series. A few types of autoregressive sub-patterns and transmission patterns drive the oscillations of the financial market. A clustering effect on fluctuations appears in the transmission process, and certain non-major autoregressive sub-patterns have high media capabilities in the financial time series. Different stock indexes exhibit similar characteristics in the transmission of fluctuation information. This work not only proposes a distinctive perspective for analysing financial time series but also provides important information for investors.
The Usage of Time Series Control Charts for Financial Process Analysis
Directory of Open Access Journals (Sweden)
Kovářík Martin
2012-09-01
Full Text Available We will deal with financial proceedings of the company using methods of SPC (Statistical Process Control, specifically through time series control charts. The paper will outline the intersection of two disciplines which are econometrics and statistical process control. The theoretical part will discuss the methodology of time series control charts and in the research part there will be this methodology demonstrated in three case studies. The first study will focus on the regulation of simulated financial flows for a company by CUSUM control chart. The second study will involve the regulation of financial flows for a heteroskedastic financial process by EWMA control chart. The last case study of our paper will be devoted to applications of ARIMA, EWMA and CUSUM control charts in the financial data that are sensitive to the mean shifting while calculating the autocorrelation in the data. In this paper, we highlight the versatility of control charts not only in manufacturing but also in managing the financial stability of cash flows.
Stationary and nonstationary properties of evolving networks with preferential linkage
International Nuclear Information System (INIS)
Jezewski, W.
2002-01-01
Networks evolving by preferential attachment of both external and internal links are investigated. The rate of adding an external link is assumed to depend linearly on the degree of a preexisting node to which a new node is connected. The process of creating an internal link, between a pair of existing vertices, is assumed to be controlled entirely by the vertex that has more links than the other vertex in the pair, and the rate of creation of such a link is assumed to be, in general, nonlinear in the degree of the more strongly connected vertex. It is shown that degree distributions of networks evolving only by creating internal links display for large degrees a nonstationary power-law decay with a time-dependent scaling exponent. Nonstationary power-law behaviors are numerically shown to persist even when the number of nodes is not fixed and both external and internal connections are introduced, provided that the rate of preferential attachment of internal connections is nonlinear. It is argued that nonstationary effects are not unlikely in real networks, although these effects may not be apparent, especially in networks with a slowly varying mean degree
Econophysics — complex correlations and trend switchings in financial time series
Preis, T.
2011-03-01
This article focuses on the analysis of financial time series and their correlations. A method is used for quantifying pattern based correlations of a time series. With this methodology, evidence is found that typical behavioral patterns of financial market participants manifest over short time scales, i.e., that reactions to given price patterns are not entirely random, but that similar price patterns also cause similar reactions. Based on the investigation of the complex correlations in financial time series, the question arises, which properties change when switching from a positive trend to a negative trend. An empirical quantification by rescaling provides the result that new price extrema coincide with a significant increase in transaction volume and a significant decrease in the length of corresponding time intervals between transactions. These findings are independent of the time scale over 9 orders of magnitude, and they exhibit characteristics which one can also find in other complex systems in nature (and in physical systems in particular). These properties are independent of the markets analyzed. Trends that exist only for a few seconds show the same characteristics as trends on time scales of several months. Thus, it is possible to study financial bubbles and their collapses in more detail, because trend switching processes occur with higher frequency on small time scales. In addition, a Monte Carlo based simulation of financial markets is analyzed and extended in order to reproduce empirical features and to gain insight into their causes. These causes include both financial market microstructure and the risk aversion of market participants.
ECONOMIC AND FINANCIAL CRISIS IMPACT ON ROMANIA ALONG TIME
Directory of Open Access Journals (Sweden)
Gheorghe GRIGORESCU
2013-06-01
Full Text Available Five years after the onset of the strongest economic crisis that has seen a global economy, the world still seems to be far from solved problems. Neither Romania is no exception, sustainable economic recovery we all want is (for now only hope. We have allowed the material to make some suggestions on how the economy might revive. We talked first about the vital need for revival of investment, supporting them through tax incentives to entrepreneurs. I then point the better absorption of European funds, the source of revival of the Romanian economy. Also advocate for greater accountability in spending public money, so terms like necessity, opportunity and social need not remain only in books, but to be used effectively in the allocation of budgetary resources. We detailed several times how I propose we approached the Romanian economy and revitalize major role essential, you must have it in technical and scientific economic recovery. The regret of not having experience in macroeconomics, in order to put more ideas on the table, still think that the detailed material could give thought to avid readers.
Andriole, Katherine P; Prevedello, Luciano M; Dufault, Allen; Pezeshk, Parham; Bransfield, Robert; Hanson, Richard; Doubilet, Peter M; Seltzer, Steven E; Khorasani, Ramin
2010-03-01
Radiology report signature time (ST) can be a substantial component of total report turnaround time. Poor turnaround time resulting from lengthy ST can adversely affect patient care. The combination of technology adoption with financial incentive was evaluated to determine if ST improvement can be augmented and sustained. This prospective study was performed at a 751-bed, urban, tertiary care adult teaching hospital. Test-site imaging volume approximated 48,000 examinations per month. The radiology department has 100 trainees and 124 attending radiologists serving multiple institutions. Over a study period of 4 years and 4 months, three interventions focused on radiologist signature performance were implemented: 1) a notification paging application that alerted radiologists when reports were ready for signature, 2) a picture archiving and communications systems (PACS)-integrated speech recognition report generation system, and 3) a departmental financial incentive to reward radiologists semiannually for ST performance. Signature time was compared before and after the interventions. Wilcoxon and linear regression statistical analyses were used to assess the significance of trends. Technology adoption (paging plus speech recognition) reduced median ST from >5 to 24 to 15 to 18 hours (P financial incentive further improved 80th-percentile ST to 4 to 8 hours (P Technology interventions coupled with financial incentive can result in synergistic and sustainable improvement in radiologist report-signing behavior. The addition of a financial incentive leads to better performance than that achievable through technology alone.
Directory of Open Access Journals (Sweden)
Igor Stubelj
2014-03-01
Full Text Available The paper deals with the estimation of weighted average cost of capital (WACC for regulated industries in developing financial markets from the perspective of the current financial-economic crisis. In current financial market situation some evident changes have occurred: risk-free rates in solid and developed financial markets (e. g. USA, Germany have fallen, but due to increased market volatility, the risk premiums have increased. The latter is especially evident in transition economies where the amplitude of market volatility is extremely high. In such circumstances, there is a question of how to calculate WACC properly. WACC is an important measure in financial management decisions and in our case, business regulation. We argue in the paper that the most accurate method for calculating WACC is the estimation of the long-term WACC, which takes into consideration a long-term stable yield of capital and not the current market conditions. Following this, we propose some solutions that could be used for calculating WACC for regulated industries on the developing financial markets in times of market uncertainty. As an example, we present an estimation of the capital cost for a selected Slovenian company, which operates in the regulated industry of electric distribution.
Zhang, Wei; Wang, Jun
2017-09-01
In attempt to reproduce price dynamics of financial markets, a stochastic agent-based financial price model is proposed and investigated by stochastic exclusion process. The exclusion process, one of interacting particle systems, is usually thought of as modeling particle motion (with the conserved number of particles) in a continuous time Markov process. In this work, the process is utilized to imitate the trading interactions among the investing agents, in order to explain some stylized facts found in financial time series dynamics. To better understand the correlation behaviors of the proposed model, a new time-dependent intrinsic detrended cross-correlation (TDI-DCC) is introduced and performed, also, the autocorrelation analyses are applied in the empirical research. Furthermore, to verify the rationality of the financial price model, the actual return series are also considered to be comparatively studied with the simulation ones. The comparison results of return behaviors reveal that this financial price dynamics model can reproduce some correlation features of actual stock markets.
ANALYSIS OF MARKET TIMING TOWARD LEVERAGE OF NON-FINANCIAL COMPANIES IN INDONESIA
Wulandari, Vera Pipin; Setiawan, Kusdhianto
2015-01-01
ABSTRACTThis study aimed to examine the effect of market timing on leverage on non-financial compa-nies in Indonesia. Market timing was tested on the hot and cold market conditions. Hot and cold markets are determined by the monthly market to book ratio. A hot (cold) market occurs when the average market to book ratio of a particular month is above (below) the value of the moving average of the monthly market to book ratio. This study also aimed to test whether non-financial companies in Indo...
Non-linear forecasting in high-frequency financial time series
Strozzi, F.; Zaldívar, J. M.
2005-08-01
A new methodology based on state space reconstruction techniques has been developed for trading in financial markets. The methodology has been tested using 18 high-frequency foreign exchange time series. The results are in apparent contradiction with the efficient market hypothesis which states that no profitable information about future movements can be obtained by studying the past prices series. In our (off-line) analysis positive gain may be obtained in all those series. The trading methodology is quite general and may be adapted to other financial time series. Finally, the steps for its on-line application are discussed.
Emerging properties of financial time series in the ``Game of Life''
Hernández-Montoya, A. R.; Coronel-Brizio, H. F.; Stevens-Ramírez, G. A.; Rodríguez-Achach, M.; Politi, M.; Scalas, E.
2011-12-01
We explore the spatial complexity of Conway’s “Game of Life,” a prototypical cellular automaton by means of a geometrical procedure generating a two-dimensional random walk from a bidimensional lattice with periodical boundaries. The one-dimensional projection of this process is analyzed and it turns out that some of its statistical properties resemble the so-called stylized facts observed in financial time series. The scope and meaning of this result are discussed from the viewpoint of complex systems. In particular, we stress how the supposed peculiarities of financial time series are, often, overrated in their importance.
2010-01-01
... 7 Agriculture 15 2010-01-01 2010-01-01 false Requirement for RBIC to file financial statements at... financial statements at the time of request for a draw. (a) If you submit a request for a draw against your... (Short Form), you must: (1) Give the Secretary a financial statement on Form 468 (Short Form), and (2...
Quantifying complexity of financial short-term time series by composite multiscale entropy measure
Niu, Hongli; Wang, Jun
2015-05-01
It is significant to study the complexity of financial time series since the financial market is a complex evolved dynamic system. Multiscale entropy is a prevailing method used to quantify the complexity of a time series. Due to its less reliability of entropy estimation for short-term time series at large time scales, a modification method, the composite multiscale entropy, is applied to the financial market. To qualify its effectiveness, its applications in the synthetic white noise and 1 / f noise with different data lengths are reproduced first in the present paper. Then it is introduced for the first time to make a reliability test with two Chinese stock indices. After conducting on short-time return series, the CMSE method shows the advantages in reducing deviations of entropy estimation and demonstrates more stable and reliable results when compared with the conventional MSE algorithm. Finally, the composite multiscale entropy of six important stock indices from the world financial markets is investigated, and some useful and interesting empirical results are obtained.
Analysis of financial time series using multiscale entropy based on skewness and kurtosis
Xu, Meng; Shang, Pengjian
2018-01-01
There is a great interest in studying dynamic characteristics of the financial time series of the daily stock closing price in different regions. Multi-scale entropy (MSE) is effective, mainly in quantifying the complexity of time series on different time scales. This paper applies a new method for financial stability from the perspective of MSE based on skewness and kurtosis. To better understand the superior coarse-graining method for the different kinds of stock indexes, we take into account the developmental characteristics of the three continents of Asia, North America and European stock markets. We study the volatility of different financial time series in addition to analyze the similarities and differences of coarsening time series from the perspective of skewness and kurtosis. A kind of corresponding relationship between the entropy value of stock sequences and the degree of stability of financial markets, were observed. The three stocks which have particular characteristics in the eight piece of stock sequences were discussed, finding the fact that it matches the result of applying the MSE method to showing results on a graph. A comparative study is conducted to simulate over synthetic and real world data. Results show that the modified method is more effective to the change of dynamics and has more valuable information. The result is obtained at the same time, finding the results of skewness and kurtosis discrimination is obvious, but also more stable.
A comment on measuring the Hurst exponent of financial time series
Couillard, Michel; Davison, Matt
2005-03-01
A fundamental hypothesis of quantitative finance is that stock price variations are independent and can be modeled using Brownian motion. In recent years, it was proposed to use rescaled range analysis and its characteristic value, the Hurst exponent, to test for independence in financial time series. Theoretically, independent time series should be characterized by a Hurst exponent of 1/2. However, finite Brownian motion data sets will always give a value of the Hurst exponent larger than 1/2 and without an appropriate statistical test such a value can mistakenly be interpreted as evidence of long term memory. We obtain a more precise statistical significance test for the Hurst exponent and apply it to real financial data sets. Our empirical analysis shows no long-term memory in some financial returns, suggesting that Brownian motion cannot be rejected as a model for price dynamics.
How Work Affects Divorce : The Mediating Role of Financial and Time Pressures
Poortman, Anne-Rigt
2005-01-01
This study examines whether the financial and time pressures associatedwith spouses’working lives play a role in the relation between work and divorce during the first years of marriage. Using retrospective data from the Netherlands, the results show that divorce is more likely when the husband
How work affects divorce. The mediating role of financial and time pressures
Poortman, A.R.
2005-01-01
This study examines whether the financial and time pressures associated with spouses' working lives play a role in the relation between work and divorce during the first years of marriage. Using retrospective data from the Netherlands, the results show that divorce is more likely when the husband
Schnusenberg, Oliver
2009-01-01
An interesting research question in light of recent technological developments is an investigation of the relationship between the time remaining to complete online quizzes and quiz scores. The data consist of over 4,000 individual quiz scores for six sections of Financial Management at The University of North Florida taught between the Summer of…
Communications officers and the C-suite: a study of Financial Times Global 500 companies
Verhoeven, P.
2014-01-01
A content analysis of the websites or annual reports of the 2012 Financial Times Global 500 companies was performed to examine the position of communications officers (COs) on their executive boards. Almost one quarter of the companies examined had a CO on the executive board. Their distribution
How Work Affects Divorce: The Mediating Role of Financial and Time Pressures
Poortman, Anne-Rigt
2005-01-01
This study examines whether the financial and time pressures associated with spouses' working lives play a role in the relation between work and divorce during the first years of marriage. Using retrospective data from the Netherlands, the results show that divorce is more likely when the husband works on average fewer hours and the wife more…
2010-12-06
... Information: Tax Time Card Account Pilot, Screening, Focus Groups, and Study AGENCY: Financial Management... general public and other Federal agencies to take this opportunity to comment on a continuing information... Account Pilot Screening, Focus Groups, and Study.'' DATES: Written comments should be received on or...
Working women's choices for domestic help: the effects of financial and time resources
Tijdens, K.; van der Lippe, T.; de Ruijter, E.
2003-01-01
Household services are increasing. Which households consume these services, in particular domestic help? This article tests whether time and financial resources influence the use of domestic help, performing logistic regression analyses with the WWIQ-2000/01-data (N=10,969), addressing working women
Multiband Prediction Model for Financial Time Series with Multivariate Empirical Mode Decomposition
Directory of Open Access Journals (Sweden)
Md. Rabiul Islam
2012-01-01
Full Text Available This paper presents a subband approach to financial time series prediction. Multivariate empirical mode decomposition (MEMD is employed here for multiband representation of multichannel financial time series together. Autoregressive moving average (ARMA model is used in prediction of individual subband of any time series data. Then all the predicted subband signals are summed up to obtain the overall prediction. The ARMA model works better for stationary signal. With multiband representation, each subband becomes a band-limited (narrow band signal and hence better prediction is achieved. The performance of the proposed MEMD-ARMA model is compared with classical EMD, discrete wavelet transform (DWT, and with full band ARMA model in terms of signal-to-noise ratio (SNR and mean square error (MSE between the original and predicted time series. The simulation results show that the MEMD-ARMA-based method performs better than the other methods.
Results of nonlinear and nonstationary image processing
International Nuclear Information System (INIS)
Pizer, S.M.; Correla, J.A.; Chesler, D.A.; Metz, C.E.
1973-01-01
A nonstationary method, multiple z-divided filtering, and a nonlinear method, biased smearing have been applied to scintigrams. Biased smearing does not appear to hold much promise. Multiple z-divided filtering, on the other hand, appears to be justified, and initial results at minimum encourage further research into the possibility that this technique may become a method of choice
Huajiao Li; Haizhong An; Xiangyun Gao; Wei Fang
2015-01-01
The co-fluctuation of two time series has often been studied by analysing the correlation coefficient over a selected period. However, in both domestic and global financial markets, there are more than two active time series that fluctuate constantly as a result of various factors, including geographic locations, information communications and so on. In addition to correlation relationships over longer periods, daily co-fluctuation relationships and their transmission features are also import...
Schwierz, Christoph; Wübker, Achim; Wübker, Ansgar; Kuchinke, Björn A
2011-10-01
This paper shows that patients with private health insurance (PHI) are being offered significantly shorter waiting times than patients with statutory health insurance (SHI) in German acute hospital care. This behavior may be driven by the higher expected profitability of PHI relative to SHI holders. Further, we find that hospitals offering private insurees shorter waiting times when compared with SHI holders have a significantly better financial performance than those abstaining from or with less discrimination.
Finite-time singularities in the dynamics of Mexican financial crises
Alvarez-Ramirez, Jose; Ibarra-Valdez, Carlos
2004-01-01
Historically, symptoms of Mexican financial crises have been strongly reflected in the dynamics of the Mexican peso to the dollar exchange currency market. Specifically, in the Mexican financial crises during 1990's, the peso suffered significant depreciation processes, which has important impacts in the macro- and micro-economical environment. In this paper, it is shown that the peso depreciation growth was greater than an exponential and that these growth rates are compatible with a spontaneous singularity occurring at a critical time, which signals an abrupt transition to new dynamical conditions. As in the major 1990's financial crisis in 1994-1995, some control actions (e.g., increasing the USA dollar supply) are commonly taken to decelerate the degree of abruptness of peso depreciation. Implications of these control actions on the crisis dynamics are discussed. Interestingly, by means of a simple model, it is demonstrated that the time at which the control actions begin to apply is critical to moderate the adverse effects of the financial crisis.
Radiation of light impurities in a nonstationary plasma
International Nuclear Information System (INIS)
Abramov, V.A.; Krotova, G.I.
1984-01-01
In the framework of a nonstationary coronal model with account for latest data on elementary process cross sections calculations of oxygen radiation power are performed. It is shown that taking into account electron temperature nonstationarity characteristic of the initial stage in nowadays tokamaks, line emission power in the principal maximum region (Tsub(e) approximately 40 eV) changes but slightly, whereas the radiation power in the second maximum (Tsub(e) approximately 100 eV increases approximately 20 times as compared with stationary values
Nonlinear Fluctuation Behavior of Financial Time Series Model by Statistical Physics System
Directory of Open Access Journals (Sweden)
Wuyang Cheng
2014-01-01
Full Text Available We develop a random financial time series model of stock market by one of statistical physics systems, the stochastic contact interacting system. Contact process is a continuous time Markov process; one interpretation of this model is as a model for the spread of an infection, where the epidemic spreading mimics the interplay of local infections and recovery of individuals. From this financial model, we study the statistical behaviors of return time series, and the corresponding behaviors of returns for Shanghai Stock Exchange Composite Index (SSECI and Hang Seng Index (HSI are also comparatively studied. Further, we investigate the Zipf distribution and multifractal phenomenon of returns and price changes. Zipf analysis and MF-DFA analysis are applied to investigate the natures of fluctuations for the stock market.
Time-varying economic dominance in financial markets: A bistable dynamics approach
He, Xue-Zhong; Li, Kai; Wang, Chuncheng
2018-05-01
By developing a continuous-time heterogeneous agent financial market model of multi-assets traded by fundamental and momentum investors, we provide a potential mechanism for generating time-varying dominance between fundamental and non-fundamental in financial markets. We show that investment constraints lead to the coexistence of a locally stable fundamental steady state and a locally stable limit cycle around the fundamental, characterized by a Bautin bifurcation. This provides a mechanism for market prices to switch stochastically between the two persistent but very different market states, leading to the coexistence and time-varying dominance of seemingly controversial efficient market and price momentum over different time periods. The model also generates other financial market stylized facts, such as spillover effects in both momentum and volatility, market booms, crashes, and correlation reduction due to cross-sectional momentum trading. Empirical evidence based on the U.S. market supports the main findings. The mechanism developed in this paper can be used to characterize time-varying economic dominance in economics and finance in general.
International Nuclear Information System (INIS)
Mikhin, V.I.; Matukhin, N.M.
2000-01-01
The approach to generalization of the non-stationary heat exchange data for the central zones of the nuclear reactor fuel assemblies and the approximate thermal-model-testing criteria are proposed. The fuel assemblies of fast and water-cooled reactors with different fuel compositions have been investigated. The reason of the non-stationary heat exchange is the fuel-energy-release time dependence. (author)
More for less: best patient outcomes in a time of financial restraint.
Merry, Alan F; Hamblin, Richard
2012-12-01
In many countries, expenditure on health care has increased dramatically over recent years. There have been parallel improvements in many indicators of population health, but too many patients continue to be harmed by health care or receive care that is supply-sensitive, ineffective, or poorly aligned with their needs and values. In addition to human costs, this translates into substantial waste of resource. The world has recently faced economic challenges unseen since the great depression of the 1930s. The financial situation of a country can, like a business, be expressed in three sets of accounts: statements of financial position, financial performance, and cash flow. A key test of solvency is the ability to pay debts as they become due (whether from current account or further borrowing). In general, this is a function of public debt, which for many countries has become very high. However, private debt and net financial position are also relevant to a country's financial prospects. Ultimately, borrowing is not sustainable indefinitely and given limited prospects for growth in income in the coming years, most countries will likely need to reduce or at least constrain expenditure on health care. This implies obtaining better value from the resources that are available, and we suggest that the key to this lies in improving the quality of care and, in particular, reducing variation in health care. In the United States, new legislation promoting accountable care organizations may help to do this. Cardiac surgery can be particularly effective in extending patients' lives and in improving the quality of their lives. Our ability to continue to provide cardiac surgery in the face of constrained economic times will depend on engaging more actively in ensuring that what we do is the right thing: that our operations are effective and that they truly meet the needs and values of our patients. It will also depend on doing these operations right the first time.
A survey of techniques applied to non-stationary waveforms in electrical power systems
Rodrigues, R.P.; Silveira, P.M.; Ribeiro, P.F.
2010-01-01
The well-known and ever-present time-varying and non-stationary nature of waveforms in power systems requires a comprehensive and precise analytical basis that needs to be incorporated in the system studies and analyses. This time-varying behavior is due to continuous changes in system
Detrended fluctuation analysis based on higher-order moments of financial time series
Teng, Yue; Shang, Pengjian
2018-01-01
In this paper, a generalized method of detrended fluctuation analysis (DFA) is proposed as a new measure to assess the complexity of a complex dynamical system such as stock market. We extend DFA and local scaling DFA to higher moments such as skewness and kurtosis (labeled SMDFA and KMDFA), so as to investigate the volatility scaling property of financial time series. Simulations are conducted over synthetic and financial data for providing the comparative study. We further report the results of volatility behaviors in three American countries, three Chinese and three European stock markets by using DFA and LSDFA method based on higher moments. They demonstrate the dynamics behaviors of time series in different aspects, which can quantify the changes of complexity for stock market data and provide us with more meaningful information than single exponent. And the results reveal some higher moments volatility and higher moments multiscale volatility details that cannot be obtained using the traditional DFA method.
Dependency structure and scaling properties of financial time series are related.
Morales, Raffaello; Di Matteo, T; Aste, Tomaso
2014-04-04
We report evidence of a deep interplay between cross-correlations hierarchical properties and multifractality of New York Stock Exchange daily stock returns. The degree of multifractality displayed by different stocks is found to be positively correlated to their depth in the hierarchy of cross-correlations. We propose a dynamical model that reproduces this observation along with an array of other empirical properties. The structure of this model is such that the hierarchical structure of heterogeneous risks plays a crucial role in the time evolution of the correlation matrix, providing an interpretation to the mechanism behind the interplay between cross-correlation and multifractality in financial markets, where the degree of multifractality of stocks is associated to their hierarchical positioning in the cross-correlation structure. Empirical observations reported in this paper present a new perspective towards the merging of univariate multi scaling and multivariate cross-correlation properties of financial time series.
Radhakrishnan, Srinivasan; Duvvuru, Arjun; Sultornsanee, Sivarit; Kamarthi, Sagar
2016-02-01
The cross correlation coefficient has been widely applied in financial time series analysis, in specific, for understanding chaotic behaviour in terms of stock price and index movements during crisis periods. To better understand time series correlation dynamics, the cross correlation matrices are represented as networks, in which a node stands for an individual time series and a link indicates cross correlation between a pair of nodes. These networks are converted into simpler trees using different schemes. In this context, Minimum Spanning Trees (MST) are the most favoured tree structures because of their ability to preserve all the nodes and thereby retain essential information imbued in the network. Although cross correlations underlying MSTs capture essential information, they do not faithfully capture dynamic behaviour embedded in the time series data of financial systems because cross correlation is a reliable measure only if the relationship between the time series is linear. To address the issue, this work investigates a new measure called phase synchronization (PS) for establishing correlations among different time series which relate to one another, linearly or nonlinearly. In this approach the strength of a link between a pair of time series (nodes) is determined by the level of phase synchronization between them. We compare the performance of phase synchronization based MST with cross correlation based MST along selected network measures across temporal frame that includes economically good and crisis periods. We observe agreement in the directionality of the results across these two methods. They show similar trends, upward or downward, when comparing selected network measures. Though both the methods give similar trends, the phase synchronization based MST is a more reliable representation of the dynamic behaviour of financial systems than the cross correlation based MST because of the former's ability to quantify nonlinear relationships among time
He, Jiayi; Shang, Pengjian; Xiong, Hui
2018-06-01
Stocks, as the concrete manifestation of financial time series with plenty of potential information, are often used in the study of financial time series. In this paper, we utilize the stock data to recognize their patterns through out the dissimilarity matrix based on modified cross-sample entropy, then three-dimensional perceptual maps of the results are provided through multidimensional scaling method. Two modified multidimensional scaling methods are proposed in this paper, that is, multidimensional scaling based on Kronecker-delta cross-sample entropy (MDS-KCSE) and multidimensional scaling based on permutation cross-sample entropy (MDS-PCSE). These two methods use Kronecker-delta based cross-sample entropy and permutation based cross-sample entropy to replace the distance or dissimilarity measurement in classical multidimensional scaling (MDS). Multidimensional scaling based on Chebyshev distance (MDSC) is employed to provide a reference for comparisons. Our analysis reveals a clear clustering both in synthetic data and 18 indices from diverse stock markets. It implies that time series generated by the same model are easier to have similar irregularity than others, and the difference in the stock index, which is caused by the country or region and the different financial policies, can reflect the irregularity in the data. In the synthetic data experiments, not only the time series generated by different models can be distinguished, the one generated under different parameters of the same model can also be detected. In the financial data experiment, the stock indices are clearly divided into five groups. Through analysis, we find that they correspond to five regions, respectively, that is, Europe, North America, South America, Asian-Pacific (with the exception of mainland China), mainland China and Russia. The results also demonstrate that MDS-KCSE and MDS-PCSE provide more effective divisions in experiments than MDSC.
Analysis of the Financial Times ranking "master in management" with machine learning
Jansen, Arthur
2017-01-01
University rankings play nowadays a major role in the decision of many students with regards to their future schools. Nonetheless, these rankings often remain quite opaque: not all data are made available, the methodology behind the rankings is not well defined, etc. One of the main ranking centred on business schools is the "Master in Management" from the Financial Times. This work aims to study the relevance of this ranking and its possible flaws. Several techniques are conducted, as a robu...
Energy Technology Data Exchange (ETDEWEB)
Ruiz, Jordi-Roger Riba [EUETII, Dept. d' Enginyeria Electrica, Universitat Politecnica de Catalunya, Placa del Rei 15, 08700 Igualada, Barcelona (Spain); Garcia Espinosa, Antonio [Dept. d' Enginyeria Electrica, Universitat Politecnica de Catalunya C/Colom 1, 08222 Terrassa (Spain); Romeral, Luis; Cusido, Jordi [Dept. d' Enginyeria Electronica, Universitat Politecnica de Catalunya C/Colom 1, 08222 Terrassa (Spain)
2010-10-15
Permanent magnet synchronous motors (PMSMs) are applied in high performance positioning and variable speed applications because of their enhanced features with respect to other AC motor types. Fault detection and diagnosis of electrical motors for critical applications is an active field of research. However, much research remains to be done in the field of PMSM demagnetization faults, especially when running under non-stationary conditions. This paper presents a time-frequency method specifically focused to detect and diagnose demagnetization faults in PMSMs running under non-stationary speed conditions, based on the Hilbert Huang transform. The effectiveness of the proposed method is proven by means of experimental results. (author)
International Nuclear Information System (INIS)
Lobashev, A.A.; Mostepanenko, V.M.
1993-01-01
Heisenberg formalism is developed for creation-annihilation operators of quantum fields propagating in nonstationary external fields. Quantum fields with spin 0,1/2, 1 are considered in the presence of such external fields as electromagnetic, scalar and the field of nonstationary dielectric properties of nonlinear medium. Elliptic operator parametrically depending on time is constructed. In Heisenberg representation field variables are decomposed over eigenfunction of this operator. The relation between Heisenberg creation-annihilation operators and the operators obtained in the frame of diagonalization of Hamiltonian with Bogoliubov transformations is set up
A multiscale view on inverse statistics and gain/loss asymmetry in financial time series
International Nuclear Information System (INIS)
Siven, Johannes; Lins, Jeffrey; Hansen, Jonas Lundbek
2009-01-01
Researchers have studied the first-passage time of financial time series and observed that the smallest time interval needed for a stock index to move a given distance is typically shorter for negative than for positive price movements. The same is not observed for the index constituents, the individual stocks. We use the discrete wavelet transform to show that this is a long, rather than short, timescale phenomenon—if enough low frequency content of the price process is removed, the asymmetry disappears. We also propose a model which explains the asymmetry in terms of prolonged, correlated downward movements of individual stocks
EDITORIAL: CAMOP: Quantum Non-Stationary Systems CAMOP: Quantum Non-Stationary Systems
Dodonov, Victor V.; Man'ko, Margarita A.
2010-09-01
Although time-dependent quantum systems have been studied since the very beginning of quantum mechanics, they continue to attract the attention of many researchers, and almost every decade new important discoveries or new fields of application are made. Among the impressive results or by-products of these studies, one should note the discovery of the path integral method in the 1940s, coherent and squeezed states in the 1960-70s, quantum tunneling in Josephson contacts and SQUIDs in the 1960s, the theory of time-dependent quantum invariants in the 1960-70s, different forms of quantum master equations in the 1960-70s, the Zeno effect in the 1970s, the concept of geometric phase in the 1980s, decoherence of macroscopic superpositions in the 1980s, quantum non-demolition measurements in the 1980s, dynamics of particles in quantum traps and cavity QED in the 1980-90s, and time-dependent processes in mesoscopic quantum devices in the 1990s. All these topics continue to be the subject of many publications. Now we are witnessing a new wave of interest in quantum non-stationary systems in different areas, from cosmology (the very first moments of the Universe) and quantum field theory (particle pair creation in ultra-strong fields) to elementary particle physics (neutrino oscillations). A rapid increase in the number of theoretical and experimental works on time-dependent phenomena is also observed in quantum optics, quantum information theory and condensed matter physics. Time-dependent tunneling and time-dependent transport in nano-structures are examples of such phenomena. Another emerging direction of study, stimulated by impressive progress in experimental techniques, is related to attempts to observe the quantum behavior of macroscopic objects, such as mirrors interacting with quantum fields in nano-resonators. Quantum effects manifest themselves in the dynamics of nano-electromechanical systems; they are dominant in the quite new and very promising field of circuit
Incremental learning of concept drift in nonstationary environments.
Elwell, Ryan; Polikar, Robi
2011-10-01
We introduce an ensemble of classifiers-based approach for incremental learning of concept drift, characterized by nonstationary environments (NSEs), where the underlying data distributions change over time. The proposed algorithm, named Learn(++). NSE, learns from consecutive batches of data without making any assumptions on the nature or rate of drift; it can learn from such environments that experience constant or variable rate of drift, addition or deletion of concept classes, as well as cyclical drift. The algorithm learns incrementally, as other members of the Learn(++) family of algorithms, that is, without requiring access to previously seen data. Learn(++). NSE trains one new classifier for each batch of data it receives, and combines these classifiers using a dynamically weighted majority voting. The novelty of the approach is in determining the voting weights, based on each classifier's time-adjusted accuracy on current and past environments. This approach allows the algorithm to recognize, and act accordingly, to the changes in underlying data distributions, as well as to a possible reoccurrence of an earlier distribution. We evaluate the algorithm on several synthetic datasets designed to simulate a variety of nonstationary environments, as well as a real-world weather prediction dataset. Comparisons with several other approaches are also included. Results indicate that Learn(++). NSE can track the changing environments very closely, regardless of the type of concept drift. To allow future use, comparison and benchmarking by interested researchers, we also release our data used in this paper. © 2011 IEEE
Nonstationary stochastic charge fluctuations of a dust particle in plasmas.
Shotorban, B
2011-06-01
Stochastic charge fluctuations of a dust particle that are due to discreteness of electrons and ions in plasmas can be described by a one-step process master equation [T. Matsoukas and M. Russell, J. Appl. Phys. 77, 4285 (1995)] with no exact solution. In the present work, using the system size expansion method of Van Kampen along with the linear noise approximation, a Fokker-Planck equation with an exact Gaussian solution is developed by expanding the master equation. The Gaussian solution has time-dependent mean and variance governed by two ordinary differential equations modeling the nonstationary process of dust particle charging. The model is tested via the comparison of its results to the results obtained by solving the master equation numerically. The electron and ion currents are calculated through the orbital motion limited theory. At various times of the nonstationary process of charging, the model results are in a very good agreement with the master equation results. The deviation is more significant when the standard deviation of the charge is comparable to the mean charge in magnitude.
Nonstationary interference and scattering from random media
International Nuclear Information System (INIS)
Nazikian, R.
1991-12-01
For the small angle scattering of coherent plane waves from inhomogeneous random media, the three dimensional mean square distribution of random fluctuations may be recovered from the interferometric detection of the nonstationary modulational structure of the scattered field. Modulational properties of coherent waves scattered from random media are related to nonlocal correlations in the double sideband structure of the Fourier transform of the scattering potential. Such correlations may be expressed in terms of a suitability generalized spectral coherence function for analytic fields
Complex dynamic behaviors of oriented percolation-based financial time series and Hang Seng index
International Nuclear Information System (INIS)
Niu, Hongli; Wang, Jun
2013-01-01
Highlights: • We develop a financial time series model by two-dimensional oriented percolation system. • We investigate the statistical behaviors of returns for HSI and the financial model by chaos-exploring methods. • We forecast the phase point of reconstructed phase space by RBF neural network. -- Abstract: We develop a financial price model by the two-dimensional oriented (directed) percolation system. The oriented percolation model is a directed variant of ordinary (isotropic) percolation, and it is applied to describe the fluctuations of stock prices. In this work, we assume that the price fluctuations result from the participants’ investment attitudes toward the market, and we investigate the information spreading among the traders and the corresponding effect on the price fluctuations. We study the complex dynamic behaviors of return time series of the model by using the multiaspect chaos-exploring methods. And we also explore the corresponding behaviors of the actual market index (Hang Seng Index) for comparison. Further, we introduce the radial basic function (RBF) neural network to train and forecast the phase point of reconstructed phase space
Ludescher, J.; Tsallis, C.; Bunde, A.
2011-09-01
We consider 16 representative financial records (stocks, indices, commodities, and exchange rates) and study the distribution PQ(r) of the interoccurrence times r between daily losses below negative thresholds -Q, for fixed mean interoccurrence time RQ. We find that in all cases, PQ(r) follows the form PQ(r)~1/[(1+(q- 1)βr]1/(q-1), where β and q are universal constants that depend only on RQ, but not on a specific asset. While β depends only slightly on RQ, the q-value increases logarithmically with RQ, q=1+q0 ln(RQ/2), such that for RQ→2, PQ(r) approaches a simple exponential, PQ(r)cong2-r. The fact that PQ does not scale with RQ is due to the multifractality of the financial markets. The analytic form of PQ allows also to estimate both the risk function and the Value-at-Risk, and thus to improve the estimation of the financial risk.
Cook, Steve; Watson, Duncan
2017-03-01
Following its introduction in the seminal study of Osborne (1959), a voluminous literature has emerged examining the returns-volume relationship for financial assets. The present paper revisits this relationship in an examination of the FTSE100 which extends the existing literature in two ways. First, alternative daily measures of the FTSE100 index are used to create differing returns and absolute returns series to employ in an examination of returns-volume causality. Second, rolling regression analysis is utilised to explore potential time variation in the returns-volume relationship. The findings obtained depict a hitherto unconsidered complexity in this relationship with the type of returns series considered and financial crisis found to be significant underlying factors. The implications of the newly derived results for both the understanding of the nature of the returns-volume relationship and the development of theories in connection to it are discussed.
Volatility Behaviors of Financial Time Series by Percolation System on Sierpinski Carpet Lattice
Pei, Anqi; Wang, Jun
2015-01-01
The financial time series is simulated and investigated by the percolation system on the Sierpinski carpet lattice, where percolation is usually employed to describe the behavior of connected clusters in a random graph, and the Sierpinski carpet lattice is a graph which corresponds the fractal — Sierpinski carpet. To study the fluctuation behavior of returns for the financial model and the Shanghai Composite Index, we establish a daily volatility measure — multifractal volatility (MFV) measure to obtain MFV series, which have long-range cross-correlations with squared daily return series. The autoregressive fractionally integrated moving average (ARFIMA) model is used to analyze the MFV series, which performs better when compared to other volatility series. By a comparative study of the multifractality and volatility analysis of the data, the simulation data of the proposed model exhibits very similar behaviors to those of the real stock index, which indicates somewhat rationality of the model to the market application.
Nonlinear Analysis on Cross-Correlation of Financial Time Series by Continuum Percolation System
Niu, Hongli; Wang, Jun
We establish a financial price process by continuum percolation system, in which we attribute price fluctuations to the investors’ attitudes towards the financial market, and consider the clusters in continuum percolation as the investors share the same investment opinion. We investigate the cross-correlations in two return time series, and analyze the multifractal behaviors in this relationship. Further, we study the corresponding behaviors for the real stock indexes of SSE and HSI as well as the liquid stocks pair of SPD and PAB by comparison. To quantify the multifractality in cross-correlation relationship, we employ multifractal detrended cross-correlation analysis method to perform an empirical research for the simulation data and the real markets data.
Volatility behavior of visibility graph EMD financial time series from Ising interacting system
Zhang, Bo; Wang, Jun; Fang, Wen
2015-08-01
A financial market dynamics model is developed and investigated by stochastic Ising system, where the Ising model is the most popular ferromagnetic model in statistical physics systems. Applying two graph based analysis and multiscale entropy method, we investigate and compare the statistical volatility behavior of return time series and the corresponding IMF series derived from the empirical mode decomposition (EMD) method. And the real stock market indices are considered to be comparatively studied with the simulation data of the proposed model. Further, we find that the degree distribution of visibility graph for the simulation series has the power law tails, and the assortative network exhibits the mixing pattern property. All these features are in agreement with the real market data, the research confirms that the financial model established by the Ising system is reasonable.
Financial Distress Prediction Using Discrete-time Hazard Model and Rating Transition Matrix Approach
Tsai, Bi-Huei; Chang, Chih-Huei
2009-08-01
Previous studies used constant cut-off indicator to distinguish distressed firms from non-distressed ones in the one-stage prediction models. However, distressed cut-off indicator must shift according to economic prosperity, rather than remains fixed all the time. This study focuses on Taiwanese listed firms and develops financial distress prediction models based upon the two-stage method. First, this study employs the firm-specific financial ratio and market factors to measure the probability of financial distress based on the discrete-time hazard models. Second, this paper further focuses on macroeconomic factors and applies rating transition matrix approach to determine the distressed cut-off indicator. The prediction models are developed by using the training sample from 1987 to 2004, and their levels of accuracy are compared with the test sample from 2005 to 2007. As for the one-stage prediction model, the model in incorporation with macroeconomic factors does not perform better than that without macroeconomic factors. This suggests that the accuracy is not improved for one-stage models which pool the firm-specific and macroeconomic factors together. In regards to the two stage models, the negative credit cycle index implies the worse economic status during the test period, so the distressed cut-off point is adjusted to increase based on such negative credit cycle index. After the two-stage models employ such adjusted cut-off point to discriminate the distressed firms from non-distressed ones, their error of misclassification becomes lower than that of one-stage ones. The two-stage models presented in this paper have incremental usefulness in predicting financial distress.
Cycles, determinism and persistence in agent-based games and financial time-series
Satinover, J. B.; Sornette, D.
2008-01-01
The Minority Game (MG), the Majority Game (MAJG) and the Dollar Game ($G) are important and closely-related versions of market-entry games designed to model different features of real-world financial markets. In a variant of these games, agents measure the performance of their available strategies over a fixed-length rolling window of prior time-steps. These are the so-called Time Horizon MG/MAJG/$G (THMG, THMAJG, TH$G). Their probabilistic dynamics may be completely characterized in Markov-c...
Tracking of Nonstationary Noise Based on Data-Driven Recursive Noise Power Estimation
Erkelens, J.S.; Heusdens, R.
2008-01-01
This paper considers estimation of the noise spectral variance from speech signals contaminated by highly nonstationary noise sources. The method can accurately track fast changes in noise power level (up to about 10 dB/s). In each time frame, for each frequency bin, the noise variance estimate is
Pauls-Worm, K.G.J.; Hendrix, E.M.T.; Haijema, R.; Vorst, van der J.G.A.J.
2014-01-01
We study the practical production planning problem of a food producer facing a non-stationary erratic demand for a perishable product with a fixed life time. In meeting the uncertain demand, the food producer uses a FIFO issuing policy. The food producer aims at meeting a certain service level at
Inventory control for a perishable product with non-stationary demand and service level constraints
Pauls-Worm, K.G.J.; Hendrix, E.M.T.; Haijema, R.; Vorst, van der J.G.A.J.
2013-01-01
We study the practical production planning problem of a food producer facing a non-stationary erratic demand for a perishable product with a fixed life time. In meeting the uncertain demand, the food producer uses a FIFO issuing policy. The food producer aims at meeting a certain service level at
Influence of the time scale on the construction of financial networks.
Emmert-Streib, Frank; Dehmer, Matthias
2010-09-30
In this paper we investigate the definition and formation of financial networks. Specifically, we study the influence of the time scale on their construction. For our analysis we use correlation-based networks obtained from the daily closing prices of stock market data. More precisely, we use the stocks that currently comprise the Dow Jones Industrial Average (DJIA) and estimate financial networks where nodes correspond to stocks and edges correspond to none vanishing correlation coefficients. That means only if a correlation coefficient is statistically significant different from zero, we include an edge in the network. This construction procedure results in unweighted, undirected networks. By separating the time series of stock prices in non-overlapping intervals, we obtain one network per interval. The length of these intervals corresponds to the time scale of the data, whose influence on the construction of the networks will be studied in this paper. Numerical analysis of four different measures in dependence on the time scale for the construction of networks allows us to gain insights about the intrinsic time scale of the stock market with respect to a meaningful graph-theoretical analysis.
Time series analysis of the developed financial markets' integration using visibility graphs
Zhuang, Enyu; Small, Michael; Feng, Gang
2014-09-01
A time series representing the developed financial markets' segmentation from 1973 to 2012 is studied. The time series reveals an obvious market integration trend. To further uncover the features of this time series, we divide it into seven windows and generate seven visibility graphs. The measuring capabilities of the visibility graphs provide means to quantitatively analyze the original time series. It is found that the important historical incidents that influenced market integration coincide with variations in the measured graphical node degree. Through the measure of neighborhood span, the frequencies of the historical incidents are disclosed. Moreover, it is also found that large "cycles" and significant noise in the time series are linked to large and small communities in the generated visibility graphs. For large cycles, how historical incidents significantly affected market integration is distinguished by density and compactness of the corresponding communities.
Generalized Predictive Control for Non-Stationary Systems
DEFF Research Database (Denmark)
Palsson, Olafur Petur; Madsen, Henrik; Søgaard, Henning Tangen
1994-01-01
This paper shows how the generalized predictive control (GPC) can be extended to non-stationary (time-varying) systems. If the time-variation is slow, then the classical GPC can be used in context with an adaptive estimation procedure of a time-invariant ARIMAX model. However, in this paper prior...... knowledge concerning the nature of the parameter variations is assumed available. The GPC is based on the assumption that the prediction of the system output can be expressed as a linear combination of present and future controls. Since the Diophantine equation cannot be used due to the time......-variation of the parameters, the optimal prediction is found as the general conditional expectation of the system output. The underlying model is of an ARMAX-type instead of an ARIMAX-type as in the original version of the GPC (Clarke, D. W., C. Mohtadi and P. S. Tuffs (1987). Automatica, 23, 137-148) and almost all later...
Dynamics of nonstationary dipole vortices
DEFF Research Database (Denmark)
Hesthaven, J.S.; Lynov, Jens-Peter; Nycander, J.
1993-01-01
The dynamics of tilted dipole vortices in the equivalent barotropic vorticity (or Hasegawa-Mima) equation is studied. A recent theory is compared with numerical simulations and found to describe the short time behavior of dipole vortices well. In the long time limit the dipoles are found to eithe...... disintegrate or relax toward a steady eastward propagating dipole vortex. This relaxation is a consequence of nonviscous enstrophy loss by the dipole vortex....
Shi, Yingzhong; Chung, Fu-Lai; Wang, Shitong
2015-09-01
Recently, a time-adaptive support vector machine (TA-SVM) is proposed for handling nonstationary datasets. While attractive performance has been reported and the new classifier is distinctive in simultaneously solving several SVM subclassifiers locally and globally by using an elegant SVM formulation in an alternative kernel space, the coupling of subclassifiers brings in the computation of matrix inversion, thus resulting to suffer from high computational burden in large nonstationary dataset applications. To overcome this shortcoming, an improved TA-SVM (ITA-SVM) is proposed using a common vector shared by all the SVM subclassifiers involved. ITA-SVM not only keeps an SVM formulation, but also avoids the computation of matrix inversion. Thus, we can realize its fast version, that is, improved time-adaptive core vector machine (ITA-CVM) for large nonstationary datasets by using the CVM technique. ITA-CVM has the merit of asymptotic linear time complexity for large nonstationary datasets as well as inherits the advantage of TA-SVM. The effectiveness of the proposed classifiers ITA-SVM and ITA-CVM is also experimentally confirmed.
How Volatilities Nonlocal in Time Affect the Price Dynamics in Complex Financial Systems
Tan, Lei; Zheng, Bo; Chen, Jun-Jie; Jiang, Xiong-Fei
2015-01-01
What is the dominating mechanism of the price dynamics in financial systems is of great interest to scientists. The problem whether and how volatilities affect the price movement draws much attention. Although many efforts have been made, it remains challenging. Physicists usually apply the concepts and methods in statistical physics, such as temporal correlation functions, to study financial dynamics. However, the usual volatility-return correlation function, which is local in time, typically fluctuates around zero. Here we construct dynamic observables nonlocal in time to explore the volatility-return correlation, based on the empirical data of hundreds of individual stocks and 25 stock market indices in different countries. Strikingly, the correlation is discovered to be non-zero, with an amplitude of a few percent and a duration of over two weeks. This result provides compelling evidence that past volatilities nonlocal in time affect future returns. Further, we introduce an agent-based model with a novel mechanism, that is, the asymmetric trading preference in volatile and stable markets, to understand the microscopic origin of the volatility-return correlation nonlocal in time. PMID:25723154
How volatilities nonlocal in time affect the price dynamics in complex financial systems.
Directory of Open Access Journals (Sweden)
Lei Tan
Full Text Available What is the dominating mechanism of the price dynamics in financial systems is of great interest to scientists. The problem whether and how volatilities affect the price movement draws much attention. Although many efforts have been made, it remains challenging. Physicists usually apply the concepts and methods in statistical physics, such as temporal correlation functions, to study financial dynamics. However, the usual volatility-return correlation function, which is local in time, typically fluctuates around zero. Here we construct dynamic observables nonlocal in time to explore the volatility-return correlation, based on the empirical data of hundreds of individual stocks and 25 stock market indices in different countries. Strikingly, the correlation is discovered to be non-zero, with an amplitude of a few percent and a duration of over two weeks. This result provides compelling evidence that past volatilities nonlocal in time affect future returns. Further, we introduce an agent-based model with a novel mechanism, that is, the asymmetric trading preference in volatile and stable markets, to understand the microscopic origin of the volatility-return correlation nonlocal in time.
Coupling detrended fluctuation analysis for analyzing coupled nonstationary signals
Hedayatifar, L.; Vahabi, M.; Jafari, G. R.
2011-08-01
When many variables are coupled to each other, a single case study could not give us thorough and precise information. When these time series are stationary, different methods of random matrix analysis and complex networks can be used. But, in nonstationary cases, the multifractal-detrended-cross-correlation-analysis (MF-DXA) method was introduced for just two coupled time series. In this article, we have extended the MF-DXA to the method of coupling detrended fluctuation analysis (CDFA) for the case when more than two series are correlated to each other. Here, we have calculated the multifractal properties of the coupled time series, and by comparing CDFA results of the original series with those of the shuffled and surrogate series, we can estimate the source of multifractality and the extent to which our series are coupled to each other. We illustrate the method by selected examples from air pollution and foreign exchange rates.
A Phase Vocoder Based on Nonstationary Gabor Frames
DEFF Research Database (Denmark)
Ottosen, Emil Solsbæk; Dörfler, Monika
2017-01-01
We propose a new algorithm for time stretching music signals based on the theory of nonstationary Gabor frames (NSGFs). The algorithm extends the techniques of the classical phase vocoder (PV) by incorporating adaptive timefrequency (TF) representations and adaptive phase locking. The adaptive TF...... representations imply good time resolution for the onsets of attack transients and good frequency resolution for the sinusoidal components. We estimate the phase values only at peak channels and the remaining phases are then locked to the values of the peaks in an adaptive manner. During attack transients we keep...... that with just three times as many TF coefficients as signal samples, artifacts such as phasiness and transient smearing can be greatly reduced compared to the classical PV. The proposed algorithm is tested on both synthetic and real world signals and compared with state of the art algorithms in a reproducible...
Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series
Morales, Raffaello; Di Matteo, T.; Gramatica, Ruggero; Aste, Tomaso
2012-06-01
We investigate the use of the Hurst exponent, dynamically computed over a weighted moving time-window, to evaluate the level of stability/instability of financial firms. Financial firms bailed-out as a consequence of the 2007-2008 credit crisis show a neat increase with time of the generalized Hurst exponent in the period preceding the unfolding of the crisis. Conversely, firms belonging to other market sectors, which suffered the least throughout the crisis, show opposite behaviors. We find that the multifractality of the bailed-out firms increase at the crisis suggesting that the multi fractal properties of the time series are changing. These findings suggest the possibility of using the scaling behavior as a tool to track the level of stability of a firm. In this paper, we introduce a method to compute the generalized Hurst exponent which assigns larger weights to more recent events with respect to older ones. In this way large fluctuations in the remote past are less likely to influence the recent past. We also investigate the scaling associated with the tails of the log-returns distributions and compare this scaling with the scaling associated with the Hurst exponent, observing that the processes underlying the price dynamics of these firms are truly multi-scaling.
Measurement of Non-Stationary Characteristics of a Landfall Typhoon at the Jiangyin Bridge Site
Directory of Open Access Journals (Sweden)
Xuhui He
2017-09-01
Full Text Available The wind-sensitive long-span suspension bridge is a vital element in land transportation. Understanding the wind characteristics at the bridge site is thus of great significance to the wind- resistant analysis of such a flexible structure. In this study, a strong wind event from a landfall typhoon called Soudelor recorded at the Jiangyin Bridge site with the anemometer is taken as the research object. As inherent time-varying trends are frequently captured in typhoon events, the wind characteristics of Soudelor are analyzed in a non-stationary perspective. The time-varying mean is first extracted with the wavelet-based self-adaptive method. Then, the non-stationary turbulent wind characteristics, e.g.; turbulence intensity, gust factor, turbulence integral scale, and power spectral density, are investigated and compared with the results from the stationary analysis. The comparison highlights the importance of non-stationary considerations of typhoon events, and a transition from stationarity to non-stationarity for the analysis of wind effects. The analytical results could help enrich the database of non-stationary wind characteristics, and are expected to provide references for the wind-resistant analysis of engineering structures in similar areas.
Measurement of Non-Stationary Characteristics of a Landfall Typhoon at the Jiangyin Bridge Site.
He, Xuhui; Qin, Hongxi; Tao, Tianyou; Liu, Wenshuo; Wang, Hao
2017-09-22
The wind-sensitive long-span suspension bridge is a vital element in land transportation. Understanding the wind characteristics at the bridge site is thus of great significance to the wind- resistant analysis of such a flexible structure. In this study, a strong wind event from a landfall typhoon called Soudelor recorded at the Jiangyin Bridge site with the anemometer is taken as the research object. As inherent time-varying trends are frequently captured in typhoon events, the wind characteristics of Soudelor are analyzed in a non-stationary perspective. The time-varying mean is first extracted with the wavelet-based self-adaptive method. Then, the non-stationary turbulent wind characteristics, e.g.; turbulence intensity, gust factor, turbulence integral scale, and power spectral density, are investigated and compared with the results from the stationary analysis. The comparison highlights the importance of non-stationary considerations of typhoon events, and a transition from stationarity to non-stationarity for the analysis of wind effects. The analytical results could help enrich the database of non-stationary wind characteristics, and are expected to provide references for the wind-resistant analysis of engineering structures in similar areas.
Stylised facts of financial time series and hidden Markov models in continuous time
DEFF Research Database (Denmark)
Nystrup, Peter; Madsen, Henrik; Lindström, Erik
2015-01-01
presents an extension to continuous time where it is possible to increase the number of states with a linear rather than quadratic growth in the number of parameters. The possibility of increasing the number of states leads to a better fit to both the distributional and temporal properties of daily returns....
Nonstationary signals phase-energy approach-theory and simulations
Klein, R; Braun, S; 10.1006/mssp.2001.1398
2001-01-01
Modern time-frequency methods are intended to deal with a variety of nonstationary signals. One specific class, prevalent in the area of rotating machines, is that of harmonic signals of varying frequencies and amplitude. This paper presents a new adaptive phase-energy (APE) approach for time-frequency representation of varying harmonic signals. It is based on the concept of phase (frequency) paths and the instantaneous power spectral density (PSD). It is this path which represents the dynamic behaviour of the system generating the observed signal. The proposed method utilises dynamic filters based on an extended Nyquist theorem, enabling extraction of signal components with optimal signal-to-noise ratio. The APE detects the most energetic harmonic components (frequency paths) in the analysed signal. Tests on simulated signals show the superiority of the APE in resolution and resolving power as compared to STFT and wavelets wave- packet decomposition. The dynamic filters also enable the reconstruction of the ...
Multiscale synchrony behaviors of paired financial time series by 3D multi-continuum percolation
Wang, M.; Wang, J.; Wang, B. T.
2018-02-01
Multiscale synchrony behaviors and nonlinear dynamics of paired financial time series are investigated, in an attempt to study the cross correlation relationships between two stock markets. A random stock price model is developed by a new system called three-dimensional (3D) multi-continuum percolation system, which is utilized to imitate the formation mechanism of price dynamics and explain the nonlinear behaviors found in financial time series. We assume that the price fluctuations are caused by the spread of investment information. The cluster of 3D multi-continuum percolation represents the cluster of investors who share the same investment attitude. In this paper, we focus on the paired return series, the paired volatility series, and the paired intrinsic mode functions which are decomposed by empirical mode decomposition. A new cross recurrence quantification analysis is put forward, combining with multiscale cross-sample entropy, to investigate the multiscale synchrony of these paired series from the proposed model. The corresponding research is also carried out for two China stock markets as comparison.
A simple nonstationary-volatility robust panel unit root test
Demetrescu, Matei; Hanck, Christoph
2012-01-01
We propose an IV panel unit root test robust to nonstationary error volatility. Its finite-sample performance is convincing even for many units and strong cross-correlation. An application to GDP prices illustrates the inferential impact of nonstationary volatility. (C) 2012 Elsevier B.V. All rights
Analysis of stress and deformation in non-stationary creep
International Nuclear Information System (INIS)
Feijoo, R.A.; Taroco, E.; Guerreiro, J.N.C.
1980-12-01
A variational method and its algorithm are presented; they permit the analysis of stress and deformation in non-stationary creep. This algorithm is applied to an infinite cylinder submitted to an internal pressure. The solution obtained is compared with the solution of non-stationary creep problems [pt
Agent-Based Simulation of Financial Markets: A Modular, Continuous-time Approach
K. Boer-Sorban (Katalin)
2008-01-01
textabstractThe dynamics of financial markets is subject of much debate among researchers and financial experts trying to understand and explain how financial markets work and traders behave. Diversified explanations result from the complexity of markets, and the hardly observable aspects of price
Pavlickova, Hana; Bremner, Stephen A; Priebe, Stefan
2015-08-01
A recent cluster-randomized controlled trial found that offering financial incentives improves adherence to long-acting injectable antipsychotics (LAIs). The present study investigates whether the impact of incentives diminishes over time and whether the improvement in adherence is linked to the amount of incentives offered. Seventy-three teams with 141 patients with psychotic disorders (using ICD-10) were randomized to the intervention or control group. Over 1 year, patients in the intervention group received £15 (US $23) for each LAI, while control patients received treatment as usual. Adherence levels, ie, the percentage of prescribed LAIs that were received, were calculated for quarterly intervals. The amount of incentives offered was calculated from the treatment cycle at baseline. Multilevel models were used to examine the time course of the effect of incentives and the effect of the amount of incentives offered on adherence. Adherence increased in both the intervention and the control group over time by an average of 4.2% per quarterly interval (95% CI, 2.8%-5.6%; P time and treatment group. Further, a higher total amount of incentives was associated with poorer adherence (βbootstrapped = -0.11; 95% CIbootstrapped, -0.20 to -0.01; P = .023). A substantial effect of financial incentives on adherence to LAIs occurs within the first 3 months of the intervention and is sustained over 1 year. A higher total amount of incentives does not increase the effect. ISRCTN.com identifier: ISRCTN77769281 and UKCRN.org identifier: 7033. © Copyright 2015 Physicians Postgraduate Press, Inc.
A Nonstationary Markov Model Detects Directional Evolution in Hymenopteran Morphology.
Klopfstein, Seraina; Vilhelmsen, Lars; Ronquist, Fredrik
2015-11-01
Directional evolution has played an important role in shaping the morphological, ecological, and molecular diversity of life. However, standard substitution models assume stationarity of the evolutionary process over the time scale examined, thus impeding the study of directionality. Here we explore a simple, nonstationary model of evolution for discrete data, which assumes that the state frequencies at the root differ from the equilibrium frequencies of the homogeneous evolutionary process along the rest of the tree (i.e., the process is nonstationary, nonreversible, but homogeneous). Within this framework, we develop a Bayesian approach for testing directional versus stationary evolution using a reversible-jump algorithm. Simulations show that when only data from extant taxa are available, the success in inferring directionality is strongly dependent on the evolutionary rate, the shape of the tree, the relative branch lengths, and the number of taxa. Given suitable evolutionary rates (0.1-0.5 expected substitutions between root and tips), accounting for directionality improves tree inference and often allows correct rooting of the tree without the use of an outgroup. As an empirical test, we apply our method to study directional evolution in hymenopteran morphology. We focus on three character systems: wing veins, muscles, and sclerites. We find strong support for a trend toward loss of wing veins and muscles, while stationarity cannot be ruled out for sclerites. Adding fossil and time information in a total-evidence dating approach, we show that accounting for directionality results in more precise estimates not only of the ancestral state at the root of the tree, but also of the divergence times. Our model relaxes the assumption of stationarity and reversibility by adding a minimum of additional parameters, and is thus well suited to studying the nature of the evolutionary process in data sets of limited size, such as morphology and ecology. © The Author
Modeling Financial Time Series Based on a Market Microstructure Model with Leverage Effect
Directory of Open Access Journals (Sweden)
Yanhui Xi
2016-01-01
Full Text Available The basic market microstructure model specifies that the price/return innovation and the volatility innovation are independent Gaussian white noise processes. However, the financial leverage effect has been found to be statistically significant in many financial time series. In this paper, a novel market microstructure model with leverage effects is proposed. The model specification assumed a negative correlation in the errors between the price/return innovation and the volatility innovation. With the new representations, a theoretical explanation of leverage effect is provided. Simulated data and daily stock market indices (Shanghai composite index, Shenzhen component index, and Standard and Poor’s 500 Composite index via Bayesian Markov Chain Monte Carlo (MCMC method are used to estimate the leverage market microstructure model. The results verify the effectiveness of the model and its estimation approach proposed in the paper and also indicate that the stock markets have strong leverage effects. Compared with the classical leverage stochastic volatility (SV model in terms of DIC (Deviance Information Criterion, the leverage market microstructure model fits the data better.
ENTREPRENEURSHIP IN TIMES OF ECONOMIC AND FINANCIAL CRISES, METHODS OF ADAPTATION AND SURVIVAL.
Directory of Open Access Journals (Sweden)
Radu Oprea
2011-12-01
Full Text Available This paper shows the main results of a research activity conducted in the South – East region of Romania during November 2009, over 117 small and medium-sized enterprises. The results help to better explain some of the social problems that have been generated in the region as a snow ball effect, due to the economic and financial crisis. The research has revealed the following:The majority of the employees of the companies that were interviewed do not participate in training courses related to project management and personal development. However, company administrators consider that such courses are useful to increase competitiveness in times of economic and financial crises. Personnel under 40 years of age suffer from a lack of professional training and dedication to job requirements. Companies have expressed an interest in accessing European Union funding. However, they do not have complete information that would allow them to start a project and finalize it. This lack of information is mainly due to lack of access to specialists who would write the projects and submit them. The majority of entrepreneurs consider they cannot write the projects themselves but on the other hand they do not have access to consulting companies or other organizations that could help them. Their main information source is the mass-media.As a result, companies have adjusted to the effects of the economic crisis, diminishing their activity and laying off people, decreasing the running expenses and stopping investing in their development.
Real-Time Diffusion of Information on Twitter and the Financial Markets.
Tafti, Ali; Zotti, Ryan; Jank, Wolfgang
2016-01-01
Do spikes in Twitter chatter about a firm precede unusual stock market trading activity for that firm? If so, Twitter activity may provide useful information about impending financial market activity in real-time. We study the real-time relationship between chatter on Twitter and the stock trading volume of 96 firms listed on the Nasdaq 100, during 193 days of trading in the period from May 21, 2012 to September 18, 2013. We identify observations featuring firm-specific spikes in Twitter activity, and randomly assign each observation to a ten-minute increment matching on the firm and a number of repeating time indicators. We examine the extent that unusual levels of chatter on Twitter about a firm portend an oncoming surge of trading of its stock within the hour, over and above what would normally be expected for the stock for that time of day and day of week. We also compare the findings from our explanatory model to the predictive power of Tweets. Although we find a compelling and potentially informative real-time relationship between Twitter activity and trading volume, our forecasting exercise highlights how difficult it can be to make use of this information for monetary gain.
World pharmaceuticals--Financial Times tenth annual conference. 22-23 April 1999, London, UK.
Muhsin, M
1999-07-01
This two-day conference was organized by The Financial Times, in association with PriceWaterhouseCoopers LLP. The general theme of the event was the state of the healthcare industry, past, present and future. The main areas covered included addressing the challenges of the 1990s, anticipating the challenges of the next decade, the changing shape of global marketing, IT in healthcare, consolidation challenges, shareholder expectations, and new strategies and technologies for growth sustenance within the industry. Key speakers within the industry addressed these issues to an audience of approximately 200 healthcare business executives. The first day was chaired by Mr Robert Cawthorn (Chairman Emeritus, Rhone-Poulenc Rorer Inc) and the second by Professor Trevor Jones (Director General, Association of the British Pharmaceutical Industry).
2010-01-01
... file financial statements at the time of request for a draw. 108.1220 Section 108.1220 Business Credit... Nmvc Company § 108.1220 Requirement for NMVC Company to file financial statements at the time of... financial statement on Form 468 (Short Form); and (2) File a statement of no material adverse change in your...
Refined composite multiscale weighted-permutation entropy of financial time series
Zhang, Yongping; Shang, Pengjian
2018-04-01
For quantifying the complexity of nonlinear systems, multiscale weighted-permutation entropy (MWPE) has recently been proposed. MWPE has incorporated amplitude information and been applied to account for the multiple inherent dynamics of time series. However, MWPE may be unreliable, because its estimated values show large fluctuation for slight variation of the data locations, and a significant distinction only for the different length of time series. Therefore, we propose the refined composite multiscale weighted-permutation entropy (RCMWPE). By comparing the RCMWPE results with other methods' results on both synthetic data and financial time series, RCMWPE method shows not only the advantages inherited from MWPE but also lower sensitivity to the data locations, more stable and much less dependent on the length of time series. Moreover, we present and discuss the results of RCMWPE method on the daily price return series from Asian and European stock markets. There are significant differences between Asian markets and European markets, and the entropy values of Hang Seng Index (HSI) are close to but higher than those of European markets. The reliability of the proposed RCMWPE method has been supported by simulations on generated and real data. It could be applied to a variety of fields to quantify the complexity of the systems over multiple scales more accurately.
Partitioning uncertainty in streamflow projections under nonstationary model conditions
Chawla, Ila; Mujumdar, P. P.
2018-02-01
Assessing the impacts of Land Use (LU) and climate change on future streamflow projections is necessary for efficient management of water resources. However, model projections are burdened with significant uncertainty arising from various sources. Most of the previous studies have considered climate models and scenarios as major sources of uncertainty, but uncertainties introduced by land use change and hydrologic model assumptions are rarely investigated. In this paper an attempt is made to segregate the contribution from (i) general circulation models (GCMs), (ii) emission scenarios, (iii) land use scenarios, (iv) stationarity assumption of the hydrologic model, and (v) internal variability of the processes, to overall uncertainty in streamflow projections using analysis of variance (ANOVA) approach. Generally, most of the impact assessment studies are carried out with unchanging hydrologic model parameters in future. It is, however, necessary to address the nonstationarity in model parameters with changing land use and climate. In this paper, a regression based methodology is presented to obtain the hydrologic model parameters with changing land use and climate scenarios in future. The Upper Ganga Basin (UGB) in India is used as a case study to demonstrate the methodology. The semi-distributed Variable Infiltration Capacity (VIC) model is set-up over the basin, under nonstationary conditions. Results indicate that model parameters vary with time, thereby invalidating the often-used assumption of model stationarity. The streamflow in UGB under the nonstationary model condition is found to reduce in future. The flows are also found to be sensitive to changes in land use. Segregation results suggest that model stationarity assumption and GCMs along with their interactions with emission scenarios, act as dominant sources of uncertainty. This paper provides a generalized framework for hydrologists to examine stationarity assumption of models before considering them
Non-stationary (13)C-metabolic flux ratio analysis.
Hörl, Manuel; Schnidder, Julian; Sauer, Uwe; Zamboni, Nicola
2013-12-01
(13)C-metabolic flux analysis ((13)C-MFA) has become a key method for metabolic engineering and systems biology. In the most common methodology, fluxes are calculated by global isotopomer balancing and iterative fitting to stationary (13)C-labeling data. This approach requires a closed carbon balance, long-lasting metabolic steady state, and the detection of (13)C-patterns in a large number of metabolites. These restrictions mostly reduced the application of (13)C-MFA to the central carbon metabolism of well-studied model organisms grown in minimal media with a single carbon source. Here we introduce non-stationary (13)C-metabolic flux ratio analysis as a novel method for (13)C-MFA to allow estimating local, relative fluxes from ultra-short (13)C-labeling experiments and without the need for global isotopomer balancing. The approach relies on the acquisition of non-stationary (13)C-labeling data exclusively for metabolites in the proximity of a node of converging fluxes and a local parameter estimation with a system of ordinary differential equations. We developed a generalized workflow that takes into account reaction types and the availability of mass spectrometric data on molecular ions or fragments for data processing, modeling, parameter and error estimation. We demonstrated the approach by analyzing three key nodes of converging fluxes in central metabolism of Bacillus subtilis. We obtained flux estimates that are in agreement with published results obtained from steady state experiments, but reduced the duration of the necessary (13)C-labeling experiment to less than a minute. These results show that our strategy enables to formally estimate relative pathway fluxes on extremely short time scale, neglecting cellular carbon balancing. Hence this approach paves the road to targeted (13)C-MFA in dynamic systems with multiple carbon sources and towards rich media. © 2013 Wiley Periodicals, Inc.
International Nuclear Information System (INIS)
Kraus, B.; Tittel, W.; Gisin, N.; Nilsson, M.; Kroell, S.; Cirac, J. I.
2006-01-01
We propose a method for efficient storage and recall of arbitrary nonstationary light fields, such as, for instance, single photon time-bin qubits or intense fields, in optically dense atomic ensembles. Our approach to quantum memory is based on controlled, reversible, inhomogeneous broadening and relies on a hidden time-reversal symmetry of the optical Bloch equations describing the propagation of the light field. We briefly discuss experimental realizations of our proposal
A Novel Simulator of Nonstationary Random MIMO Channels in Rayleigh Fading Scenarios
Directory of Open Access Journals (Sweden)
Qiuming Zhu
2016-01-01
Full Text Available For simulations of nonstationary multiple-input multiple-output (MIMO Rayleigh fading channels in time-variant scattering environments, a novel channel simulator is proposed based on the superposition of chirp signals. This new method has the advantages of low complexity and implementation simplicity as the sum of sinusoids (SOS method. In order to reproduce realistic time varying statistics for dynamic channels, an efficient parameter computation method is also proposed for updating the frequency parameters of employed chirp signals. Simulation results indicate that the proposed simulator is effective in generating nonstationary MIMO channels with close approximation of the time-variant statistical characteristics in accordance with the expected theoretical counterparts.
Non-stationary dynamics in the bouncing ball: A wavelet perspective
Energy Technology Data Exchange (ETDEWEB)
Behera, Abhinna K., E-mail: abhinna@iiserkol.ac.in; Panigrahi, Prasanta K., E-mail: pprasanta@iiserkol.ac.in [Department of Physical Sciences, Indian Institute of Science Education and Research (IISER) Kolkata, Mohanpur 741246 (India); Sekar Iyengar, A. N., E-mail: ansekar.iyengar@saha.ac.in [Plasma Physics Division, Saha Institute of Nuclear Physics (SINP), Sector 1, Block-AF, Bidhannagar, Kolkata 700064 (India)
2014-12-01
The non-stationary dynamics of a bouncing ball, comprising both periodic as well as chaotic behavior, is studied through wavelet transform. The multi-scale characterization of the time series displays clear signatures of self-similarity, complex scaling behavior, and periodicity. Self-similar behavior is quantified by the generalized Hurst exponent, obtained through both wavelet based multi-fractal detrended fluctuation analysis and Fourier methods. The scale dependent variable window size of the wavelets aptly captures both the transients and non-stationary periodic behavior, including the phase synchronization of different modes. The optimal time-frequency localization of the continuous Morlet wavelet is found to delineate the scales corresponding to neutral turbulence, viscous dissipation regions, and different time varying periodic modulations.
Board diversity and financial performance: A graphical time-series approach
Directory of Open Access Journals (Sweden)
Cobus CH Taljaard
2015-08-01
Full Text Available Directors need to guide and govern companies on behalf of and for the benefit of shareholders and stakeholders. However questions remain as to whether boards with higher levels of diversity amongst directors are better equipped to fulfil their fiduciary duty than boards with lower levels of diversity. This research examines whether increased levels of diversity within boards are associated with improved financial performance to shareholders. From the literature, several theoretical frameworks that could explain why increased diversity might or might not lead to improved board performance were noted. Share returns and directors’ demographic data were collected for a sample of the largest 40 companies listed on the JSE from 2000 to 2013. This data was analysed using Muller and Ward’s (2013 investment style engine by forming portfolios of companies based on board-diversity constructs. Time-series graphs of cumulative portfolio market returns were analysed to determine if the diversity dimensions tested were associated with improved share performance. The results show that racial diversity within boards is not associated with financial performance. However, increased gender diversity and younger average board age are shown to have strong associations with improved share price performance. These findings are mainly attributed to agency-, resource dependency, human capital and signalling theories. Increased diversity is seen to bolster independence and lessen agency problems. Rising diversity levels also enlarge boards’ external networks, allowing diverse stakeholders’ needs to be accommodated and limiting dependence on strategic resources. Finally, as human capital is increased, the collection of different skills and experiences are associated with better performance. The results, based on a more robust methodology and improved data set, provide additional support to previous studies.
Scaling symmetry, renormalization, and time series modeling: the case of financial assets dynamics.
Zamparo, Marco; Baldovin, Fulvio; Caraglio, Michele; Stella, Attilio L
2013-12-01
We present and discuss a stochastic model of financial assets dynamics based on the idea of an inverse renormalization group strategy. With this strategy we construct the multivariate distributions of elementary returns based on the scaling with time of the probability density of their aggregates. In its simplest version the model is the product of an endogenous autoregressive component and a random rescaling factor designed to embody also exogenous influences. Mathematical properties like increments' stationarity and ergodicity can be proven. Thanks to the relatively low number of parameters, model calibration can be conveniently based on a method of moments, as exemplified in the case of historical data of the S&P500 index. The calibrated model accounts very well for many stylized facts, like volatility clustering, power-law decay of the volatility autocorrelation function, and multiscaling with time of the aggregated return distribution. In agreement with empirical evidence in finance, the dynamics is not invariant under time reversal, and, with suitable generalizations, skewness of the return distribution and leverage effects can be included. The analytical tractability of the model opens interesting perspectives for applications, for instance, in terms of obtaining closed formulas for derivative pricing. Further important features are the possibility of making contact, in certain limits, with autoregressive models widely used in finance and the possibility of partially resolving the long- and short-memory components of the volatility, with consistent results when applied to historical series.
Scaling symmetry, renormalization, and time series modeling: The case of financial assets dynamics
Zamparo, Marco; Baldovin, Fulvio; Caraglio, Michele; Stella, Attilio L.
2013-12-01
We present and discuss a stochastic model of financial assets dynamics based on the idea of an inverse renormalization group strategy. With this strategy we construct the multivariate distributions of elementary returns based on the scaling with time of the probability density of their aggregates. In its simplest version the model is the product of an endogenous autoregressive component and a random rescaling factor designed to embody also exogenous influences. Mathematical properties like increments’ stationarity and ergodicity can be proven. Thanks to the relatively low number of parameters, model calibration can be conveniently based on a method of moments, as exemplified in the case of historical data of the S&P500 index. The calibrated model accounts very well for many stylized facts, like volatility clustering, power-law decay of the volatility autocorrelation function, and multiscaling with time of the aggregated return distribution. In agreement with empirical evidence in finance, the dynamics is not invariant under time reversal, and, with suitable generalizations, skewness of the return distribution and leverage effects can be included. The analytical tractability of the model opens interesting perspectives for applications, for instance, in terms of obtaining closed formulas for derivative pricing. Further important features are the possibility of making contact, in certain limits, with autoregressive models widely used in finance and the possibility of partially resolving the long- and short-memory components of the volatility, with consistent results when applied to historical series.
Indexation and causation of financial markets
Tanokura, Yoko
2015-01-01
This book presents a new statistical method of constructing a price index of a financial asset where the price distributions are skewed and heavy-tailed and investigates the effectiveness of the method. In order to fully reflect the movements of prices or returns on a financial asset, the index should reflect their distributions. However, they are often heavy-tailed and possibly skewed, and identifying them directly is not easy. This book first develops an index construction method depending on the price distributions, by using nonstationary time series analysis. Firstly, the long-term trend of the distributions of the optimal Box–Cox transformed prices is estimated by fitting a trend model with time-varying observation noises. By applying state space modeling, the estimation is performed and missing observations are automatically interpolated. Finally, the index is defined by taking the inverse Box–Cox transformation of the optimal long-term trend. This book applies the method to various financial data. ...
King, Elizabeth K.; Johnson, Amy V.; Cassidy, Deborah J.; Wang, Yudan C.; Lower, Joanna K.; Kintner-Duffy, Victoria L.
2016-01-01
The current study examined associations among teachers' financial well-being, including teachers' wages and their perceptions of their ability to pay for basic expenses, and teachers' work time supports, including teachers' paid planning time, vacation days, and sick days, and children's positive emotional expressions and behaviors in preschool…
Certification of Financial Aid Administrators: Is It Time to Move Forward?
Peterson, Stacey A.
2017-01-01
Financial aid administrators administer various aspects of financial assistance programs; oversee, direct, coordinate, evaluate, and provide training for program activities and the personnel who manage office operations and supervise support staff; and ensure alignment of student and institutional needs while protecting the public interest. They…
2016-03-01
each IDF curve and subsequently used to force a calibrated and validated precipitation - runoff model. Probability-based, risk-informed hydrologic...ERDC/CHL CHETN-X-2 March 2016 Approved for public release; distribution is unlimited. Bayesian Inference of Nonstationary Precipitation Intensity...based means by which to develop local precipitation Intensity-Duration-Frequency (IDF) curves using historical rainfall time series data collected for
Bučar, Bojan
2007-01-01
The assumption that non-stationary sorption processes associated with wood canbe evaluated by analysis of their transient system response to the disturbance developed is undoubtedly correct. In general it is, in fact, possible to obtain by time analysis of the transient phenomenon - involving the transition into an arbitrary new state of equilibrium - all data required for a credible evaluation of the observed system. Evaluation of moisture movement during drying or moistening requires determ...
Non-stationary Condition Monitoring of large diesel engines with the AEWATT toolbox
DEFF Research Database (Denmark)
Pontoppidan, Niels Henrik; Larsen, Jan; Sigurdsson, Sigurdur
2005-01-01
We are developing a specialized toolbox for non-stationary condition monitoring of large 2-stroke diesel engines based on acoustic emission measurements. The main contribution of this toolbox has so far been the utilization of adaptive linear models such as Principal and Independent Component Ana......, the inversion of those angular timing changes called “event alignment”, has allowed for condition monitoring across operation load settings, successfully enabling a single model to be used with realistic data under varying operational conditions-...
Energy Technology Data Exchange (ETDEWEB)
Todorov, N S [Low Temperature Department of the Institute of Solid State Physics of the Bulgarian Academy of Sciences, Sofia
1981-04-01
It is shown that the nonstationary Schroedinger equation does not satisfy a well-known adiabatical principle in thermodynamics. A ''renormalization procedure'' based on the possible existence of a time-irreversible basic evolution equation is proposed with the help of which one comes to agreement in a variety of specific cases of an adiabatic inclusion of a perturbing potential. The ideology of the present article rests essentially on the ideology of the preceding articles, in particular article I.
Energy Technology Data Exchange (ETDEWEB)
Todorov, N S
1981-04-01
It is shown that the nonstationary Schroedinger equation does not satisfy a well-known adiabatical principle in thermodynamics. A ''renormalization procedure'' based on the possible existence of a time-irreversible basic evolution equation is proposed with the help of which one comes to agreement in a variety of specific cases of an adiabatic inclusion of a perturbing potential. The ideology of the present article IV rests essentially on the ideology of the preceding articles, in particular article I.
Multifractals in Western Major STOCK Markets Historical Volatilities in Times of Financial Crisis
Lahmiri, Salim
In this paper, the generalized Hurst exponent is used to investigate multifractal properties of historical volatility (CHV) in stock market price and return series before, during and after 2008 financial crisis. Empirical results from NASDAQ, S&P500, TSE, CAC40, DAX, and FTSE stock market data show that there is strong evidence of multifractal patterns in HV of both price and return series. In addition, financial crisis deeply affected the behavior and degree of multifractality in volatility of Western financial markets at price and return levels.
Linssen, R.; Scheepers, P.L.H.; Grotenhuis, H.F. te; Schmeets, J.J.G.
2018-01-01
In this contribution, we investigate the extent to which the recent financial crisis has affected levels of political participation in general and more particularly within privileged and underprivileged societal groups in the Netherlands. We derive competing and complementary theoretical
A regional and nonstationary model for partial duration series of extreme rainfall
DEFF Research Database (Denmark)
Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan
2017-01-01
as the explanatory variables in the regional and temporal domain, respectively. Further analysis of partial duration series with nonstationary and regional thresholds shows that the mean exceedances also exhibit a significant variation in space and time for some rainfall durations, while the shape parameter is found...... of extreme rainfall. The framework is built on a partial duration series approach with a nonstationary, regional threshold value. The model is based on generalized linear regression solved by generalized estimation equations. It allows a spatial correlation between the stations in the network and accounts...... furthermore for variable observation periods at each station and in each year. Marginal regional and temporal regression models solved by generalized least squares are used to validate and discuss the results of the full spatiotemporal model. The model is applied on data from a large Danish rain gauge network...
A comparison of three approaches to non-stationary flood frequency analysis
Debele, S. E.; Strupczewski, W. G.; Bogdanowicz, E.
2017-08-01
Non-stationary flood frequency analysis (FFA) is applied to statistical analysis of seasonal flow maxima from Polish and Norwegian catchments. Three non-stationary estimation methods, namely, maximum likelihood (ML), two stage (WLS/TS) and GAMLSS (generalized additive model for location, scale and shape parameters), are compared in the context of capturing the effect of non-stationarity on the estimation of time-dependent moments and design quantiles. The use of a multimodel approach is recommended, to reduce the errors due to the model misspecification in the magnitude of quantiles. The results of calculations based on observed seasonal daily flow maxima and computer simulation experiments showed that GAMLSS gave the best results with respect to the relative bias and root mean square error in the estimates of trend in the standard deviation and the constant shape parameter, while WLS/TS provided better accuracy in the estimates of trend in the mean value. Within three compared methods the WLS/TS method is recommended to deal with non-stationarity in short time series. Some practical aspects of the GAMLSS package application are also presented. The detailed discussion of general issues related to consequences of climate change in the FFA is presented in the second part of the article entitled "Around and about an application of the GAMLSS package in non-stationary flood frequency analysis".
A Non-Stationary Approach for Estimating Future Hydroclimatic Extremes Using Monte-Carlo Simulation
Byun, K.; Hamlet, A. F.
2017-12-01
There is substantial evidence that observed hydrologic extremes (e.g. floods, extreme stormwater events, and low flows) are changing and that climate change will continue to alter the probability distributions of hydrologic extremes over time. These non-stationary risks imply that conventional approaches for designing hydrologic infrastructure (or making other climate-sensitive decisions) based on retrospective analysis and stationary statistics will become increasingly problematic through time. To develop a framework for assessing risks in a non-stationary environment our study develops a new approach using a super ensemble of simulated hydrologic extremes based on Monte Carlo (MC) methods. Specifically, using statistically downscaled future GCM projections from the CMIP5 archive (using the Hybrid Delta (HD) method), we extract daily precipitation (P) and temperature (T) at 1/16 degree resolution based on a group of moving 30-yr windows within a given design lifespan (e.g. 10, 25, 50-yr). Using these T and P scenarios we simulate daily streamflow using the Variable Infiltration Capacity (VIC) model for each year of the design lifespan and fit a Generalized Extreme Value (GEV) probability distribution to the simulated annual extremes. MC experiments are then used to construct a random series of 10,000 realizations of the design lifespan, estimating annual extremes using the estimated unique GEV parameters for each individual year of the design lifespan. Our preliminary results for two watersheds in Midwest show that there are considerable differences in the extreme values for a given percentile between conventional MC and non-stationary MC approach. Design standards based on our non-stationary approach are also directly dependent on the design lifespan of infrastructure, a sensitivity which is notably absent from conventional approaches based on retrospective analysis. The experimental approach can be applied to a wide range of hydroclimatic variables of interest.
On the non-stationary generalized Langevin equation
Meyer, Hugues; Voigtmann, Thomas; Schilling, Tanja
2017-12-01
In molecular dynamics simulations and single molecule experiments, observables are usually measured along dynamic trajectories and then averaged over an ensemble ("bundle") of trajectories. Under stationary conditions, the time-evolution of such averages is described by the generalized Langevin equation. By contrast, if the dynamics is not stationary, it is not a priori clear which form the equation of motion for an averaged observable has. We employ the formalism of time-dependent projection operator techniques to derive the equation of motion for a non-equilibrium trajectory-averaged observable as well as for its non-stationary auto-correlation function. The equation is similar in structure to the generalized Langevin equation but exhibits a time-dependent memory kernel as well as a fluctuating force that implicitly depends on the initial conditions of the process. We also derive a relation between this memory kernel and the autocorrelation function of the fluctuating force that has a structure similar to a fluctuation-dissipation relation. In addition, we show how the choice of the projection operator allows us to relate the Taylor expansion of the memory kernel to data that are accessible in MD simulations and experiments, thus allowing us to construct the equation of motion. As a numerical example, the procedure is applied to Brownian motion initialized in non-equilibrium conditions and is shown to be consistent with direct measurements from simulations.
Time and financial costs of programs for live trapping feral cats.
Nutter, Felicia B; Stoskopf, Michael K; Levine, Jay F
2004-11-01
To determine the time and financial costs of programs for live trapping feral cats and determine whether allowing cats to become acclimated to the traps improved trapping effectiveness. Prospective cohort study. 107 feral cats in 9 colonies. 15 traps were set at each colony for 5 consecutive nights, and 5 traps were then set per night until trapping was complete. In 4 colonies, traps were immediately baited and set; in the remaining 5 colonies, traps were left open and cats were fed in the traps for 3 days prior to the initiation of trapping. Costs for bait and labor were calculated, and trapping effort and efficiency were assessed. Mean +/- SD overall trapping effort (ie, number of trap-nights until at least 90% of the cats in the colony had been captured or until no more than 1 cat remained untrapped) was 8.9 +/- 3.9 trap-nights per cat captured. Mean overall trapping efficiency (ie, percentage of cats captured per colony) was 98.0 +/- 4.0%. There were no significant differences in trapping effort or efficiency between colonies that were provided an acclimation period and colonies that were not. Overall trapping costs were significantly higher for colonies provided an acclimation period. Results suggest that these live-trapping protocols were effective. Feeding cats their regular diets in the traps for 3 days prior to the initiation of trapping did not have a significant effect on trapping effort or efficiency in the present study but was associated with significant increases in trapping costs.
Lexa, Frank James; Berlin, Jonathan W
2005-03-01
In this article, the authors cover tools for financial modeling. Commonly used time lines and cash flow diagrams are discussed. Commonly used but limited terms such as payback and breakeven are introduced. The important topics of the time value of money and discount rates are introduced to lay the foundation for their use in modeling and in more advanced metrics such as the internal rate of return. Finally, the authors broach the more sophisticated topic of net present value.
THE IMPORTANCE OF THE SCENARIOS METHODOLOGY FOR FINANCIAL INSTITUTIONS DURING TIMES OF CRISIS
Directory of Open Access Journals (Sweden)
Paulo Roberto Correa Leão
2010-11-01
Full Text Available Recently, the need to apply strategic planning methodologies in business has risen, since corporations are part of a globalized world in which technological change and economic dynamism are evolving at a faster pace. Thus, firms must perform not only efficiently but also effectively in adapting to changes as they occur in the political, economic, technological, legal and environmental dimensions. This dictates the need for new strategic organizational positioning. The potential usefulness of the scenarios methodology was investigated for a sample of financial institutions with assets in the Brazilian market, based on management reports and in accordance with strategic dimensions needed to cope with crises. Therefore, we propose a new methodology for the qualitative analysis of official management reports, which indicates a perception of scenario building within organizations. The results suggest a positive relationship between the quality of the process of generating scenarios and the financial results of the banking institution. Key-words: Scenarios. Financial institutions. Crisis.
Gray, A. B.
2017-12-01
Watersheds with sufficient monitoring data have been predominantly found to display nonstationary suspended sediment dynamics, whereby the relationship between suspended sediment concentration and discharge changes over time. Despite the importance of suspended sediment as a keystone of geophysical and biochemical processes, and as a primary mediator of water quality, stationary behavior remains largely assumed in the context of these applications. This study presents an investigation into the time dependent behavior of small mountainous rivers draining the coastal ranges of the western continental US over interannual to interdecadal time scales. Of the 250+ small coastal (drainage area systems. Temporal patterns of non-stationary behavior provided some evidence for spatial coherence, which may be related to synoptic hydro-metrological patterns and regional scale changes in land use patterns. However, the results also highlight the complex, integrative nature of watershed scale fluvial suspended sediment dynamics. This underscores the need for in-depth, forensic approaches for initial processes identification, which require long term, high resolution monitoring efforts in order to adequately inform management. The societal implications of nonstationary sediment dynamics and their controls were further explored through the case of California, USA, where over 150 impairment listings have resulted in more than 50 sediment TMDLs, only 3 of which are flux based - none of which account for non-stationary behavior.
Poplová, Michaela; Sovka, Pavel; Cifra, Michal
2017-01-01
Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.
Nonstationary influence of El Niño on the synchronous dengue epidemics in Thailand.
Directory of Open Access Journals (Sweden)
Bernard Cazelles
2005-04-01
Full Text Available BACKGROUND: Several factors, including environmental and climatic factors, influence the transmission of vector-borne diseases. Nevertheless, the identification and relative importance of climatic factors for vector-borne diseases remain controversial. Dengue is the world's most important viral vector-borne disease, and the controversy about climatic effects also applies in this case. Here we address the role of climate variability in shaping the interannual pattern of dengue epidemics. METHODS AND FINDINGS: We have analysed monthly data for Thailand from 1983 to 1997 using wavelet approaches that can describe nonstationary phenomena and that also allow the quantification of nonstationary associations between time series. We report a strong association between monthly dengue incidence in Thailand and the dynamics of El Niño for the 2-3-y periodic mode. This association is nonstationary, seen only from 1986 to 1992, and appears to have a major influence on the synchrony of dengue epidemics in Thailand. CONCLUSION: The underlying mechanism for the synchronisation of dengue epidemics may resemble that of a pacemaker, in which intrinsic disease dynamics interact with climate variations driven by El Niño to propagate travelling waves of infection. When association with El Niño is strong in the 2-3-y periodic mode, one observes high synchrony of dengue epidemics over Thailand. When this association is absent, the seasonal dynamics become dominant and the synchrony initiated in Bangkok collapses.
Overcoming the hard law/soft law dichotomy in times of (financial crises
Directory of Open Access Journals (Sweden)
Rolf H. Weber
2012-03-01
Full Text Available Traditional legal doctrine calls for hard law to regulate markets. Nevertheless, in financial markets, soft law has a long tradition, not at least due to the lack of multilateral agreements in this field. On the one hand, the recent financial crisis has shown that soft law does not suffice to avoid detrimental developments; on the other hand, a straight call for hard law would not be able to manage the recognized regulatory weaknesses. Therefore, emphasis should be put on the possibilities of combining hard law and soft law; specific areas allowing realizing such kind of “combination” are organizational issues, transparency requirements, and dispute settlement mechanisms.
J. Chen (Jinghui); M. Kobayashi (Masahito); M.J. McAleer (Michael)
2016-01-01
textabstractThe paper considers the problem as to whether financial returns have a common volatility process in the framework of stochastic volatility models that were suggested by Harvey et al. (1994). We propose a stochastic volatility version of the ARCH test proposed by Engle and Susmel (1993),
Time to Pay Up: Analyzing the Motivational Potential of Financial Awards in a TIF Program
Rice, Jennifer King; Malen, Betty; Jackson, Cara; Hoyer, Kathleen Mulvaney
2015-01-01
The effectiveness of educator incentive programs rests on the assumption that the potential rewards for participants will motivate them to behave in certain ways (e.g., choose certain jobs, expend greater effort, engage in capacity-building professional development). Some researchers have examined the impact of financial incentives on teacher…
Dual Enrollment in Times of Financial Constraint: A Community College Perspective
Hockley, Lori White
2013-01-01
Community college leaders today must contend with a formidable challenge: dwindling state funding and declining resources. Increased enrollments without proportional increases in state and local financial support have placed colleges in the unenviable position of needing to do more with less--or in some cases, simply do less. Despite the…
Financial Times näeb abiprogrammides ülemaailmset ohtu / Mikk Salu
Salu, Mikk, 1975-
2009-01-01
Financial Timesi kolumnisti Martin Wolfe'i hinnangul sünniks katastroof siis, kui USA valitsus kaks aastat küll pingutaks ja stimuleeriks majandust, kuid, tööpuudus oleks endiselt suur ja defitsiit kasvaks. Majandusprofessor Willem Buiter arvab, et lähima kahe aasta jooksul kukuvad maailmas kokku dollaris hinnatud varad
Teaching Business Ethics after the Financial Meltdown: Is It Time for Ethics with a Sermon?
Cavaliere, Frank J.; Mulvaney, Toni P.; Swerdlow, Marleen R.
2010-01-01
Our country is faced with a financial crisis of mammoth proportions: a crisis rooted in ethics, or rather, the lack of ethics. Critics are increasingly complaining that business schools focus too much teaching effort on maximizing shareholder value, with only a limited understanding of ethical and social aspects of business leadership. Business…
Lin, Weilu; Wang, Zejian; Huang, Mingzhi; Zhuang, Yingping; Zhang, Siliang
2018-06-01
The isotopically non-stationary 13C labelling experiments, as an emerging experimental technique, can estimate the intracellular fluxes of the cell culture under an isotopic transient period. However, to the best of our knowledge, the issue of the structural identifiability analysis of non-stationary isotope experiments is not well addressed in the literature. In this work, the local structural identifiability analysis for non-stationary cumomer balance equations is conducted based on the Taylor series approach. The numerical rank of the Jacobian matrices of the finite extended time derivatives of the measured fractions with respect to the free parameters is taken as the criterion. It turns out that only one single time point is necessary to achieve the structural identifiability analysis of the cascaded linear dynamic system of non-stationary isotope experiments. The equivalence between the local structural identifiability of the cascaded linear dynamic systems and the local optimum condition of the nonlinear least squares problem is elucidated in the work. Optimal measurements sets can then be determined for the metabolic network. Two simulated metabolic networks are adopted to demonstrate the utility of the proposed method. Copyright © 2018 Elsevier Inc. All rights reserved.
Damping Identification of Bridges Under Nonstationary Ambient Vibration
Directory of Open Access Journals (Sweden)
Sunjoong Kim
2017-12-01
Full Text Available This research focuses on identifying the damping ratio of bridges using nonstationary ambient vibration data. The damping ratios of bridges in service have generally been identified using operational modal analysis (OMA based on a stationary white noise assumption for input signals. However, most bridges are generally subjected to nonstationary excitations while in service, and this violation of the basic assumption can lead to uncertainties in damping identification. To deal with nonstationarity, an amplitude-modulating function was calculated from measured responses to eliminate global trends caused by nonstationary input. A natural excitation technique (NExT-eigensystem realization algorithm (ERA was applied to estimate the damping ratio for a stationarized process. To improve the accuracy of OMA-based damping estimates, a comparative analysis was performed between an extracted stationary process and nonstationary data to assess the effect of eliminating nonstationarity. The mean value and standard deviation of the damping ratio for the first vertical mode decreased after signal stationarization. Keywords: Damping, Operational modal analysis, Traffic-induced vibration, Nonstationary, Signal stationarization, Amplitude-modulating, Bridge, Cable-stayed, Suspension
Time-varying causal network of the Korean financial system based on firm-specific risk premiums
Song, Jae Wook; Ko, Bonggyun; Cho, Poongjin; Chang, Woojin
2016-09-01
The aim of this paper is to investigate the Korean financial system based on time-varying causal network. We discover many stylized facts by utilizing the firm-specific risk premiums for measuring the causality direction from a firm to firm. At first, we discover that the interconnectedness of causal network is affected by the outbreak of financial events; the co-movement of firm-specific risk premium is strengthened after each positive event, and vice versa. Secondly, we find that the major sector of the Korean financial system is the Depositories, and the financial reform in June-2011 achieves its purpose by weakening the power of risk-spillovers of Broker-Dealers. Thirdly, we identify that the causal network is a small-world network with scale-free topology where the power-law exponents of out-Degree and negative event are more significant than those of in-Degree and positive event. Lastly, we discuss that the current aspects of causal network are closely related to the long-term future scenario of the KOSPI Composite index where the direction and stability are significantly affected by the power of risk-spillovers and the power-law exponents of degree distributions, respectively.
Distributed Nonstationary Heat Model of Two-Channel Solar Air Heater
International Nuclear Information System (INIS)
Klychev, Sh. I.; Bakhramov, S. A.; Ismanzhanov, A. I.; Tashiev, N.N.
2011-01-01
An algorithm for a distributed nonstationary heat model of a solar air heater (SAH) with two operating channels is presented. The model makes it possible to determine how the coolant temperature changes with time along the solar air heater channel by considering its main thermal and ambient parameters, as well as variations in efficiency. Examples of calculations are presented. It is shown that the time within which the mean-day efficiency of the solar air heater becomes stable is significantly higher than the time within which the coolant temperature reaches stable values. The model can be used for investigation of the performances of solar water-heating collectors. (authors)
ENSO's non-stationary and non-Gaussian character: the role of climate shifts
Boucharel, J.; Dewitte, B.; Garel, B.; Du Penhoat, Y.
2009-07-01
El Niño Southern Oscillation (ENSO) is the dominant mode of climate variability in the Pacific, having socio-economic impacts on surrounding regions. ENSO exhibits significant modulation on decadal to inter-decadal time scales which is related to changes in its characteristics (onset, amplitude, frequency, propagation, and predictability). Some of these characteristics tend to be overlooked in ENSO studies, such as its asymmetry (the number and amplitude of warm and cold events are not equal) and the deviation of its statistics from those of the Gaussian distribution. These properties could be related to the ability of the current generation of coupled models to predict ENSO and its modulation. Here, ENSO's non-Gaussian nature and asymmetry are diagnosed from in situ data and a variety of models (from intermediate complexity models to full-physics coupled general circulation models (CGCMs)) using robust statistical tools initially designed for financial mathematics studies. In particular α-stable laws are used as theoretical background material to measure (and quantify) the non-Gaussian character of ENSO time series and to estimate the skill of ``naïve'' statistical models in producing deviation from Gaussian laws and asymmetry. The former are based on non-stationary processes dominated by abrupt changes in mean state and empirical variance. It is shown that the α-stable character of ENSO may result from the presence of climate shifts in the time series. Also, cool (warm) periods are associated with ENSO statistics having a stronger (weaker) tendency towards Gaussianity and lower (greater) asymmetry. This supports the hypothesis of ENSO being rectified by changes in mean state through nonlinear processes. The relationship between changes in mean state and nonlinearity (skewness) is further investigated both in the Zebiak and Cane (1987)'s model and the models of the Intergovernmental Panel for Climate Change (IPCC). Whereas there is a clear relationship in all
Matérn-based nonstationary cross-covariance models for global processes
Jun, Mikyoung
2014-01-01
-covariance models, based on the Matérn covariance model class, that are suitable for describing prominent nonstationary characteristics of the global processes. In particular, we seek nonstationary versions of Matérn covariance models whose smoothness parameters
Non-Stationary Internal Tides Observed with Satellite Altimetry
Ray, Richard D.; Zaron, E. D.
2011-01-01
Temporal variability of the internal tide is inferred from a 17-year combined record of Topex/Poseidon and Jason satellite altimeters. A global sampling of along-track sea-surface height wavenumber spectra finds that non-stationary variance is generally 25% or less of the average variance at wavenumbers characteristic of mode-l tidal internal waves. With some exceptions the non-stationary variance does not exceed 0.25 sq cm. The mode-2 signal, where detectable, contains a larger fraction of non-stationary variance, typically 50% or more. Temporal subsetting of the data reveals interannual variability barely significant compared with tidal estimation error from 3-year records. Comparison of summer vs. winter conditions shows only one region of noteworthy seasonal changes, the northern South China Sea. Implications for the anticipated SWOT altimeter mission are briefly discussed.
Directory of Open Access Journals (Sweden)
X. X. Cheng
2017-01-01
Full Text Available Wind effects on structures obtained by field measurements are often found to be nonstationary, but related researches shared by the wind-engineering community are still limited. In this paper, empirical mode decomposition (EMD is applied to the nonstationary wind pressure time-history samples measured on an actual 167-meter high large cooling tower. It is found that the residue and some intrinsic mode functions (IMFs of low frequencies produced by EMD are responsible for the samples’ nonstationarity. Replacing the residue by the constant mean and subtracting the IMFs of low frequencies can help the nonstationary samples become stationary ones. A further step is taken to compare the loading characteristics extracted from the original nonstationary samples with those extracted from the processed stationary samples. Results indicate that nonstationarity effects on wind loads are notable in most cases. The passive wind tunnel simulation technique based on the assumption of stationarity is also examined, and it is found that the technique is basically conservative for use.
Financial development and energy consumption nexus in Malaysia: A multivariate time series analysis
Islam, Faridul; Shahbaz, Muhammad; Alam, Mahmudul
2011-01-01
Despite a bourgeoning literature on the existence of a long-run relationship between energy consumption and economic growth, the findings have failed to establish clearly the direction of causation. A growing economy needs more energy, which is exacerbated by growing population. Evidence suggests that financial development can reduce overall energy consumption by achieving energy efficiency. Economic growth and energy consumption in Malaysia have been rising in tandem over the past several ye...
Directory of Open Access Journals (Sweden)
Sung Soo Kim
2016-02-01
Full Text Available We consider a discrete-time dependent Sparre Andersen risk model which incorporates multiple threshold levels characterizing an insurer’s minimal capital requirement, dividend paying situations, and external financial activities. We focus on the development of a recursive computational procedure to calculate the finite-time ruin probabilities and expected total discounted dividends paid prior to ruin associated with this model. We investigate several numerical examples and make some observations concerning the impact our threshold levels have on the finite-time ruin probabilities and expected total discounted dividends paid prior to ruin.
Lopez Bernal, James A; Gasparrini, Antonio; Artundo, Carlos M; McKee, Martin
2013-10-01
The current financial crisis is having a major impact on European economies, especially that of Spain. Past evidence suggests that adverse macro-economic conditions exacerbate mental illness, but evidence from the current crisis is limited. This study analyses the association between the financial crisis and suicide rates in Spain. An interrupted time-series analysis of national suicides data between 2005 and 2010 was used to establish whether there has been any deviation in the underlying trend in suicide rates associated with the financial crisis. Segmented regression with a seasonally adjusted quasi-Poisson model was used for the analysis. Stratified analyses were performed to establish whether the effect of the crisis on suicides varied by region, sex and age group. The mean monthly suicide rate in Spain during the study period was 0.61 per 100 000 with an underlying trend of a 0.3% decrease per month. We found an 8.0% increase in the suicide rate above this underlying trend since the financial crisis (95% CI: 1.009-1.156; P = 0.03); this was robust to sensitivity analysis. A control analysis showed no change in deaths from accidental falls associated with the crisis. Stratified analyses suggested that the association between the crisis and suicide rates is greatest in the Mediterranean and Northern areas, in males and amongst those of working age. The financial crisis in Spain has been associated with a relative increase in suicides. Males and those of working age may be at particular risk of suicide associated with the crisis and may benefit from targeted interventions.
International Nuclear Information System (INIS)
Nicolaides, C.A.; Mercouris, T.
1996-01-01
The detailed time dependence of the decay of a three-electron autoionizing state close to threshold has been obtained ab initio by solving the time-dependent Schrodinger equation (TDSE). The theory allows the definition and computation of energy-dependent matrix elements in terms of the appropriate N-electron wavefunctions, representing the localized initial state, Ψ O , the stationary scattering states of the continuous spectrum, U( e psilon ) , and the localized excited states, Ψ n , of the effective Hamiltonian QHQ, where Q ''ident to'' |Ψ O > O |. The time-dependent wavefunction is expanded over these states and the resulting coupled equations with time-dependent coefficients (in the thousands) are solved to all orders by a Taylor series expansion technique. The robustness of the method was verified by using a model interaction in analytic form and comparing the results from two different methods for integrating the TDSE (appendix B). For the physically relevant application, the chosen state was the He - 1s2p 24 P shape resonance, about which very accurate theoretical and experimental relevant information exists. Calculations using accurate wavefunctions and an energy grid of 20.000 points in the range 0.0-21.77 eV show that the effective interaction depends on energy in a state-specific manner, thereby leading to state-specific characteristics of non-exponential decay over about 6 x 10 4 au of time, from which a width of Γ = 5.2 meV and a lifetime of 1.26 x 10 -13 s is deduced. The results suggest that either in this state or in other autoionizing states close to threshold, NED may have sufficient presence to make the violation of the law of exponential decay observable. (Author)
The World Economy in the Times of Financial Crisis and its Impact on European Energy Policy
Peter Baláž; Juraj Bayer
2015-01-01
Since 2007, globalization of the world economy has led to the expansion of the financial crisis. It affects the long-term international negative positions of EU members. They reacted to the new situation by carrying out structural reforms and by support of new adaptation programs. An important element of this process was the preparing of the convergence of the national energy policies in the framework of the Europe 20-20-20 program, which should remain one of the determining elements of their...
The World Economy in the Times of Financial Crisis and its Impact on European Energy Policy
Directory of Open Access Journals (Sweden)
Peter Baláž
2015-03-01
Full Text Available Since 2007, globalization of the world economy has led to the expansion of the financial crisis. It affects the long-term international negative positions of EU members. They reacted to the new situation by carrying out structural reforms and by support of new adaptation programs. An important element of this process was the preparing of the convergence of the national energy policies in the framework of the Europe 20-20-20 program, which should remain one of the determining elements of their success in support of the international competitiveness of the EU.
DEFF Research Database (Denmark)
Kristensen, Erling Lundager; Østergaard, Søren; Krogh, Mogens Agerbo
2008-01-01
The manager of a dairy herd and the affiliated consultants constantly need to judge whether financial performance of the production system is satisfactory and whether financial performance relates to real (systematic) effects of changes in management. This is no easy task because the dairy herd...... is a very complex system. Thus, it is difficult to obtain empirical data that allows a valid estimation of the random (within-herd) variation in financial performance corrected for management changes. Thus, simulation seems to be the only option. This study suggests that much caution must be recommended...
Financialization and financial profit
Directory of Open Access Journals (Sweden)
Arturo Guillén
2014-09-01
Full Text Available This article starts from the critical review of the concept of financial capital. I consider it is necessary not to confuse this category with of financialization, which has acquired a certificate of naturalization from the rise of neoliberalism. Although financial monopoly-financial capital is the hegemonic segment of the bourgeoisie in the major capitalist countries, their dominance does not imply, a fortiori, financialization of economic activity, since it depends of the conditions of the process reproduction of capital. The emergence of joint stock companies modified the formation of the average rate of profit. The "promoter profit" becomes one of the main forms of income of monopoly-financial capital. It is postulated that financial profit is a kind of "extraordinary surplus-value" which is appropriated by monopoly-financial capital by means of the monopolistic control it exerts on the issue and circulation of fictitious capital.
Assessing the extent of non-stationary biases in GCMs
Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish
2017-06-01
General circulation models (GCMs) are the main tools for estimating changes in the climate for the future. The imperfect representation of climate models introduces biases in the simulations that need to be corrected prior to their use for impact assessments. Bias correction methods generally assume that the bias calculated over the historical period does not change and can be applied to the future. This study investigates this assumption by considering the extent and nature of bias non-stationarity using 20th century precipitation and temperature simulations from six CMIP5 GCMs across Australia. Four statistics (mean, standard deviation, 10th and 90th quantiles) in monthly and seasonal biases are obtained for three different time window lengths (10, 25 and 33 years) to examine the properties of bias over time. This approach is repeated for two different phases of the Interdecadal Pacific Oscillation (IPO), which is known to have strong influences on the Australian climate. It is found that bias non-stationarity at decadal timescales is indeed an issue over some of Australia for some GCMs. When considering interdecadal variability there are significant difference in the bias between positive and negative phases of the IPO. Regional analyses confirmed these findings with the largest differences seen on the east coast of Australia, where IPO impacts tend to be the strongest. The nature of the bias non-stationarity found in this study suggests that it will be difficult to modify existing bias correction approaches to account for non-stationary biases. A more practical approach for impact assessments that use bias correction maybe to use a selection of GCMs where the assumption of bias non-stationarity holds.
Designing and operating infrastructure for nonstationary flood risk management
Doss-Gollin, J.; Farnham, D. J.; Lall, U.
2017-12-01
Climate exhibits organized low-frequency and regime-like variability at multiple time scales, causing the risk associated with climate extremes such as floods and droughts to vary in time. Despite broad recognition of this nonstationarity, there has been little theoretical development of ideas for the design and operation of infrastructure considering the regime structure of such changes and their potential predictability. We use paleo streamflow reconstructions to illustrate an approach to the design and operation of infrastructure to address nonstationary flood and drought risk. Specifically, we consider the tradeoff between flood control and conservation storage, and develop design and operation principles for allocating these storage volumes considering both a m-year project planning period and a n-year historical sampling record. As n increases, the potential uncertainty in probabilistic estimates of the return periods associated with the T-year extreme event decreases. As the duration m of the future operation period decreases, the uncertainty associated with the occurrence of the T-year event also increases. Finally, given the quasi-periodic nature of the system it may be possible to offer probabilistic predictions of the conditions in the m-year future period, especially if m is small. In the context of such predictions, one can consider that a m-year prediction may have lower bias, but higher variance, than would be associated with using a stationary estimate from the preceding n years. This bias-variance trade-off, and the potential for considering risk management for multiple values of m, provides an interesting system design challenge. We use wavelet-based simulation models in a Bayesian framework to estimate these biases and uncertainty distributions and devise a risk-optimized decision rule for the allocation of flood and conservation storage. The associated theoretical development also provides a methodology for the sizing of storage for new
Numerical Clifford Analysis for the Non-stationary Schroedinger Equation
International Nuclear Information System (INIS)
Faustino, N.; Vieira, N.
2007-01-01
We construct a discrete fundamental solution for the parabolic Dirac operator which factorizes the non-stationary Schroedinger operator. With such fundamental solution we construct a discrete counterpart for the Teodorescu and Cauchy-Bitsadze operators and the Bergman projectors. We finalize this paper with convergence results regarding the operators and a concrete numerical example
Nonstationary Narrow-Band Response and First-Passage Probability
DEFF Research Database (Denmark)
Krenk, Steen
1979-01-01
The notion of a nonstationary narrow-band stochastic process is introduced without reference to a frequency spectrum, and the joint distribution function of two consecutive maxima is approximated by use of an envelope. Based on these definitions the first passage problem is treated as a Markov po...
Elastic-plastic response characteristics during frequency nonstationary waves
International Nuclear Information System (INIS)
Miyama, T.; Kanda, J.; Iwasaki, R.; Sunohara, H.
1987-01-01
The purpose of this paper is to study fundamental effects of the frequency nonstationarity on the inelastic responses. First, the inelastic response characteristics are examined by applying stationary waves. Then simple representation of nonstationary characteristics is considered to general nonstationary input. The effects for frequency nonstationary response are summarized for inelastic systems. The inelastic response characteristics under white noise and simple frequency nonstationary wave were investigated, and conclusions can be summarized as follows. 1) The maximum response values for both BL model and OO model corresponds fairly well with those estimated from the energy constant law, even when R is small. For the OO model, the maximum displacement response forms a unique curve except for very small R. 2) The plastic deformation for the BL model is affected by wide frequency components, as R decreases. The plastic deformation for the OO model can be determined from the last stiffness. 3). The inelastic response of the BL model is considerably affected by the frequency nonstationarity of the input motion, while the response is less affected by the nonstationarity for OO model. (orig./HP)
A bootstrap invariance principle for highly nonstationary long memory processes
Kapetanios, George
2004-01-01
This paper presents an invariance principle for highly nonstationary long memory processes, defined as processes with long memory parameter lying in (1, 1.5). This principle provides the tools for showing asymptotic validity of the bootstrap in the context of such processes.
Non-Stationary Dependence Structures for Spatial Extremes
Huser, Raphaë l; Genton, Marc G.
2016-01-01
been developed, and fitted to various types of data. However, a recurrent problem is the modeling of non-stationarity. In this paper, we develop non-stationary max-stable dependence structures in which covariates can be easily incorporated. Inference
Dynamic Memory Model for Non-Stationary Optimization
DEFF Research Database (Denmark)
Bendtsen, Claus Nørgaard; Krink, Thiemo
2002-01-01
Real-world problems are often nonstationary and can cause cyclic, repetitive patterns in the search landscape. For this class of problems, we introduce a new GA with dynamic explicit memory, which showed superior performance compared to a classic GA and a previously introduced memory-based GA for...
Characterizing and modelling cyclic behaviour in non-stationary ...
Indian Academy of Sciences (India)
journal of. September 2008 physics pp. 459–485. Characterizing and ... analysis on two different financial time series, in order to find out the similarities ...... [6] P C Biswal, B Kamaiah and P K Panigrahi, J. Quantitative Economics 2, 133 (2004).
Valenza, Gaetano; Faes, Luca; Citi, Luca; Orini, Michele; Barbieri, Riccardo
2018-05-01
Measures of transfer entropy (TE) quantify the direction and strength of coupling between two complex systems. Standard approaches assume stationarity of the observations, and therefore are unable to track time-varying changes in nonlinear information transfer with high temporal resolution. In this study, we aim to define and validate novel instantaneous measures of TE to provide an improved assessment of complex nonstationary cardiorespiratory interactions. We here propose a novel instantaneous point-process TE (ipTE) and validate its assessment as applied to cardiovascular and cardiorespiratory dynamics. In particular, heartbeat and respiratory dynamics are characterized through discrete time series, and modeled with probability density functions predicting the time of the next physiological event as a function of the past history. Likewise, nonstationary interactions between heartbeat and blood pressure dynamics are characterized as well. Furthermore, we propose a new measure of information transfer, the instantaneous point-process information transfer (ipInfTr), which is directly derived from point-process-based definitions of the Kolmogorov-Smirnov distance. Analysis on synthetic data, as well as on experimental data gathered from healthy subjects undergoing postural changes confirms that ipTE, as well as ipInfTr measures are able to dynamically track changes in physiological systems coupling. This novel approach opens new avenues in the study of hidden, transient, nonstationary physiological states involving multivariate autonomic dynamics in cardiovascular health and disease. The proposed method can also be tailored for the study of complex multisystem physiology (e.g., brain-heart or, more in general, brain-body interactions).
Identification of Non-Stationary Magnetic Field Sources Using the Matching Pursuit Method
Directory of Open Access Journals (Sweden)
Beata Palczynska
2017-05-01
Full Text Available The measurements of electromagnetic field emissions, performed on board a vessel have showed that, in this specific environment, a high level of non-stationary magnetic fields (MFs is observed. The adaptive time-frequency method can be used successfully to analyze this type of measured signal. It allows one to specify the time interval in which the individual frequency components of the signal occur. In this paper, the method of identification of non-stationary MF sources based on the matching pursuit (MP algorithm is presented. It consists of the decomposition of an examined time-waveform into the linear expansion of chirplet atoms and the analysis of the matrix of their parameters. The main feature of the proposed method is the modification of the chirplet’s matrix in a way that atoms, whose normalized energies are lower than a certain threshold, will be rejected. On the time-frequency planes of the spectrograms, obtained separately for each remaining chirlpet, it can clearly identify the time-frequency structures appearing in the examined signal. The choice of a threshold defines the computing speed and precision of the performed analysis. The method was implemented in the virtual application and used for processing real data, obtained from measurements of time-vary MF emissions onboard a ship.
Rethinking Social Work in times of economic and financial crisis in Portugal
Directory of Open Access Journals (Sweden)
Maria-Irene Carvalho
2017-06-01
Full Text Available The purpose of this paper is to contextualize the social policy transformations in social services and health care system in the context of the economic and financial crisis and following intervention of the international monetary fund, the World Bank and the European Central Bank (Troika in Portugal, over the past four years. We analyze the social emergency program, which replaced the national plan for social inclusion, and the implementation of the national integrated network for long term care. Based on the evidence of the results we reflect on these transformations in Social Work, highlighting the negative aspects and the challenges for this profession. To achieve these aims we analyzed documents, statistical data and research on this subject. In this context of scarcity and emergency interventions, Social Work is challenged to rethink itself as a sociopolitical profession, taking into account the temporality of the intervention, the allocation of resources and the training of professionals.
Global health and national borders: the ethics of foreign aid in a time of financial crisis.
Johri, Mira; Chung, Ryoa; Dawson, Angus; Schrecker, Ted
2012-06-28
The governments and citizens of the developed nations are increasingly called upon to contribute financially to health initiatives outside their borders. Although international development assistance for health has grown rapidly over the last two decades, austerity measures related to the 2008 and 2011 global financial crises may impact negatively on aid expenditures. The competition between national priorities and foreign aid commitments raises important ethical questions for donor nations. This paper aims to foster individual reflection and public debate on donor responsibilities for global health. We undertook a critical review of contemporary accounts of justice. We selected theories that: (i) articulate important and widely held moral intuitions; (ii) have had extensive impact on debates about global justice; (iii) represent diverse approaches to moral reasoning; and (iv) present distinct stances on the normative importance of national borders. Due to space limitations we limit the discussion to four frameworks. Consequentialist, relational, human rights, and social contract approaches were considered. Responsibilities to provide international assistance were seen as significant by all four theories and place limits on the scope of acceptable national autonomy. Among the range of potential aid foci, interventions for health enjoyed consistent prominence. The four theories concur that there are important ethical responsibilities to support initiatives to improve the health of the worst off worldwide, but offer different rationales for intervention and suggest different implicit limits on responsibilities. Despite significant theoretical disagreements, four influential accounts of justice offer important reasons to support many current initiatives to promote global health. Ethical argumentation can complement pragmatic reasons to support global health interventions and provide an important foundation to strengthen collective action.
Global health and national borders: the ethics of foreign aid in a time of financial crisis
Directory of Open Access Journals (Sweden)
Johri Mira
2012-06-01
Full Text Available Abstract Background The governments and citizens of the developed nations are increasingly called upon to contribute financially to health initiatives outside their borders. Although international development assistance for health has grown rapidly over the last two decades, austerity measures related to the 2008 and 2011 global financial crises may impact negatively on aid expenditures. The competition between national priorities and foreign aid commitments raises important ethical questions for donor nations. This paper aims to foster individual reflection and public debate on donor responsibilities for global health. Methods We undertook a critical review of contemporary accounts of justice. We selected theories that: (i articulate important and widely held moral intuitions; (ii have had extensive impact on debates about global justice; (iii represent diverse approaches to moral reasoning; and (iv present distinct stances on the normative importance of national borders. Due to space limitations we limit the discussion to four frameworks. Results Consequentialist, relational, human rights, and social contract approaches were considered. Responsibilities to provide international assistance were seen as significant by all four theories and place limits on the scope of acceptable national autonomy. Among the range of potential aid foci, interventions for health enjoyed consistent prominence. The four theories concur that there are important ethical responsibilities to support initiatives to improve the health of the worst off worldwide, but offer different rationales for intervention and suggest different implicit limits on responsibilities. Conclusions Despite significant theoretical disagreements, four influential accounts of justice offer important reasons to support many current initiatives to promote global health. Ethical argumentation can complement pragmatic reasons to support global health interventions and provide an important
Non-stationary ionization in the low ionosphere by gravitational wave action
International Nuclear Information System (INIS)
Nikitin, M.A.; Kashchenko, N.M.
1977-01-01
Non-stationary effects in the lower ionosphere caused by gravitation waves are analyzed. Time dependences are obtained for extremum electron concentrations, which describe the dynamics of heterogeneous layer formation from the initially homogeneous distribution under the effect of gravitation waves. Diffusion of plasma and its complex composition are not taken into account. The problem is solved for two particular cases of low and high frequency gravitation waves impact on the ionosphere. Only in the former case electron concentration in the lower ionosphere deviates considerably from the equilibrium
Faster Simulation Methods for the Non-Stationary Random Vibrations of Non-Linear MDOF Systems
DEFF Research Database (Denmark)
Askar, A.; Köylüoglu, H. U.; Nielsen, Søren R. K.
subject to nonstationary Gaussian white noise excitation, as an alternative to conventional direct simulation methods. These alternative simulation procedures rely on an assumption of local Gaussianity during each time step. This assumption is tantamount to various linearizations of the equations....... Such a treatment offers higher rates of convergence, faster speed and higher accuracy. These procedures are compared to the direct Monte Carlo simulation procedure, which uses a fourth order Runge-Kutta scheme with the white noise process approximated by a broad band Ruiz-Penzien broken line process...
Faster Simulation Methods for the Nonstationary Random Vibrations of Non-linear MDOF Systems
DEFF Research Database (Denmark)
Askar, A.; Köylüo, U.; Nielsen, Søren R.K.
1996-01-01
subject to nonstationary Gaussian white noise excitation, as an alternative to conventional direct simulation methods. These alternative simulation procedures rely on an assumption of local Gaussianity during each time step. This assumption is tantamount to various linearizations of the equations....... Such a treatment offers higher rates of convergence, faster speed and higher accuracy. These procedures are compared to the direct Monte Carlo simulation procedure, which uses a fourth order Runge-Kutta scheme with the white noise process approximated by a broad band Ruiz-Penzien broken line process...
Essays on forecasting stationary and nonstationary economic time series
Bachmeier, Lance Joseph
This dissertation consists of three essays. Chapter II considers the question of whether M2 growth can be used to forecast inflation at horizons of up to ten years. A vector error correction (VEC) model serves as our benchmark model. We find that M2 growth does have marginal predictive content for inflation at horizons of more than two years, but only when allowing for cointegration and when the cointegrating rank and vector are specified a priori. When estimating the cointegration vector or failing to impose cointegration, there is no longer evidence of causality running from M2 growth to inflation at any forecast horizon. Finally, we present evidence that M2 needs to be redefined, as forecasts of the VEC model using data on M2 observed after 1993 are worse than the forecasts of an autoregressive model of inflation. Chapter III reconsiders the evidence for a "rockets and feathers" effect in gasoline markets. We estimate an error correction model of gasoline prices using daily data for the period 1985--1998 and fail to find any evidence of asymmetry. We show that previous work suffered from two problems. First, nonstationarity in some of the regressors was ignored, leading to invalid inference. Second, the weekly data used in previous work leads to a temporal aggregation problem, and thus biased estimates of impulse response functions. Chapter IV tests for a forecasting relationship between the volume of litigation and macroeconomic variables. We analyze annual data for the period 1960--2000 on the number of cases filed, real GDP, real consumption expenditures, inflation, unemployment, and interest rates. Bivariate Granger causality tests show that several of the macroeconomic variables can be used to forecast the volume of litigation, but show no evidence that the volume of litigation can be used to forecast any of the macroeconomic variables. The analysis is then extended to bivariate and multivariate regression models, and we find similar evidence to that of the Granger causality tests. We conclude that agents desiring a forecast of the volume of litigation should consider the state of the economy.
Signatures of Depression in Non-Stationary Biometric Time Series
Directory of Open Access Journals (Sweden)
Milka Culic
2009-01-01
Full Text Available This paper is based on a discussion that was held during a special session on models of mental disorders, at the NeuroMath meeting in Stockholm, Sweden, in September 2008. At this occasion, scientists from different countries and different fields of research presented their research and discussed open questions with regard to analyses and models of mental disorders, in particular depression. The content of this paper emerged from these discussions and in the presentation we briefly link biomarkers (hormones, bio-signals (EEG and biomaps (brain-maps via EEG to depression and its treatments, via linear statistical models as well as nonlinear dynamic models. Some examples involving EEG-data are presented.
Ferrer, Román; Jammazi, Rania; Bolós, Vicente J.; Benítez, Rafael
2018-02-01
This paper examines the interactions between the main U.S. financial stress indices and several measures of economic activity in the time-frequency domain using a number of continuous cross-wavelet tools, including the usual wavelet squared coherence and phase difference as well as two new summary wavelet-based measures. The empirical results show that the relationship between financial stress and the U.S. real economy varies considerably over time and depending on the time horizon considered. A significant adverse effect of financial stress on U.S. economic activity is observed since the onset of the subprime mortgage crisis in the summer of 2007, indicating that the impact of financial market stress on the real economy is particularly severe during periods of major financial turmoil. Furthermore, the significant linkage between financial stress and the economic environment is mostly concentrated at time horizons from one to four years, demonstrating that the effect of financial stress on economic activity is especially visible in the long-run.
Vaus-Tamm, Heili, 1961-
2002-01-01
Olari Elts juhatab Fankfurdi Raadio Sümfooniaorkestrit. 4. jaan. Financial Time'is kirjutatakse Estonia uuslavastusest "Tark naine". Tallinna Filharmoonia sarja "Diplomaatilised noodid" lähimatest kontsertidest Tallinnas. 100 mustlasviiulit esineb 27. juulil Põltsamaa lossihoovis
Effects of time delay on stochastic resonance of the stock prices in financial system
International Nuclear Information System (INIS)
Li, Jiang-Cheng; Li, Chun; Mei, Dong-Cheng
2014-01-01
The effect of time delay on stochastic resonance of the stock prices in finance system was investigated. The time delay is introduced into the Heston model driven by the extrinsic and intrinsic periodic information for stock price. The signal power amplification (SPA) was calculated by numerical simulation. The results indicate that an optimal critical value of delay time maximally enhances the reverse-resonance in the behaviors of SPA as a function of long-run variance of volatility or cross correlation coefficient between noises for both cases of intrinsic and extrinsic periodic information. Moreover, in both cases, being a critical value in the delay time, when the delay time takes value below the critical value, reverse-resonance increases with the delay time increasing, however, when the delay time takes value above the critical value, the reverse-resonance decrease with the delay time increasing. - Highlights: • The effects of delay time on stochastic resonance of the stock prices was investigated. • There is an optimal critical value of delay time maximally enhances the reverse-resonance • The reverse-resonance increases with the delay time increasing as the delay time takes value below the critical value • The reverse-resonance decrease with the delay time increasing as the delay time takes value above the critical value
Effects of time delay on stochastic resonance of the stock prices in financial system
Energy Technology Data Exchange (ETDEWEB)
Li, Jiang-Cheng [Department of Physics, Yunnan University, Kunming, 650091 (China); Li, Chun [Department of Computer Science, Puer Teachers' College, Puer 665000 (China); Mei, Dong-Cheng, E-mail: meidch@ynu.edu.cn [Department of Physics, Yunnan University, Kunming, 650091 (China)
2014-06-13
The effect of time delay on stochastic resonance of the stock prices in finance system was investigated. The time delay is introduced into the Heston model driven by the extrinsic and intrinsic periodic information for stock price. The signal power amplification (SPA) was calculated by numerical simulation. The results indicate that an optimal critical value of delay time maximally enhances the reverse-resonance in the behaviors of SPA as a function of long-run variance of volatility or cross correlation coefficient between noises for both cases of intrinsic and extrinsic periodic information. Moreover, in both cases, being a critical value in the delay time, when the delay time takes value below the critical value, reverse-resonance increases with the delay time increasing, however, when the delay time takes value above the critical value, the reverse-resonance decrease with the delay time increasing. - Highlights: • The effects of delay time on stochastic resonance of the stock prices was investigated. • There is an optimal critical value of delay time maximally enhances the reverse-resonance • The reverse-resonance increases with the delay time increasing as the delay time takes value below the critical value • The reverse-resonance decrease with the delay time increasing as the delay time takes value above the critical value.
Allan deviation analysis of financial return series
Hernández-Pérez, R.
2012-05-01
We perform a scaling analysis for the return series of different financial assets applying the Allan deviation (ADEV), which is used in the time and frequency metrology to characterize quantitatively the stability of frequency standards since it has demonstrated to be a robust quantity to analyze fluctuations of non-stationary time series for different observation intervals. The data used are opening price daily series for assets from different markets during a time span of around ten years. We found that the ADEV results for the return series at short scales resemble those expected for an uncorrelated series, consistent with the efficient market hypothesis. On the other hand, the ADEV results for absolute return series for short scales (first one or two decades) decrease following approximately a scaling relation up to a point that is different for almost each asset, after which the ADEV deviates from scaling, which suggests that the presence of clustering, long-range dependence and non-stationarity signatures in the series drive the results for large observation intervals.
Non-stationary discharge patterns in motor cortex under subthalamic nucleus deep brain stimulation.
Santaniello, Sabato; Montgomery, Erwin B; Gale, John T; Sarma, Sridevi V
2012-01-01
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) directly modulates the basal ganglia (BG), but how such stimulation impacts the cortex upstream is largely unknown. There is evidence of cortical activation in 6-hydroxydopamine (OHDA)-lesioned rodents and facilitation of motor evoked potentials in Parkinson's disease (PD) patients, but the impact of the DBS settings on the cortical activity in normal vs. Parkinsonian conditions is still debated. We use point process models to analyze non-stationary activation patterns and inter-neuronal dependencies in the motor and sensory cortices of two non-human primates during STN DBS. These features are enhanced after treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), which causes a consistent PD-like motor impairment, while high-frequency (HF) DBS (i.e., ≥100 Hz) strongly reduces the short-term patterns (period: 3-7 ms) both before and after MPTP treatment, and elicits a short-latency post-stimulus activation. Low-frequency DBS (i.e., ≤50 Hz), instead, has negligible effects on the non-stationary features. Finally, by using tools from the information theory [i.e., receiver operating characteristic (ROC) curve and information rate (IR)], we show that the predictive power of these models is dependent on the DBS settings, i.e., the probability of spiking of the cortical neurons (which is captured by the point process models) is significantly conditioned on the timely delivery of the DBS input. This dependency increases with the DBS frequency and is significantly larger for high- vs. low-frequency DBS. Overall, the selective suppression of non-stationary features and the increased modulation of the spike probability suggest that HF STN DBS enhances the neuronal activation in motor and sensory cortices, presumably because of reinforcement mechanisms, which perhaps involve the overlap between feedback antidromic and feed-forward orthodromic responses along the BG-thalamo-cortical loop.
Carbon financial markets: A time-frequency analysis of CO2 prices
Sousa, Rita; Aguiar-Conraria, Luís; Soares, Maria Joana
2014-11-01
We characterize the interrelation of CO2 prices with energy prices (electricity, gas and coal), and with economic activity. Previous studies have relied on time-domain techniques, such as Vector Auto-Regressions. In this study, we use multivariate wavelet analysis, which operates in the time-frequency domain. Wavelet analysis provides convenient tools to distinguish relations at particular frequencies and at particular time horizons. Our empirical approach has the potential to identify relations getting stronger and then disappearing over specific time intervals and frequencies. We are able to examine the coherency of these variables and lead-lag relations at different frequencies for the time periods in focus.
Energy Technology Data Exchange (ETDEWEB)
Solodov, V G [Kharkov State Automobile and Highway Technical University, Theoretical Mechanics and Hydraulics Department, Kharkov (Ukraine)
1998-12-31
The article describes numerical models and some results of numerical simulation of self-excited oscillatory flow regimes through exhaust diffusers of large steam turbines, operating as a part of compartment (jointly with last stage). The modelling is based on a model of ideal gas flow and full nonstationary 3D formulation and 2nd time and space order explicit Godunov`s scheme. (author) 11 refs.
Energy Technology Data Exchange (ETDEWEB)
Solodov, V.G. [Kharkov State Automobile and Highway Technical University, Theoretical Mechanics and Hydraulics Department, Kharkov (Ukraine)
1997-12-31
The article describes numerical models and some results of numerical simulation of self-excited oscillatory flow regimes through exhaust diffusers of large steam turbines, operating as a part of compartment (jointly with last stage). The modelling is based on a model of ideal gas flow and full nonstationary 3D formulation and 2nd time and space order explicit Godunov`s scheme. (author) 11 refs.
A hybrid approach EMD-HW for short-term forecasting of daily stock market time series data
Awajan, Ahmad Mohd; Ismail, Mohd Tahir
2017-08-01
Recently, forecasting time series has attracted considerable attention in the field of analyzing financial time series data, specifically within the stock market index. Moreover, stock market forecasting is a challenging area of financial time-series forecasting. In this study, a hybrid methodology between Empirical Mode Decomposition with the Holt-Winter method (EMD-HW) is used to improve forecasting performances in financial time series. The strength of this EMD-HW lies in its ability to forecast non-stationary and non-linear time series without a need to use any transformation method. Moreover, EMD-HW has a relatively high accuracy and offers a new forecasting method in time series. The daily stock market time series data of 11 countries is applied to show the forecasting performance of the proposed EMD-HW. Based on the three forecast accuracy measures, the results indicate that EMD-HW forecasting performance is superior to traditional Holt-Winter forecasting method.
Wohlmuth, Johannes; Andersen, Jørgen Vitting
2006-05-01
We use agent-based models to study the competition among investors who use trading strategies with different amount of information and with different time scales. We find that mixing agents that trade on the same time scale but with different amount of information has a stabilizing impact on the large and extreme fluctuations of the market. Traders with the most information are found to be more likely to arbitrage traders who use less information in the decision making. On the other hand, introducing investors who act on two different time scales has a destabilizing effect on the large and extreme price movements, increasing the volatility of the market. Closeness in time scale used in the decision making is found to facilitate the creation of local trends. The larger the overlap in commonly shared information the more the traders in a mixed system with different time scales are found to profit from the presence of traders acting at another time scale than themselves.
AUTOMATIC CONTROL OF PARAMETERS OF A NON-STATIONARY OBJECT WITH CROSS LINKS
Directory of Open Access Journals (Sweden)
A. Pavlov
2018-04-01
Full Text Available Many objects automatic control unsteady. This is manifested in the change of their parameters. Therefore, periodically adjust the required parameters of the controller. This work is usually carried out rarely. For a long time, regulators are working with is not the optimal settings. The consequence of this is the low quality of many industrial control systems. The solution problem is the use of robust controllers. ACS with traditional PI and PID controllers have a very limited range of normal operation modes due to the appearance of parametric disturbances due to changes in the characteristics of the automated unit and changes in the load on it. The situation is different when using in the architecture of artificial neural network controllers. It is known that when training a neural network, the adaptation procedure is often used. This makes it possible to greatly expand the area of normal operating modes of ACS with neural automatic regulators in comparison with traditional linear regulators. It is also possible to significantly improve the quality of control (especially for a non-stationary multidimensional object, provided that when designing the ACS at the stage of its simulation in the model of the regulatory object model, an adequate simulation model of the executive device. It is also possible to significantly improve the quality of control (especially for a non-stationary multidimensional regulatory object model, an adequate simulation model of the executive device. Especially actual implementation of all these requirements in the application of electric actuators. This article fully complies with these requirements. This is what makes it possible to provide a guaranteed quality of control in non-stationary ACS with multidimensional objects and cross-links between control channels. The possibility of using a known hybrid automatic regulator to stabilize the parameters of a two-channel non-stationary object with two cross-linked. A
Cunningham, Peter J
2011-06-01
This study examines whether affordability thresholds for medical care as defined by families change over time. The results from two nationally representative surveys show that while financial stress from medical bills--defined as the percent with problems paying medical bills--increased between 2003 and 2007, greater out-of-pocket spending accounted for this increase only for higher-income persons with employer-sponsored insurance coverage. Increased spending did not account for an increase in medical bill problems among lower-income persons. Moreover, the increase in medical bill problems among low-income persons occurred at relatively low levels of out-of-pocket spending rather than at higher levels. The results suggest that "affordability thresholds" for medical care as defined by individuals and families are not stable over time, especially for lower-income persons, which has implications for setting affordability standards in health reform.
International Nuclear Information System (INIS)
Chang, C C; Hsiao, T C; Kao, S C; Hsu, H Y
2014-01-01
Arterial blood pressure (ABP) is an important indicator of cardiovascular circulation and presents various intrinsic regulations. It has been found that the intrinsic characteristics of blood vessels can be assessed quantitatively by ABP analysis (called reflection wave analysis (RWA)), but conventional RWA is insufficient for assessment during non-stationary conditions, such as the Valsalva maneuver. Recently, a novel adaptive method called empirical mode decomposition (EMD) was proposed for non-stationary data analysis. This study proposed a RWA algorithm based on EMD (EMD-RWA). A total of 51 subjects participated in this study, including 39 healthy subjects and 12 patients with autonomic nervous system (ANS) dysfunction. The results showed that EMD-RWA provided a reliable estimation of reflection time in baseline and head-up tilt (HUT). Moreover, the estimated reflection time is able to assess the ANS function non-invasively, both in normal, healthy subjects and in the patients with ANS dysfunction. EMD-RWA provides a new approach for reflection time estimation in non-stationary conditions, and also helps with non-invasive ANS assessment. (paper)
Splines employment for inverse problem of nonstationary thermal conduction
International Nuclear Information System (INIS)
Nikonov, S.P.; Spolitak, S.I.
1985-01-01
An analytical solution has been obtained for an inverse problem of nonstationary thermal conduction which is faced in nonstationary heat transfer data processing when the rewetting in channels with uniform annular fuel element imitators is investigated. In solving the problem both boundary conditions and power density within the imitator are regularized via cubic splines constructed with the use of Reinsch algorithm. The solution can be applied for calculation of temperature distribution in the imitator and the heat flux in two-dimensional approximation (r-z geometry) under the condition that the rewetting front velocity is known, and in one-dimensional r-approximation in cases with negligible axial transport or when there is a lack of data about the temperature disturbance source velocity along the channel
Non-stationary condition monitoring through event alignment
DEFF Research Database (Denmark)
Pontoppidan, Niels Henrik; Larsen, Jan
2004-01-01
We present an event alignment framework which enables change detection in non-stationary signals. change detection. Classical condition monitoring frameworks have been restrained to laboratory settings with stationary operating conditions, which are not resembling real world operation....... In this paper we apply the technique for non-stationary condition monitoring of large diesel engines based on acoustical emission sensor signals. The performance of the event alignment is analyzed in an unsupervised probabilistic detection framework based on outlier detection with either Principal Component...... Analysis or Gaussian Processes modeling. We are especially interested in the true performance of the condition monitoring performance with mixed aligned and unaligned data, e.g. detection of fault condition of unaligned examples versus false alarms of aligned normal condition data. Further, we expect...
Nonstationary ARCH and GARCH with t-distributed Innovations
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard; Rahbek, Anders
Consistency and asymptotic normality are established for the maximum likelihood estimators in the nonstationary ARCH and GARCH models with general t-distributed innovations. The results hold for joint estimation of (G)ARCH effects and the degrees of freedom parameter parametrizing the t-distribut......Consistency and asymptotic normality are established for the maximum likelihood estimators in the nonstationary ARCH and GARCH models with general t-distributed innovations. The results hold for joint estimation of (G)ARCH effects and the degrees of freedom parameter parametrizing the t......-distribution. With T denoting sample size, classic square-root T-convergence is shown to hold with closed form expressions for the multivariate covariances....
Non-Stationary Dependence Structures for Spatial Extremes
Huser, Raphaël
2016-03-03
Max-stable processes are natural models for spatial extremes because they provide suitable asymptotic approximations to the distribution of maxima of random fields. In the recent past, several parametric families of stationary max-stable models have been developed, and fitted to various types of data. However, a recurrent problem is the modeling of non-stationarity. In this paper, we develop non-stationary max-stable dependence structures in which covariates can be easily incorporated. Inference is performed using pairwise likelihoods, and its performance is assessed by an extensive simulation study based on a non-stationary locally isotropic extremal t model. Evidence that unknown parameters are well estimated is provided, and estimation of spatial return level curves is discussed. The methodology is demonstrated with temperature maxima recorded over a complex topography. Models are shown to satisfactorily capture extremal dependence.
Learning in Non-Stationary Environments Methods and Applications
Lughofer, Edwin
2012-01-01
Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences. Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dyna...
ADSL Transceivers Applying DSM and Their Nonstationary Noise Robustness
Directory of Open Access Journals (Sweden)
Bostoen Tom
2006-01-01
Full Text Available Dynamic spectrum management (DSM comprises a new set of techniques for multiuser power allocation and/or detection in digital subscriber line (DSL networks. At the Alcatel Research and Innovation Labs, we have recently developed a DSM test bed, which allows the performance of DSM algorithms to be evaluated in practice. With this test bed, we have evaluated the performance of a DSM level-1 algorithm known as iterative water-filling in an ADSL scenario. This paper describes the results of, on the one hand, the performance gains achieved with iterative water-filling, and, on the other hand, the nonstationary noise robustness of DSM-enabled ADSL modems. It will be shown that DSM trades off nonstationary noise robustness for performance improvements. A new bit swap procedure is then introduced to increase the noise robustness when applying DSM.
López, J.; Francés, F.
2013-08-01
Recent evidences of the impact of persistent modes of regional climate variability, coupled with the intensification of human activities, have led hydrologists to study flood regime without applying the hypothesis of stationarity. In this study, a framework for flood frequency analysis is developed on the basis of a tool that enables us to address the modelling of non-stationary time series, namely, the "generalized additive models for location, scale and shape" (GAMLSS). Two approaches to non-stationary modelling in GAMLSS were applied to the annual maximum flood records of 20 continental Spanish rivers. The results of the first approach, in which the parameters of the selected distributions were modelled as a function of time only, show the presence of clear non-stationarities in the flood regime. In a second approach, the parameters of the flood distributions are modelled as functions of climate indices (Arctic Oscillation, North Atlantic Oscillation, Mediterranean Oscillation and the Western Mediterranean Oscillation) and a reservoir index that is proposed in this paper. The results when incorporating external covariates in the study highlight the important role of interannual variability in low-frequency climate forcings when modelling the flood regime in continental Spanish rivers. Also, with this approach it is possible to properly introduce the impact on the flood regime of intensified reservoir regulation strategies. The inclusion of external covariates permits the use of these models as predictive tools. Finally, the application of non-stationary analysis shows that the differences between the non-stationary quantiles and their stationary equivalents may be important over long periods of time.
Directory of Open Access Journals (Sweden)
J. López
2013-08-01
Full Text Available Recent evidences of the impact of persistent modes of regional climate variability, coupled with the intensification of human activities, have led hydrologists to study flood regime without applying the hypothesis of stationarity. In this study, a framework for flood frequency analysis is developed on the basis of a tool that enables us to address the modelling of non-stationary time series, namely, the "generalized additive models for location, scale and shape" (GAMLSS. Two approaches to non-stationary modelling in GAMLSS were applied to the annual maximum flood records of 20 continental Spanish rivers. The results of the first approach, in which the parameters of the selected distributions were modelled as a function of time only, show the presence of clear non-stationarities in the flood regime. In a second approach, the parameters of the flood distributions are modelled as functions of climate indices (Arctic Oscillation, North Atlantic Oscillation, Mediterranean Oscillation and the Western Mediterranean Oscillation and a reservoir index that is proposed in this paper. The results when incorporating external covariates in the study highlight the important role of interannual variability in low-frequency climate forcings when modelling the flood regime in continental Spanish rivers. Also, with this approach it is possible to properly introduce the impact on the flood regime of intensified reservoir regulation strategies. The inclusion of external covariates permits the use of these models as predictive tools. Finally, the application of non-stationary analysis shows that the differences between the non-stationary quantiles and their stationary equivalents may be important over long periods of time.
A non-stationary cost-benefit based bivariate extreme flood estimation approach
Qi, Wei; Liu, Junguo
2018-02-01
Cost-benefit analysis and flood frequency analysis have been integrated into a comprehensive framework to estimate cost effective design values. However, previous cost-benefit based extreme flood estimation is based on stationary assumptions and analyze dependent flood variables separately. A Non-Stationary Cost-Benefit based bivariate design flood estimation (NSCOBE) approach is developed in this study to investigate influence of non-stationarities in both the dependence of flood variables and the marginal distributions on extreme flood estimation. The dependence is modeled utilizing copula functions. Previous design flood selection criteria are not suitable for NSCOBE since they ignore time changing dependence of flood variables. Therefore, a risk calculation approach is proposed based on non-stationarities in both marginal probability distributions and copula functions. A case study with 54-year observed data is utilized to illustrate the application of NSCOBE. Results show NSCOBE can effectively integrate non-stationarities in both copula functions and marginal distributions into cost-benefit based design flood estimation. It is also found that there is a trade-off between maximum probability of exceedance calculated from copula functions and marginal distributions. This study for the first time provides a new approach towards a better understanding of influence of non-stationarities in both copula functions and marginal distributions on extreme flood estimation, and could be beneficial to cost-benefit based non-stationary bivariate design flood estimation across the world.
Online updating and uncertainty quantification using nonstationary output-only measurement
Yuen, Ka-Veng; Kuok, Sin-Chi
2016-01-01
Extended Kalman filter (EKF) is widely adopted for state estimation and parametric identification of dynamical systems. In this algorithm, it is required to specify the covariance matrices of the process noise and measurement noise based on prior knowledge. However, improper assignment of these noise covariance matrices leads to unreliable estimation and misleading uncertainty estimation on the system state and model parameters. Furthermore, it may induce diverging estimation. To resolve these problems, we propose a Bayesian probabilistic algorithm for online estimation of the noise parameters which are used to characterize the noise covariance matrices. There are three major appealing features of the proposed approach. First, it resolves the divergence problem in the conventional usage of EKF due to improper choice of the noise covariance matrices. Second, the proposed approach ensures the reliability of the uncertainty quantification. Finally, since the noise parameters are allowed to be time-varying, nonstationary process noise and/or measurement noise are explicitly taken into account. Examples using stationary/nonstationary response of linear/nonlinear time-varying dynamical systems are presented to demonstrate the efficacy of the proposed approach. Furthermore, comparison with the conventional usage of EKF will be provided to reveal the necessity of the proposed approach for reliable model updating and uncertainty quantification.
Self-adaptive change detection in streaming data with non-stationary distribution
Zhang, Xiangliang
2010-01-01
Non-stationary distribution, in which the data distribution evolves over time, is a common issue in many application fields, e.g., intrusion detection and grid computing. Detecting the changes in massive streaming data with a non-stationary distribution helps to alarm the anomalies, to clean the noises, and to report the new patterns. In this paper, we employ a novel approach for detecting changes in streaming data with the purpose of improving the quality of modeling the data streams. Through observing the outliers, this approach of change detection uses a weighted standard deviation to monitor the evolution of the distribution of data streams. A cumulative statistical test, Page-Hinkley, is employed to collect the evidence of changes in distribution. The parameter used for reporting the changes is self-adaptively adjusted according to the distribution of data streams, rather than set by a fixed empirical value. The self-adaptability of the novel approach enhances the effectiveness of modeling data streams by timely catching the changes of distributions. We validated the approach on an online clustering framework with a benchmark KDDcup 1999 intrusion detection data set as well as with a real-world grid data set. The validation results demonstrate its better performance on achieving higher accuracy and lower percentage of outliers comparing to the other change detection approaches. © 2010 Springer-Verlag.
On the dynamics of non-stationary binary stellar systems
International Nuclear Information System (INIS)
Bekov, A. A.; Bejsekov, A.N.; Aldibaeva, L.T.
2005-01-01
The motion of test body in the external gravitational field of the binary stellar system with slowly variable some physical parameters of radiating components is considered on the base of restricted non-stationary photo-gravitational three and two bodies problem. The family of polar and coplanar solutions are obtained. These solutions give the possibility of the dynamical and structure interpretation of the binary young evolving stars and galaxies. (author)
Nonstationary heat flow in the piston of the turbocharged engine
Directory of Open Access Journals (Sweden)
Piotr GUSTOF
2010-01-01
Full Text Available In this study the numeric computations of nonstationary heat flow in form of temperature distribution on characteristic surfaces of the piston of the turbocharged engine at the beginning phase its work was presented. The computations were performed for fragmentary load engine by means of the two-zone combustion model, the boundary conditions of III kind and the finite elements method (FEM by using of COSMOS/M program.
Real-time decision support and information gathering system for financial domain
Tseng, Chiu-Che; Gmytrasiewicz, Piotr J.
2006-05-01
The challenge of the investment domain is that a large amount of diverse information can be potentially relevant to an investment decision, and that, frequently, the decisions have to be made in a timely manner. This presents the potential for better decision support, but poses the challenge of building a decision support agent that gathers information from different sources and incorporates it for timely decision support. These problems motivate us to investigate ways in which the investors can be equipped with a flexible real-time decision support system to be practical in time-critical situations. The flexible real-time decision support system considers a tradeoff between decision quality and computation cost. For this purpose, we propose a system that uses the object oriented Bayesian knowledge base (OOBKB) design to create a decision model at the most suitable level of detail to guide the information gathering activities, and to produce an investment recommendation within a reasonable length of time. The decision models our system uses are implemented as influence diagrams. We validate our system with experiments in a simplified investment domain. The experiments show that our system produces a quality recommendation under different urgency situations. The contribution of our system is that it provides the flexible decision recommendation for an investor under time constraints in a complex environment.
Energy Technology Data Exchange (ETDEWEB)
Zentner, I. [IMSIA, UMR EDF-ENSTA-CNRS-CEA 9219, Université Paris-Saclay, 828 Boulevard des Maréchaux, 91762 Palaiseau Cedex (France); Ferré, G., E-mail: gregoire.ferre@ponts.org [CERMICS – Ecole des Ponts ParisTech, 6 et 8 avenue Blaise Pascal, Cité Descartes, Champs sur Marne, 77455 Marne la Vallée Cedex 2 (France); Poirion, F. [Department of Structural Dynamics and Aeroelasticity, ONERA, BP 72, 29 avenue de la Division Leclerc, 92322 Chatillon Cedex (France); Benoit, M. [Institut de Recherche sur les Phénomènes Hors Equilibre (IRPHE), UMR 7342 (CNRS, Aix-Marseille Université, Ecole Centrale Marseille), 49 rue Frédéric Joliot-Curie, BP 146, 13384 Marseille Cedex 13 (France)
2016-06-01
In this paper, a new method for the identification and simulation of non-Gaussian and non-stationary stochastic fields given a database is proposed. It is based on two successive biorthogonal decompositions aiming at representing spatio–temporal stochastic fields. The proposed double expansion allows to build the model even in the case of large-size problems by separating the time, space and random parts of the field. A Gaussian kernel estimator is used to simulate the high dimensional set of random variables appearing in the decomposition. The capability of the method to reproduce the non-stationary and non-Gaussian features of random phenomena is illustrated by applications to earthquakes (seismic ground motion) and sea states (wave heights).
Ghosh, Sayantan; Manimaran, P.; Panigrahi, Prasanta K.
2011-11-01
We make use of wavelet transform to study the multi-scale, self-similar behavior and deviations thereof, in the stock prices of large companies, belonging to different economic sectors. The stock market returns exhibit multi-fractal characteristics, with some of the companies showing deviations at small and large scales. The fact that, the wavelets belonging to the Daubechies’ (Db) basis enables one to isolate local polynomial trends of different degrees, plays the key role in isolating fluctuations at different scales. One of the primary motivations of this work is to study the emergence of the k-3 behavior [X. Gabaix, P. Gopikrishnan, V. Plerou, H. Stanley, A theory of power law distributions in financial market fluctuations, Nature 423 (2003) 267-270] of the fluctuations starting with high frequency fluctuations. We make use of Db4 and Db6 basis sets to respectively isolate local linear and quadratic trends at different scales in order to study the statistical characteristics of these financial time series. The fluctuations reveal fat tail non-Gaussian behavior, unstable periodic modulations, at finer scales, from which the characteristic k-3 power law behavior emerges at sufficiently large scales. We further identify stable periodic behavior through the continuous Morlet wavelet.
Law and Financial Development: What we are learning from time-series evidence
Armour, J.; Deakin, S.; Mollica, V.; Siems, M.M.
2010-01-01
The legal origins hypothesis is one of the most important and influential ideas to emerge in the social sciences in the past decade. However, the empirical base of the legal origins claim has always been contestable, as it largely consists of cross-sectional datasets which provide evidence on the state of the law only at limited points in time. There is now a growing body of data derived from techniques for coding cross-national legal variation over time. This time-series evidence is reviewed...
Park, Jeryang; Rao, P Suresh C
2014-11-15
We present here a conceptual model and analysis of complex systems using hypothetical cases of regime shifts resulting from temporal non-stationarity in attractor strengths, and then present selected published cases to illustrate such regime shifts in hydrologic systems (shallow aquatic ecosystems; water table shifts; soil salinization). Complex systems are dynamic and can exist in two or more stable states (or regimes). Temporal variations in state variables occur in response to fluctuations in external forcing, which are modulated by interactions among internal processes. Combined effects of external forcing and non-stationary strengths of alternative attractors can lead to shifts from original to alternate regimes. In systems with bi-stable states, when the strengths of two competing attractors are constant in time, or are non-stationary but change in a linear fashion, regime shifts are found to be temporally stationary and only controlled by the characteristics of the external forcing. However, when attractor strengths change in time non-linearly or vary stochastically, regime shifts in complex systems are characterized by non-stationary probability density functions (pdfs). We briefly discuss implications and challenges to prediction and management of hydrologic complex systems. Copyright © 2014 Elsevier B.V. All rights reserved.
Financial globalisation uncertainty/instability is good for financial development
Asongu, Simplice A.; Koomson, Isaac; Tchamyou, Vanessa S.
2015-01-01
Purpose – This study assesses the effect of time-dynamic financial globalisation uncertainty on financial development in 53 African countries for the period 2000-2011. Design/methodology/approach – Financial globalisation uncertainty is estimated as time-dynamic to capture business cycle disturbances while all dimensions identified by the Financial Development and Structure Database of the World Bank are employed, namely: financial depth (money supply and liquid liabilities), financial sy...
Directory of Open Access Journals (Sweden)
Sunaryo Sunaryo
2012-11-01
Full Text Available The primary objective of this research is to learn the effect among ROA, Leverage, Company Size, and Outsider Ownership with time lines, either partially or simultaneously. Secondary data were collected by purposive sampling of manufacturing company groups listed on IDX and the preceding scientific research journals, using logistic regression to test the hypothesis simultaneously. The results of this research describe that ROA and Leverage do not significant effect to time lines, but company size and outsider ownership have significant effect to time lines. It is recommended that the topic of this research can be continued with merchandising company groups, or service company groups either general or special, like: hotels, insurances, bankings; or, with new independence variables added.
Directory of Open Access Journals (Sweden)
Yue Hu
2018-01-01
Full Text Available Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST and multi-taper empirical wavelet transform (MTEWT is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR. As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults.
Hu, Yue; Tu, Xiaotong; Li, Fucai; Meng, Guang
2018-01-07
Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR). As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults.
Kavanagh, Anne M; Mason, Kate E; Bentley, Rebecca J; Studdert, David M; McVernon, Jodie; Fielding, James E; Petrony, Sylvia; Gurrin, Lyle; LaMontagne, Anthony D
2012-11-20
The Australian state of Victoria, with 5.2 million residents, enforced home quarantine during a H1N1 pandemic in 2009. The strategy was targeted at school children. The objective of this study was to investigate the extent to which parents' access to paid sick leave or paid carer's leave was associated with (a) time taken off work to care for quarantined children, (b) household finances, and (c) compliance with quarantine recommendations. We conducted an online and telephone survey of households recruited through 33 schools (85% of eligible schools), received 314 responses (27%), and analysed the subsample of 133 households in which all resident parents were employed. In 52% of households, parents took time off work to care for quarantined children. Households in which no resident parent had access to leave appeared to be less likely to take time off work (42% vs 58%, p=0.08) although this difference had only borderline significance. Among parents who did take time off work, those in households without access to leave were more likely to lose pay (73% vs 21%, pparent lost pay due to taking time off work, 42% experienced further financial consequences such as being unable to pay a bill. Access to leave did not predict compliance with quarantine recommendations. Future pandemic plans should consider the economic costs borne by households and options for compensating quarantined families for income losses.
The Philosopher's Stone: How Basic Skills Programs Fare in Troubled Financial Times
Ray, Thomas P.
2012-01-01
This mixed methods study examined the relative position of basic skills programs with transfer and career technical programs in a large suburban community college in California during the three-year period of budget reductions from 2009-2010 through 2011-2012. The budget line dedicated to part-time or non-contract instruction was analyzed along…
Career in the bank for collection in times of financial crisis
Directory of Open Access Journals (Sweden)
Ioana Florentina BUDU
2009-06-01
Full Text Available Staffing a collection call centre, in a period of crisis, requires more than hiring the most qualified applicants. Collection managers must define a recruiting, hiring and staffing plan to meet inbound call service levels and maximize outbound calling during optimal customer contact times, usually on nights and weekends. Job candidates who have prior telephone job experience, especially in telemarketing or customer service, have proven to be successful collectors because of their skill sets and experience. Screening collectors through testing has proven to be a reliable tool to assist managers in the selection process. Staffing the call centre operation with the right balance between full time and part time collectors will assist in meeting department targets. There are many creative ways to schedule collectors to cover all the required hours. Management must be prepared to offset ‘irregular’ staffing hours, especially on nights and weekends, with incentive, perks and benefits so they can recruit and retain a reliable staff to place outbound calls during the best times to reach the customer. A consistent hiring policy that is constantly evaluated and improved will help reduce turnover by recruiting and staffing the most qualified collectors for the job
Non-stationary and relaxation phenomena in cavity-assisted quantum memories
Veselkova, N. G.; Sokolov, I. V.
2017-12-01
We investigate the non-stationary and relaxation phenomena in cavity-assisted quantum memories for light. As a storage medium we consider an ensemble of cold atoms with standard Lambda-scheme of working levels. Some theoretical aspects of the problem were treated previously by many authors, and recent experiments stimulate more deep insight into the ultimate ability and limitations of the device. Since quantum memories can be used not only for the storage of quantum information, but also for a substantial manipulation of ensembles of quantum states, the speed of such manipulation and hence the ability to write and retrieve the signals of relatively short duration becomes important. In our research we do not apply the so-called bad cavity limit, and consider the memory operation of the signals whose duration is not much larger than the cavity field lifetime, accounting also for the finite lifetime of atomic coherence. In our paper we present an effective approach that makes it possible to find the non-stationary amplitude and phase behavior of strong classical control field, that matches the desirable time profile of both the envelope and the phase of the retrieved quantized signal. The phase properties of the retrieved quantized signals are of importance for the detection and manipulation of squeezing, entanglement, etc by means of optical mixing and homodyning.
Quantum Radiation Properties of Dirac Particles in General Nonstationary Black Holes
Directory of Open Access Journals (Sweden)
Jia-Chen Hua
2014-01-01
Full Text Available Quantum radiation properties of Dirac particles in general nonstationary black holes in the general case are investigated by both using the method of generalized tortoise coordinate transformation and considering simultaneously the asymptotic behaviors of the first-order and second-order forms of Dirac equation near the event horizon. It is generally shown that the temperature and the shape of the event horizon of this kind of black holes depend on both the time and different angles. Further, we give a general expression of the new extra coupling effect in thermal radiation spectrum of Dirac particles which is absent from the thermal radiation spectrum of scalar particles. Also, we reveal a relationship that is ignored before between thermal radiation and nonthermal radiation in the case of scalar particles, which is that the chemical potential in thermal radiation spectrum is equal to the highest energy of the negative energy state of scalar particles in nonthermal radiation for general nonstationary black holes.
Directory of Open Access Journals (Sweden)
P. Ribereau
2008-12-01
Full Text Available Since the pioneering work of Landwehr et al. (1979, Hosking et al. (1985 and their collaborators, the Probability Weighted Moments (PWM method has been very popular, simple and efficient to estimate the parameters of the Generalized Extreme Value (GEV distribution when modeling the distribution of maxima (e.g., annual maxima of precipitations in the Identically and Independently Distributed (IID context. When the IID assumption is not satisfied, a flexible alternative, the Maximum Likelihood Estimation (MLE approach offers an elegant way to handle non-stationarities by letting the GEV parameters to be time dependent. Despite its qualities, the MLE applied to the GEV distribution does not always provide accurate return level estimates, especially for small sample sizes or heavy tails. These drawbacks are particularly true in some non-stationary situations. To reduce these negative effects, we propose to extend the PWM method to a more general framework that enables us to model temporal covariates and provide accurate GEV-based return levels. Theoretical properties of our estimators are discussed. Small and moderate sample sizes simulations in a non-stationary context are analyzed and two brief applications to annual maxima of CO_{2} and seasonal maxima of cumulated daily precipitations are presented.
Climate variability and nonstationary dynamics of Mycoplasma pneumoniae pneumonia in Japan.
Onozuka, Daisuke; Chaves, Luis Fernando
2014-01-01
A stationary association between climate factors and epidemics of Mycoplasma pneumoniae (M. pneumoniae) pneumonia has been widely assumed. However, it is unclear whether elements of the local climate that are relevant to M. pneumoniae pneumonia transmission have stationary signatures of climate factors on their dynamics over different time scales. We performed a cross-wavelet coherency analysis to assess the patterns of association between monthly M. pneumoniae cases in Fukuoka, Japan, from 2000 to 2012 and indices for the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO). Monthly M. pneumoniae cases were strongly associated with the dynamics of both the IOD and ENSO for the 1-2-year periodic mode in 2005-2007 and 2010-2011. This association was non-stationary and appeared to have a major influence on the synchrony of M. pneumoniae epidemics. Our results call for the consideration of non-stationary, possibly non-linear, patterns of association between M. pneumoniae cases and climatic factors in early warning systems.
Climate variability and nonstationary dynamics of Mycoplasma pneumoniae pneumonia in Japan.
Directory of Open Access Journals (Sweden)
Daisuke Onozuka
Full Text Available BACKGROUND: A stationary association between climate factors and epidemics of Mycoplasma pneumoniae (M. pneumoniae pneumonia has been widely assumed. However, it is unclear whether elements of the local climate that are relevant to M. pneumoniae pneumonia transmission have stationary signatures of climate factors on their dynamics over different time scales. METHODS: We performed a cross-wavelet coherency analysis to assess the patterns of association between monthly M. pneumoniae cases in Fukuoka, Japan, from 2000 to 2012 and indices for the Indian Ocean Dipole (IOD and El Niño Southern Oscillation (ENSO. RESULTS: Monthly M. pneumoniae cases were strongly associated with the dynamics of both the IOD and ENSO for the 1-2-year periodic mode in 2005-2007 and 2010-2011. This association was non-stationary and appeared to have a major influence on the synchrony of M. pneumoniae epidemics. CONCLUSIONS: Our results call for the consideration of non-stationary, possibly non-linear, patterns of association between M. pneumoniae cases and climatic factors in early warning systems.
A review on prognostic techniques for non-stationary and non-linear rotating systems
Kan, Man Shan; Tan, Andy C. C.; Mathew, Joseph
2015-10-01
The field of prognostics has attracted significant interest from the research community in recent times. Prognostics enables the prediction of failures in machines resulting in benefits to plant operators such as shorter downtimes, higher operation reliability, reduced operations and maintenance cost, and more effective maintenance and logistics planning. Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. As such, there is an urgent need to develop prognostic techniques for such complex systems operating in the real world. This review paper focuses on prognostic techniques that can be applied to rotating machinery operating under non-linear and non-stationary conditions. The general concept of these techniques, the pros and cons of applying these methods, as well as their applications in the research field are discussed. Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under non-stationary and non-linear conditions are also discussed.
Khot, Umesh N; Johnson-Wood, Michele L; Geddes, Jason B; Ramsey, Curtis; Khot, Monica B; Taillon, Heather; Todd, Randall; Shaikh, Saeed R; Berg, William J
2009-07-26
The impact of reducing door-to-balloon time on hospital revenues, costs, and net income is unknown. We prospectively determined the impact on hospital finances of (1) emergency department physician activation of the catheterization lab and (2) immediate transfer of the patient to an immediately available catheterization lab by an in-house transfer team consisting of an emergency department nurse, a critical care unit nurse, and a chest pain unit nurse. We collected financial data for 52 consecutive ST-elevation myocardial infarction patients undergoing emergency percutaneous intervention from October 1, 2004-August 31, 2005 and compared this group to 80 consecutive ST-elevation myocardial infarction patients from September 1, 2005-June 26, 2006 after protocol implementation. Per hospital admission, insurance payments (hospital revenue) decreased ($35,043 +/- $36,670 vs. $25,329 +/- $16,185, P = 0.039) along with total hospital costs ($28,082 +/- $31,453 vs. $18,195 +/- $9,242, P = 0.009). Hospital net income per admission was unchanged ($6962 vs. $7134, P = 0.95) as the drop in hospital revenue equaled the drop in costs. For every $1000 reduction in total hospital costs, insurance payments (hospital revenue) dropped $1077 for private payers and $1199 for Medicare/Medicaid. A decrease in hospital charges ($70,430 +/- $74,033 vs. $53,514 +/- $23,378, P = 0.059), diagnosis related group relative weight (3.7479 +/- 2.6731 vs. 2.9729 +/- 0.8545, P = 0.017) and outlier payments with hospital revenue>$100,000 (7.7% vs. 0%, P = 0.022) all contributed to decreasing ST-elevation myocardial infarction hospitalization revenue. One-year post-discharge financial follow-up revealed similar results: Insurance payments: $49,959 +/- $53,741 vs. $35,937 +/- $23,125, P = 0.044; Total hospital costs: $39,974 +/- $37,434 vs. $26,778 +/- $15,561, P = 0.007; Net Income: $9984 vs. $9159, P = 0.855. All of the financial benefits of reducing door-to-balloon time in ST-elevation myocardial
Scaling Exponents in Financial Markets
Kim, Kyungsik; Kim, Cheol-Hyun; Kim, Soo Yong
2007-03-01
We study the dynamical behavior of four exchange rates in foreign exchange markets. A detrended fluctuation analysis (DFA) is applied to detect the long-range correlation embedded in the non-stationary time series. It is for our case found that there exists a persistent long-range correlation in volatilities, which implies the deviation from the efficient market hypothesis. Particularly, the crossover is shown to exist in the scaling behaviors of the volatilities.
DEFF Research Database (Denmark)
Amado, Cristina; Teräsvirta, Timo
-run and the short-run dynamic behaviour of the volatilities. The structure of the conditional correlation matrix is assumed to be either time independent or to vary over time. We apply our model to pairs of seven daily stock returns belonging to the S&P 500 composite index and traded at the New York Stock Exchange......In this paper we investigate the effects of careful modelling the long-run dynamics of the volatilities of stock market returns on the conditional correlation structure. To this end we allow the individual unconditional variances in Conditional Correlation GARCH models to change smoothly over time...... by incorporating a nonstationary component in the variance equations. The modelling technique to determine the parametric structure of this time-varying component is based on a sequence of specification Lagrange multiplier-type tests derived in Amado and Teräsvirta (2011). The variance equations combine the long...
Aristizabal, F; Glavinovic, M I
2003-10-01
Tracking spectral changes of rapidly varying signals is a demanding task. In this study, we explore on Monte Carlo-simulated glutamate-activated AMPA patch and synaptic currents whether a wavelet analysis offers such a possibility. Unlike Fourier methods that determine only the frequency content of a signal, the wavelet analysis determines both the frequency and the time. This is owing to the nature of the basis functions, which are infinite for Fourier transforms (sines and cosines are infinite), but are finite for wavelet analysis (wavelets are localized waves). In agreement with previous reports, the frequency of the stationary patch current fluctuations is higher for larger currents, whereas the mean-variance plots are parabolic. The spectra of the current fluctuations and mean-variance plots are close to the theoretically predicted values. The median frequency of the synaptic and nonstationary patch currents is, however, time dependent, though at the peak of synaptic currents, the median frequency is insensitive to the number of glutamate molecules released. Such time dependence demonstrates that the "composite spectra" of the current fluctuations gathered over the whole duration of synaptic currents cannot be used to assess the mean open time or effective mean open time of AMPA channels. The current (patch or synaptic) versus median frequency plots show hysteresis. The median frequency is thus not a simple reflection of the overall receptor saturation levels and is greater during the rise phase for the same saturation level. The hysteresis is due to the higher occupancy of the doubly bound state during the rise phase and not due to the spatial spread of the saturation disk, which remains remarkably constant. Albeit time dependent, the variance of the synaptic and nonstationary patch currents can be accurately determined. Nevertheless the evaluation of the number of AMPA channels and their single current from the mean-variance plots of patch or synaptic
Financial history and financial economics
Turner, John D.
2014-01-01
This essay looks at the bidirectional relationship between financial history and financial economics. It begins by giving a brief history of financial economics by outlining the main topics of interest to financial economists. It then documents and explains the increasing influence of financial economics upon financial history, and warns of the dangers of applying financial economics unthinkingly to the study of financial history. The essay proceeds to highlight the many insights that financi...
Optimizing a Military Supply Chain in the Presence of Random, Non-Stationary Demands
National Research Council Canada - National Science Library
Yew
2003-01-01
... logistics supply chain that satisfies uncertain, non-stationary demands, while taking into account the volatility and singularity of military operations This research focuses on the development...
Jaber, Abobaker M; Ismail, Mohd Tahir; Altaher, Alsaidi M
2014-01-01
This paper mainly forecasts the daily closing price of stock markets. We propose a two-stage technique that combines the empirical mode decomposition (EMD) with nonparametric methods of local linear quantile (LLQ). We use the proposed technique, EMD-LLQ, to forecast two stock index time series. Detailed experiments are implemented for the proposed method, in which EMD-LPQ, EMD, and Holt-Winter methods are compared. The proposed EMD-LPQ model is determined to be superior to the EMD and Holt-Winter methods in predicting the stock closing prices.
Park, Junehyeong; Sung, Jang Hyun; Lim, Yoon-Jin; Kang, Hyun-Suk
2018-05-01
The widely used meteorological drought index, the Standardized Precipitation Index (SPI), basically assumes stationarity, but recent changes in the climate have led to a need to review this hypothesis. In this study, a new non-stationary SPI that considers not only the modified probability distribution parameter but also the return period under the non-stationary process was proposed. The results were evaluated for two severe drought cases during the last 10 years in South Korea. As a result, SPIs considered that the non-stationary hypothesis underestimated the drought severity than the stationary SPI despite that these past two droughts were recognized as significantly severe droughts. It may be caused by that the variances of summer and autumn precipitation become larger over time then it can make the probability distribution wider than before. This implies that drought expressions by statistical index such as SPI can be distorted by stationary assumption and cautious approach is needed when deciding drought level considering climate changes.
Thiombiano, Alida N.; El Adlouni, Salaheddine; St-Hilaire, André; Ouarda, Taha B. M. J.; El-Jabi, Nassir
2017-07-01
In this paper, a statistical inference of Southeastern Canada extreme daily precipitation amounts is proposed using a classical nonstationary peaks-over-threshold model. Indeed, the generalized Pareto distribution (GPD) is fitted to excess time series derived from annual averages of independent precipitation amount events above a fixed threshold, the 99th percentile. Only the scale parameter of the fitted distribution is allowed to vary as a function of a covariate. This variability is modeled using B-spline function. Nonlinear correlation and cross-wavelet analysis allowed identifying two dominant climate indices as covariates in the study area, Arctic Oscillation (AO) and Pacific North American (PNA). The nonstationary frequency analysis showed that there is an east-west behavior of the AO index effects on extreme daily precipitation amounts in the study area. Indeed, the higher quantiles of these events are conditional to the AO positive phase in Atlantic Canada, while those in the more southeastern part of Canada, especially in Southern Quebec and Ontario, are negatively related to AO. The negative phase of PNA also gives the best significant correlation in these regions. Moreover, a regression analysis between AO (PNA) index and conditional quantiles provided slope values for the positive phase of the index on the one hand and the negative phase and on the other hand. This statistic allows computing a slope ratio which permits to sustain the nonlinear relation assumption between climate indices and precipitation and the development of the nonstationary GPD model for Southeastern Canada extremes precipitation modeling.
Time is ripe to act on Middle East weapons. Op-ed essay, published in the Financial Times
International Nuclear Information System (INIS)
ElBaradei, M.; Rotblat, J.
2004-01-01
Full text: The writing is on the wall: the Middle East is fertile ground for proliferation concerns. Despite progress in obtaining greater transparency on the nuclear programmes of Iran, Iraq and Libya, a deep sense of insecurity remains. The symptoms are everywhere in the region: the Arab-Israeli conflict continues to fester. Regime change is talked of as the most efficient route to democracy. The situation in Iraq, and its regional security implications, remains far from certain. Tensions with the west have increasingly become subtly - and not so subtly - associated with Muslim culture. More countries in the Middle East have refused to sign global treaties banning nuclear, biological and chemical weapons than in any other region. In the absence of a comprehensive settlement, Israel refuses to discuss its purportedly sizeable nuclear arsenal and shrugs off repeated requests to join the Treaty on the Non-Proliferation of Nuclear Weapons (NPT). This and the accompanying sense of insecurity have served as an incentive for countries to arm themselves with equal or similar weapons capacity. A recent poll by the Arabic-language Al-Jazeera website showed that more than 80 per cent of respondents favoured acquisition of nuclear weapons by the Arab world. But this mini arms-race has made no one feel more secure. In addition, the increasing sophistication of clandestine programmes, greater access to nuclear and other weapons technology and the increasingly evident black market for illicit acquisition of designs, components and expertise increase the prospect that extremist groups will acquire weapons of mass destruction. If we had any doubts before, it should be clear now that the Middle East situation is unsustainable. If we do nothing, catastrophe is only a matter of time. A great deal of rhetoric has emerged over the idea of making the Middle East a WMD-free region. The establishment of a nuclear-weapons-free zone has been the topic of UN resolutions for 30 years, with
Impact of the global financial crisis on low birth weight in Portugal: a time-trend analysis.
Kana, Musa Abubakar; Correia, Sofia; Peleteiro, Barbara; Severo, Milton; Barros, Henrique
2017-01-01
The 2007-2008 global financial crisis had adverse consequences on population health of affected European countries. Few contemporary studies have studied its effect on perinatal indicators with long-lasting influence on adult health. Therefore, in this study, we investigated the impact of the 2007-2008 global financial crisis on low birth weight (LBW) in Portugal. Data on 2 045 155 singleton births of 1995-2014 were obtained from Statistics Portugal. Joinpoint regression analysis was performed to identify the years in which changes in LBW trends occurred, and to estimate the annual per cent changes (APC). LBW risk by time period expressed as prevalence ratios were computed using the Poisson regression. Contextual changes in sociodemographic and economic factors were provided by their trends. The joinpoint analysis identified 3 distinct periods (2 jointpoints) with different APC in LBW, corresponding to 1995-1999 (APC=4.4; 95% CI 3.2 to 5.6), 2000-2006 (APC=0.1; 95% CI -050 to 0.7) and 2007-2014 (APC=1.6; 95% CI 1.2 to 2.0). For non-Portuguese, it was, respectively, 1995-1999 (APC=1.4; 95% CI -3.9 to 7.0%), 2000-2007 (APC=-4.2; 95% CI -6.4 to -2.0) and 2008-2014 (APC=3.1; 95% CI 0.8 to 5.5). Compared with 1995-1999, all specific maternal characteristics had a 10-15% increase in LBW risk in 2000-2006 and a 20-25% increase in 2007-2014, except among migrants, for which LBW risk remained lower than in 1995-1999 but increased after the crisis. The increasing LBW risk coincides with a deceleration in gross domestic product growth rate, reduction in health expenditure, social protection allocation on family/children support and sickness. The 2007-2008 global financial crisis was associated with a significant increase in LBW, particularly among infants of non-Portuguese mothers. We recommend strengthening social policies aimed at maternity protection for vulnerable mothers and health system maintenance of social equity in perinatal healthcare.
Clustering of financial time series with application to index and enhanced index tracking portfolio
Dose, Christian; Cincotti, Silvano
2005-09-01
A stochastic-optimization technique based on time series cluster analysis is described for index tracking and enhanced index tracking problems. Our methodology solves the problem in two steps, i.e., by first selecting a subset of stocks and then setting the weight of each stock as a result of an optimization process (asset allocation). Present formulation takes into account constraints on the number of stocks and on the fraction of capital invested in each of them, whilst not including transaction costs. Computational results based on clustering selection are compared to those of random techniques and show the importance of clustering in noise reduction and robust forecasting applications, in particular for enhanced index tracking.
Banks' Stability: The effect of Monetary Policies in the light of Global Financial Crisis
Directory of Open Access Journals (Sweden)
Wael Bakhit
2014-04-01
Full Text Available This paper employs a quarterly time series to determine the timing of structural breaks for interest rates in USA over the last 60 years. The Chow test is used for investigating the non-stationary, where the date of the potential break is assumed to be known. Moreover, an empirically examination of the financial sector to check if it is positively related to deviations from an assumed interest rate as given in a standard Taylor rule. The empirical analysis is strengthened by analysing the rule from a historical perspective and look at the effect of setting the interest rate by the central bank on financial imbalances. The empirical evidence indicates that deviation in monetary policy has a potential causal factor in the build up of financial imbalances and the subsequent crisis where macro prudential intervention could have beneficial effect. Thus, my findings tend to support the view which states that the probable existence of central banks has been one source of global financial crisis since the past decade.
International Nuclear Information System (INIS)
Winkler, R.; Wilhelm, J.
A detailed description is presented of calculating the nonstationary electron distribution function in a weakly ionized collision-dominated plasma from the Boltzmann kinetic equation respecting the effects of the time-dependent electric field, collision processes and the electron formation and loss. The finite difference approximation was used for numerical solution. Using the Crank-Nicolson method and parabolic interpolation between the grid points the Boltzmann equation was transformed to a system of linear equations which was then solved by iterations at a preset accuracy. Using the calculated distribution function values, the macroscopic plasma parameters were determined and the balance of electron density and energy checked in each time step. The mathematical procedure is illustrated using a neon plasma perturbed by a rectangular electric pulse. The time development shown of the distribution function at moments when the pulse was switched on and off demonstrates the great stability of the numerical solution. (J.U.)
Bush, Sarah B.; McGatha, Maggie B.; Bay-Williams, Jennifer M.
2012-01-01
The current state of the economy elevates the need to build awareness of financial markets and personal finance among the nation's young people through implementing a financial literacy curriculum in schools. A limited amount of time spent on financial literacy can have a positive effect on students' budgeting skills. This knowledge will only add…
Omi, Takahiro; Hirata, Yoshito; Aihara, Kazuyuki
2017-07-01
A Hawkes process model with a time-varying background rate is developed for analyzing the high-frequency financial data. In our model, the logarithm of the background rate is modeled by a linear model with a relatively large number of variable-width basis functions, and the parameters are estimated by a Bayesian method. Our model can capture not only the slow time variation, such as in the intraday seasonality, but also the rapid one, which follows a macroeconomic news announcement. By analyzing the tick data of the Nikkei 225 mini, we find that (i) our model is better fitted to the data than the Hawkes models with a constant background rate or a slowly varying background rate, which have been commonly used in the field of quantitative finance; (ii) the improvement in the goodness-of-fit to the data by our model is significant especially for sessions where considerable fluctuation of the background rate is present; and (iii) our model is statistically consistent with the data. The branching ratio, which quantifies the level of the endogeneity of markets, estimated by our model is 0.41, suggesting the relative importance of exogenous factors in the market dynamics. We also demonstrate that it is critically important to appropriately model the time-dependent background rate for the branching ratio estimation.
Omi, Takahiro; Hirata, Yoshito; Aihara, Kazuyuki
2017-07-01
A Hawkes process model with a time-varying background rate is developed for analyzing the high-frequency financial data. In our model, the logarithm of the background rate is modeled by a linear model with a relatively large number of variable-width basis functions, and the parameters are estimated by a Bayesian method. Our model can capture not only the slow time variation, such as in the intraday seasonality, but also the rapid one, which follows a macroeconomic news announcement. By analyzing the tick data of the Nikkei 225 mini, we find that (i) our model is better fitted to the data than the Hawkes models with a constant background rate or a slowly varying background rate, which have been commonly used in the field of quantitative finance; (ii) the improvement in the goodness-of-fit to the data by our model is significant especially for sessions where considerable fluctuation of the background rate is present; and (iii) our model is statistically consistent with the data. The branching ratio, which quantifies the level of the endogeneity of markets, estimated by our model is 0.41, suggesting the relative importance of exogenous factors in the market dynamics. We also demonstrate that it is critically important to appropriately model the time-dependent background rate for the branching ratio estimation.
Goldrick-Rab, Sara; Harris, Douglas N.; Benson, James
2011-01-01
The authors examine whether a need-based financial grant distribution "at random" to 1,500 Wisconsin Pell Grant recipients attending 13 public universities had an impact on how they allocated their time devoted to (a) working, (b) studying, (c) sleeping, and (d) socializing. To test whether time use mediates the relationship between aid…
Lane, Tyler J; Gray, Shannon; Hassani-Mahmooei, Behrooz; Collie, Alex
2018-01-05
Early intervention following occupational injury can improve health outcomes and reduce the duration and cost of workers' compensation claims. Financial early reporting incentives (ERIs) for employers may shorten the time between injury and access to compensation benefits and services. We examined ERI effect on time spent in the claim lodgement process in two Australian states: South Australia (SA), which introduced them in January 2009, and Tasmania (TAS), which introduced them in July 2010. Using administrative records of 1.47 million claims lodged between July 2006 and June 2012, we conducted an interrupted time series study of ERI impact on monthly median days in the claim lodgement process. Time periods included claim reporting, insurer decision, and total time. The 18-month gap in implementation between the states allowed for a multiple baseline design. In SA, we analysed periods within claim reporting: worker and employer reporting times (similar data were not available in TAS). To account for external threats to validity, we examined impact in reference to a comparator of other Australian workers' compensation jurisdictions. Total time in the process did not immediately change, though trend significantly decreased in both jurisdictions (SA: -0.36 days per month, 95% CI -0.63 to -0.09; TAS: 0.35, -0.50 to -0.20). Claim reporting time also decreased in both (SA: -1.6 days, -2.4 to -0.8; TAS: -5.4, -7.4 to -3.3). In TAS, there was a significant increase in insurer decision time (4.6, 3.9 to 5.4) and a similar but non-significant pattern in SA. In SA, worker reporting time significantly decreased (-4.7, -5.8 to -3.5), but employer reporting time did not (-0.3, -0.8 to 0.2). The results suggest that ERIs reduced claim lodgement time and, in the long-term, reduced total time in the claim lodgement process. However, only worker reporting time significantly decreased in SA, indicating that ERIs may not have shortened the process through the intended target of
Junor, Sean; Usher, Alex
2006-01-01
This paper describes a looming crisis in Canadian student financial assistance. It begins by summarizing the known evidence with respect to student financial assistance. It notes that many studies have emphasized the central importance of grants targeted to low-income students as a means to expand of access to post-secondary education, but that…
Cannon, A. J.
2009-12-01
Parameters in a Generalized Extreme Value (GEV) distribution are specified as a function of covariates using a conditional density network (CDN), which is a probabilistic extension of the multilayer perceptron neural network. If the covariate is time, or is dependent on time, then the GEV-CDN model can be used to perform nonlinear, nonstationary GEV analysis of hydrological or climatological time series. Due to the flexibility of the neural network architecture, the model is capable of representing a wide range of nonstationary relationships. Model parameters are estimated by generalized maximum likelihood, an approach that is tailored to the estimation of GEV parameters from geophysical time series. Model complexity is identified using the Bayesian information criterion and the Akaike information criterion with small sample size correction. Monte Carlo simulations are used to validate GEV-CDN performance on four simple synthetic problems. The model is then demonstrated on precipitation data from southern California, a series that exhibits nonstationarity due to interannual/interdecadal climatic variability. A hierarchy of models can be defined by adjusting three aspects of the GEV-CDN model architecture: (i) by specifying either a linear or a nonlinear hidden-layer activation function; (ii) by adjusting the number of hidden-layer nodes; or (iii) by disconnecting weights leading to output-layer nodes. To illustrate, five GEV-CDN models are shown here in order of increasing complexity for the case of a single covariate, which, in this case, is assumed to be time. The shape parameter is assumed to be constant in all models, although this is not a requirement of the GEV-CDN framework.
Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique
Directory of Open Access Journals (Sweden)
Daniel Maposa
2016-05-01
Full Text Available In this article we fit a time-dependent generalised extreme value (GEV distribution to annual maximum flood heights at three sites: Chokwe, Sicacate and Combomune in the lower Limpopo River basin of Mozambique. A GEV distribution is fitted to six annual maximum time series models at each site, namely: annual daily maximum (AM1, annual 2-day maximum (AM2, annual 5-day maximum (AM5, annual 7-day maximum (AM7, annual 10-day maximum (AM10 and annual 30-day maximum (AM30. Non-stationary time-dependent GEV models with a linear trend in location and scale parameters are considered in this study. The results show lack of sufficient evidence to indicate a linear trend in the location parameter at all three sites. On the other hand, the findings in this study reveal strong evidence of the existence of a linear trend in the scale parameter at Combomune and Sicacate, whilst the scale parameter had no significant linear trend at Chokwe. Further investigation in this study also reveals that the location parameter at Sicacate can be modelled by a nonlinear quadratic trend; however, the complexity of the overall model is not worthwhile in fit over a time-homogeneous model. This study shows the importance of extending the time-homogeneous GEV model to incorporate climate change factors such as trend in the lower Limpopo River basin, particularly in this era of global warming and a changing climate. Keywords: nonstationary extremes; annual maxima; lower Limpopo River; generalised extreme value
Autocalibration method for non-stationary CT bias correction.
Vegas-Sánchez-Ferrero, Gonzalo; Ledesma-Carbayo, Maria J; Washko, George R; Estépar, Raúl San José
2018-02-01
Computed tomography (CT) is a widely used imaging modality for screening and diagnosis. However, the deleterious effects of radiation exposure inherent in CT imaging require the development of image reconstruction methods which can reduce exposure levels. The development of iterative reconstruction techniques is now enabling the acquisition of low-dose CT images whose quality is comparable to that of CT images acquired with much higher radiation dosages. However, the characterization and calibration of the CT signal due to changes in dosage and reconstruction approaches is crucial to provide clinically relevant data. Although CT scanners are calibrated as part of the imaging workflow, the calibration is limited to select global reference values and does not consider other inherent factors of the acquisition that depend on the subject scanned (e.g. photon starvation, partial volume effect, beam hardening) and result in a non-stationary noise response. In this work, we analyze the effect of reconstruction biases caused by non-stationary noise and propose an autocalibration methodology to compensate it. Our contributions are: 1) the derivation of a functional relationship between observed bias and non-stationary noise, 2) a robust and accurate method to estimate the local variance, 3) an autocalibration methodology that does not necessarily rely on a calibration phantom, attenuates the bias caused by noise and removes the systematic bias observed in devices from different vendors. The validation of the proposed methodology was performed with a physical phantom and clinical CT scans acquired with different configurations (kernels, doses, algorithms including iterative reconstruction). The results confirmed the suitability of the proposed methods for removing the intra-device and inter-device reconstruction biases. Copyright © 2017 Elsevier B.V. All rights reserved.
Enhancement and Noise Statistics Estimation for Non-Stationary Voiced Speech
DEFF Research Database (Denmark)
Nørholm, Sidsel Marie; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2016-01-01
In this paper, single channel speech enhancement in the time domain is considered. We address the problem of modelling non-stationary speech by describing the voiced speech parts by a harmonic linear chirp model instead of using the traditional harmonic model. This means that the speech signal...... through simulations on synthetic and speech signals, that the chirp versions of the filters perform better than their harmonic counterparts in terms of output signal-to-noise ratio (SNR) and signal reduction factor. For synthetic signals, the output SNR for the harmonic chirp APES based filter...... is increased 3 dB compared to the harmonic APES based filter at an input SNR of 10 dB, and at the same time the signal reduction factor is decreased. For speech signals, the increase is 1.5 dB along with a decrease in the signal reduction factor of 0.7. As an implicit part of the APES filter, a noise...
Markov-switching model for nonstationary runoff conditioned on El Nino information
DEFF Research Database (Denmark)
Gelati, Emiliano; Madsen, H.; Rosbjerg, Dan
2010-01-01
We define a Markov-modulated autoregressive model with exogenous input (MARX) to generate runoff scenarios using climatic information. Runoff parameterization is assumed to be conditioned on a hidden climate state following a Markov chain, where state transition probabilities are functions...... of the climatic input. MARX allows stochastic modeling of nonstationary runoff, as runoff anomalies are described by a mixture of autoregressive models with exogenous input, each one corresponding to a climate state. We apply MARX to inflow time series of the Daule Peripa reservoir (Ecuador). El Nino Southern...... Oscillation (ENSO) information is used to condition runoff parameterization. Among the investigated ENSO indexes, the NINO 1+2 sea surface temperature anomalies and the trans-Nino index perform best as predictors. In the perspective of reservoir optimization at various time scales, MARX produces realistic...
Nonstationary modeling of a long record of rainfall and temperature over Rome
Villarini, Gabriele; Smith, James A.; Napolitano, Francesco
2010-10-01
A long record (1862-2004) of seasonal rainfall and temperature from the Rome observatory of Collegio Romano are modeled in a nonstationary framework by means of the Generalized Additive Models in Location, Scale and Shape (GAMLSS). Modeling analyses are used to characterize nonstationarities in rainfall and related climate variables. It is shown that the GAMLSS models are able to represent the magnitude and spread in the seasonal time series with parameters which are a smooth function of time. Covariate analyses highlight the role of seasonal and interannual variability of large-scale climate forcing, as reflected in three teleconnection indexes (Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and Mediterranean Index), for modeling seasonal rainfall and temperature over Rome. In particular, the North Atlantic Oscillation is a significant predictor during the winter, while the Mediterranean Index is a significant predictor for almost all seasons.
Mathematical modeling of non-stationary gas flow in gas pipeline
Fetisov, V. G.; Nikolaev, A. K.; Lykov, Y. V.; Duchnevich, L. N.
2018-03-01
An analysis of the operation of the gas transportation system shows that for a considerable part of time pipelines operate in an unsettled regime of gas movement. Its pressure and flow rate vary along the length of pipeline and over time as a result of uneven consumption and selection, switching on and off compressor units, shutting off stop valves, emergence of emergency leaks. The operational management of such regimes is associated with difficulty of reconciling the operating modes of individual sections of gas pipeline with each other, as well as with compressor stations. Determining the grounds that cause change in the operating mode of the pipeline system and revealing patterns of these changes determine the choice of its parameters. Therefore, knowledge of the laws of changing the main technological parameters of gas pumping through pipelines in conditions of non-stationary motion is of great importance for practice.
On a Nonstationary Route Problem with Constraints
Directory of Open Access Journals (Sweden)
A. G. Chentsov
2012-01-01
Full Text Available The extremal route problem of permutations under constraints in the form of preceding conditions is investigated. It is supposed that an executer leaves the initial point (the base after which he visits a system of megalopolises (finite goal sets and performs some work on each megalopolis. The cost functions for executor permutations and interior works depend on the “visiting moment” that can correspond to the real time or can also correspond to the natural regular succession (the first visiting, the second visiting, and so on. An economic variant of the widely interpreted dynamic programming method (DPM is constructed. On this basis an optimal computer realized algorithm is constructed. A variant of a greed algorithm is proposed.
Local polynomial Whittle estimation covering non-stationary fractional processes
DEFF Research Database (Denmark)
Nielsen, Frank
to the non-stationary region. By approximating the short-run component of the spectrum by a polynomial, instead of a constant, in a shrinking neighborhood of zero we alleviate some of the bias that the classical local Whittle estimators is prone to. This bias reduction comes at a cost as the variance is in...... study illustrates the performance of the proposed estimator compared to the classical local Whittle estimator and the local polynomial Whittle estimator. The empirical justi.cation of the proposed estimator is shown through an analysis of credit spreads....
Theoretical analysis of radiographic images by nonstationary Poisson processes
International Nuclear Information System (INIS)
Tanaka, Kazuo; Uchida, Suguru; Yamada, Isao.
1980-01-01
This paper deals with the noise analysis of radiographic images obtained in the usual fluorescent screen-film system. The theory of nonstationary Poisson processes is applied to the analysis of the radiographic images containing the object information. The ensemble averages, the autocorrelation functions, and the Wiener spectrum densities of the light-energy distribution at the fluorescent screen and of the film optical-density distribution are obtained. The detection characteristics of the system are evaluated theoretically. Numerical examples one-dimensional image are shown and the results are compared with those obtained under the assumption that the object image is related to the background noise by the additive process. (author)
Detrending of non-stationary noise data by spline techniques
International Nuclear Information System (INIS)
Behringer, K.
1989-11-01
An off-line method for detrending non-stationary noise data has been investigated. It uses a least squares spline approximation of the noise data with equally spaced breakpoints. Subtraction of the spline approximation from the noise signal at each data point gives a residual noise signal. The method acts as a high-pass filter with very sharp frequency cutoff. The cutoff frequency is determined by the breakpoint distance. The steepness of the cutoff is controlled by the spline order. (author) 12 figs., 1 tab., 5 refs
Nonstationary Heat Conduction in Atomic Systems
Singh, Amit K.
Understanding heat at the atomistic level is an interesting exercises. It is fascinating to note how the vibration of atoms result into thermodynamic concept of heat. This thesis aims to bring insights into different constitutive laws of heat conduction. We also develop a framework in which the interaction of thermostats to the system can be studied and a well known Kapitza effect can be reduced. The thesis also explores stochastic and continuum methods to model the latent heat release in the first order transition of ideal silicon surfaces into dimers. We divide the thesis into three works which are connected to each other: 1. Fourier's law leads to a diffusive model of heat transfer in which a thermal signal propagates infinitely fast and the only material parameter is the thermal conductivity. In micro- and nano-scale systems, non-Fourier effects involving coupled diffusion and wavelike propagation of heat can become important. An extension of Fourier's law to account for such effects leads to a Jeffreys-type model for heat transfer with two relaxation times. In this thesis, we first propose a new Thermal Parameter Identification (TPI) method for obtaining the Jeffreys-type thermal parameters from molecular dynamics simulations. The TPI method makes use of a nonlinear regression-based approach for obtaining the coefficients in analytical expressions for cosine and sine-weighted averages of temperature and heat flux over the length of the system. The method is applied to argon nanobeams over a range of temperature and system sizes. The results for thermal conductivity are found to be in good agreement with standard Green-Kubo and direct method calculations. The TPI method is more efficient for systems with high diffusivity and has the advantage, that unlike the direct method, it is free from the influence of thermostats. In addition, the method provides the thermal relaxation times for argon. Using the determined parameters, the Jeffreys-type model is able to
Forcing and variability of nonstationary rip currents
Long, Joseph W.; H.T. Özkan-Haller,
2016-01-01
Surface wave transformation and the resulting nearshore circulation along a section of coast with strong alongshore bathymetric gradients outside the surf zone are modeled for a consecutive 4 week time period. The modeled hydrodynamics are compared to in situ measurements of waves and currents collected during the Nearshore Canyon Experiment and indicate that for the entire range of observed conditions, the model performance is similar to other studies along this stretch of coast. Strong alongshore wave height gradients generate rip currents that are observed by remote sensing data and predicted qualitatively well by the numerical model. Previous studies at this site have used idealized scenarios to link the rip current locations to undulations in the offshore bathymetry but do not explain the dichotomy between permanent offshore bathymetric features and intermittent rip current development. Model results from the month‐long simulation are used to track the formation and location of rip currents using hourly statistics, and results show that the direction of the incoming wave energy strongly controls whether rip currents form. In particular, most of the offshore wave spectra were bimodal and we find that the ratio of energy contained in each mode dictates rip current development, and the alongshore rip current position is controlled by the incident wave period. Additionally, model simulations performed with and without updating the nearshore morphology yield no significant change in the accuracy of the predicted surf zone hydrodyanmics indicating that the large‐scale offshore features (e.g., submarine canyon) predominately control the nearshore wave‐circulation system.
Salomatov, V. V.; Puzyrev, E. M.; Salomatov, A. V.
2018-05-01
A class of nonlinear problems of nonstationary radiative-convective heat transfer under the microwave action with a small penetration depth is considered in a stabilized coolant flow in a circular channel. The solutions to these problems are obtained, using asymptotic procedures at the stages of nonstationary and stationary convective heat transfer on the heat-radiating channel surface. The nonstationary and stationary stages of the solution are matched, using the "longitudinal coordinate-time" characteristic. The approximate solutions constructed on such principles correlate reliably with the exact ones at the limiting values of the operation parameters, as well as with numerical and experimental data of other researchers. An important advantage of these solutions is that they allow the determination of the main regularities of the microwave and thermal radiation influence on convective heat transfer in a channel even before performing cumbersome calculations. It is shown that, irrespective of the heat exchange regime (nonstationary or stationary), the Nusselt number decreases and the rate of the surface temperature change increases with increase in the intensity of thermal action.
Guo, L.; Van der Wegen, M.; Jay, D.A.; Matte, P.; Wang, Z.B.; Roelvink, J.A.; He, Q.
2015-01-01
River-tide dynamics remain poorly understood, in part because conventional harmonic analysis (HA) does not cope effectively with nonstationary signals. To explore nonstationary behavior of river tides and the modulation effects of river discharge, this work analyzes tidal signals in the Yangtze
Flood frequency analysis of historical flood data under stationary and non-stationary modelling
Machado, M. J.; Botero, B. A.; López, J.; Francés, F.; Díez-Herrero, A.; Benito, G.
2015-06-01
Historical records are an important source of information on extreme and rare floods and fundamental to establish a reliable flood return frequency. The use of long historical records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 yr flood record from the Tagus River in Aranjuez (central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their contribution within hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations in flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation (NAO) index. Over the systematic gauge record (1913-2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators, and (b) a time-varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, which incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency
Jackson, Taylor J; Blumberg, Todd J; Shah, Apurva S; Sankar, Wudbhav N
2018-03-01
Musculoskeletal injuries are among the most common reasons for emergency department (ED) visits in the pediatric population. Many such injuries can be managed with a single follow-up outpatient visit. However, untimely (ie, premature) referrals by emergency physicians to orthopaedic surgeons are common and may inadvertently create need for a second visit, generating unnecessary expenditures. We sought to elucidate the cost of premature musculoskeletal follow-up visits to the patients, families, and the health care system. We performed a retrospective review of pediatric patients with acute musculoskeletal injuries referred from our ED (without a formal orthopaedic consult) to our outpatient clinic. Patients were retrospectively reviewed in a consecutive fashion. The appropriateness of the recommended follow-up time interval was determined for each patient, and the direct and indirect cost of the inappropriate services were calculated utilizing a combination of traditional cost accounting techniques and time-driven activity-based costing. The characteristics of patients with appropriate and untimely follow-up referrals were compared. Two hundred consecutive referrals from the ED were reviewed. Overall, 96.5% of the follow-up visits recommended by the ED were premature, which led 106 (53%) patients to require a second visit to complete their clinical care. Patients who required a second visit were significantly younger (P=0.005), more likely to be male (P=0.042), more likely to have a fracture (Pcost of $342.93 per patient. Untimely referrals for follow-up of acute pediatric musculoskeletal conditions are very common and represent a significant financial burden to patients, families, and the health care system. Over 40% of unnecessary visits resulted from just 3 diagnoses. Improved orthopaedic follow-up guidelines, particularly for these readily recognizable conditions, and feedback to referring providers may reduce poorly timed clinic visits and decrease costs in
Financial Ratios and Perceived Household Financial Satisfaction
Directory of Open Access Journals (Sweden)
Scott Garrett
2013-08-01
Full Text Available This paper tests the relative strength of three objective measures of financial health (using the solvency, liquidity, and investment asset ratio in predicting a household’s subjective feeling of current financial satisfaction. Using a sample of 6,923 respondents in the 2008 Health and Retirement Study this paper presents evidence of two main findings: 1 the solvency ratio is most strongly associated with financial satisfaction levels based on a cross-sectional design and 2 changes in the investment asset ratio are most strongly associated with changes in financial satisfaction over time.
Sampling design optimisation for rainfall prediction using a non-stationary geostatistical model
Wadoux, Alexandre M. J.-C.; Brus, Dick J.; Rico-Ramirez, Miguel A.; Heuvelink, Gerard B. M.
2017-09-01
The accuracy of spatial predictions of rainfall by merging rain-gauge and radar data is partly determined by the sampling design of the rain-gauge network. Optimising the locations of the rain-gauges may increase the accuracy of the predictions. Existing spatial sampling design optimisation methods are based on minimisation of the spatially averaged prediction error variance under the assumption of intrinsic stationarity. Over the past years, substantial progress has been made to deal with non-stationary spatial processes in kriging. Various well-documented geostatistical models relax the assumption of stationarity in the mean, while recent studies show the importance of considering non-stationarity in the variance for environmental processes occurring in complex landscapes. We optimised the sampling locations of rain-gauges using an extension of the Kriging with External Drift (KED) model for prediction of rainfall fields. The model incorporates both non-stationarity in the mean and in the variance, which are modelled as functions of external covariates such as radar imagery, distance to radar station and radar beam blockage. Spatial predictions are made repeatedly over time, each time recalibrating the model. The space-time averaged KED variance was minimised by Spatial Simulated Annealing (SSA). The methodology was tested using a case study predicting daily rainfall in the north of England for a one-year period. Results show that (i) the proposed non-stationary variance model outperforms the stationary variance model, and (ii) a small but significant decrease of the rainfall prediction error variance is obtained with the optimised rain-gauge network. In particular, it pays off to place rain-gauges at locations where the radar imagery is inaccurate, while keeping the distribution over the study area sufficiently uniform.
Flood frequency analysis for nonstationary annual peak records in an urban drainage basin
Villarini, G.; Smith, J.A.; Serinaldi, F.; Bales, J.; Bates, P.D.; Krajewski, W.F.
2009-01-01
Flood frequency analysis in urban watersheds is complicated by nonstationarities of annual peak records associated with land use change and evolving urban stormwater infrastructure. In this study, a framework for flood frequency analysis is developed based on the Generalized Additive Models for Location, Scale and Shape parameters (GAMLSS), a tool for modeling time series under nonstationary conditions. GAMLSS is applied to annual maximum peak discharge records for Little Sugar Creek, a highly urbanized watershed which drains the urban core of Charlotte, North Carolina. It is shown that GAMLSS is able to describe the variability in the mean and variance of the annual maximum peak discharge by modeling the parameters of the selected parametric distribution as a smooth function of time via cubic splines. Flood frequency analyses for Little Sugar Creek (at a drainage area of 110 km2) show that the maximum flow with a 0.01-annual probability (corresponding to 100-year flood peak under stationary conditions) over the 83-year record has ranged from a minimum unit discharge of 2.1 m3 s- 1 km- 2 to a maximum of 5.1 m3 s- 1 km- 2. An alternative characterization can be made by examining the estimated return interval of the peak discharge that would have an annual exceedance probability of 0.01 under the assumption of stationarity (3.2 m3 s- 1 km- 2). Under nonstationary conditions, alternative definitions of return period should be adapted. Under the GAMLSS model, the return interval of an annual peak discharge of 3.2 m3 s- 1 km- 2 ranges from a maximum value of more than 5000 years in 1957 to a minimum value of almost 8 years for the present time (2007). The GAMLSS framework is also used to examine the links between population trends and flood frequency, as well as trends in annual maximum rainfall. These analyses are used to examine evolving flood frequency over future decades. ?? 2009 Elsevier Ltd.
Flood frequency analysis for nonstationary annual peak records in an urban drainage basin
Villarini, Gabriele; Smith, James A.; Serinaldi, Francesco; Bales, Jerad; Bates, Paul D.; Krajewski, Witold F.
2009-08-01
Flood frequency analysis in urban watersheds is complicated by nonstationarities of annual peak records associated with land use change and evolving urban stormwater infrastructure. In this study, a framework for flood frequency analysis is developed based on the Generalized Additive Models for Location, Scale and Shape parameters (GAMLSS), a tool for modeling time series under nonstationary conditions. GAMLSS is applied to annual maximum peak discharge records for Little Sugar Creek, a highly urbanized watershed which drains the urban core of Charlotte, North Carolina. It is shown that GAMLSS is able to describe the variability in the mean and variance of the annual maximum peak discharge by modeling the parameters of the selected parametric distribution as a smooth function of time via cubic splines. Flood frequency analyses for Little Sugar Creek (at a drainage area of 110km) show that the maximum flow with a 0.01-annual probability (corresponding to 100-year flood peak under stationary conditions) over the 83-year record has ranged from a minimum unit discharge of 2.1mskm to a maximum of 5.1mskm. An alternative characterization can be made by examining the estimated return interval of the peak discharge that would have an annual exceedance probability of 0.01 under the assumption of stationarity (3.2mskm). Under nonstationary conditions, alternative definitions of return period should be adapted. Under the GAMLSS model, the return interval of an annual peak discharge of 3.2mskm ranges from a maximum value of more than 5000 years in 1957 to a minimum value of almost 8 years for the present time (2007). The GAMLSS framework is also used to examine the links between population trends and flood frequency, as well as trends in annual maximum rainfall. These analyses are used to examine evolving flood frequency over future decades.
Directory of Open Access Journals (Sweden)
Amanda Jane Succi
2012-02-01
At first this will involve the policy makers at the central level, like the Ministry of Education and Sciences and the main research actors in the public and in the private sector. The criteria of the geographical and the subjects coverage has been also used in order to be able to present a public institutions of the higher education and research but even the enterprises that act in the research area are mainly focusing to the integration of these two systems which have been working separately for a long period of time and that must become efficient in order to adapt to the conditions of a country that has limited financial resources. This article is intended to provide a comprehensive overview of the scientific research in Albania, focusing in defining the priority areas for the research in social sciences. The information about the higher education and the potential problems that it faces, is based on a big number of research institutions, selected based on their involvement in scientific research in social sciences. This article brings into evidence the fact that in order to establish a stable and effective infrastructure in scientific research in Albania, is important to work in different directions. A successful way to increase the efficasity through the elements of the “innovative system” is by working with organizations that work in specific sectors of the economy, aiming for a possible cooperation in scientific search, for an important social contribution.
Directory of Open Access Journals (Sweden)
Vladimir N. Vodyakov
2017-12-01
Full Text Available Introduction: Mathematical modeling allows assigning optimal parameters for the process of compression molding of plates and calculating the dimensions of the mold without costly and long-term experiments. The options ensure the required precision of pressing. The disadvantages of the known models are the assumptions about the process isothermicity and independence of the thermal-physical coefficients from temperature. The models do not take into account the dependence of the pressure in the cavity of the mold on the excess of the melt; the problem of calculating the dimensions of the mold cavity for given plate dimensions is not posed. The known models do not give a complete description of all stages of the process. The aim of this paper is to develop a perfect mathematical model without limitations for the compression molding of plates from a granulate of highly filled thermoplastic composites. Materials and Methods: The paper proposes a non-stationary mathematical model. The model takes into account the presence of physical states transitions and dependence of the thermophysical characteristics of composites on temperature. The model is based on the known equations of thermal physics and continuum mechanics. Results: Initial and boundary conditions, rheological equations, systems of equations for the material, thermal, and power balance are determined for three stages of the process. The calculation problems are determined too. A program of iterative numerical calculation has been developed because of the resulting system of equations has no analytical solution. A convergence of experimental and theoretical results with the correlation coefficient confirms the adequacy of the developed mathematical model and the calculation program. Discussion and Conclusions: The results of the study allow calculating the dimensions of the mold cavity, the initial granulate required mass, technological losses, the time functions of pressure and temperature
Instantaneous Purified Orbit: A New Tool for Analysis of Nonstationary Vibration of Rotor System
Directory of Open Access Journals (Sweden)
Shi Dongfeng
2001-01-01
Full Text Available In some circumstances, vibration signals of large rotating machinery possess time-varying characteristics to some extent. Traditional diagnosis methods, such as FFT spectrum and orbit diagram, are confronted with a huge challenge to deal with this problem. This work aims at studying the four intrinsic drawbacks of conventional vibration signal processing method and instantaneous purified orbit (IPO on the basis of improved Fourier spectrum (IFS to analyze nonstationary vibration. On account of integration, the benefits of short period Fourier transform (SPFT and regular holospectrum, this method can intuitively reflect vibration characteristics of’a rotor system by means of parameter analysis for corresponding frequency ellipses. Practical examples, such as transient vibration in run-up stages and bistable condition of rotor show that IPO is a powerful tool for diagnosis and analysis of the vibration behavior of rotor systems.
Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows
Gay-Balmaz, François; Holm, Darryl D.
2018-01-01
Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.
Unveiling non-stationary coupling between Amazon and ocean during recent extreme events
Ramos, Antônio M. de T.; Zou, Yong; de Oliveira, Gilvan Sampaio; Kurths, Jürgen; Macau, Elbert E. N.
2018-02-01
The interplay between extreme events in the Amazon's precipitation and the anomaly in the temperature of the surrounding oceans is not fully understood, especially its causal relations. In this paper, we investigate the climatic interaction between these regions from 1999 until 2012 using modern tools of complex system science. We identify the time scale of the coupling quantitatively and unveil the non-stationary influence of the ocean's temperature. The findings show consistently the distinctions between the coupling in the recent major extreme events in Amazonia, such as the two droughts that happened in 2005 and 2010 and the three floods during 1999, 2009 and 2012. Interestingly, the results also reveal the influence over the anomalous precipitation of Southwest Amazon has become increasingly lagged. The analysis can shed light on the underlying dynamics of the climate network system and consequently can improve predictions of extreme rainfall events.
Experimental data processing technique for nonstationary heat transfer on fuel rod simulators
International Nuclear Information System (INIS)
Nikonov, S.P.; Nikonov, A.P.; Belyukin, V.A.
1982-01-01
Non-stationary heat-transfer data processing is considered in connection with experimental studies of the emergency cooling whereat fuel rod imitators both with direct and indirect shell heating were used. The objective of data processing was obtaining the temperature distribution within the imitator, the heat flux removed by the coolant and the shell-coolant heat-transfer coefficient. The special attention was paid to the temperature distribution calculation at the data processing during the reflooding experiments. In this case two factors are assumed to be known: the time dependency of temperature variation at a certain point within the imitator cross-section and the heat flux at some point of the same cross-section. The initial data preparation for calculations, employing the procedure of smoothing by cubic spline functions, is considered as well, with application of an algorithm reported in the literature, which is efficient for the given functional dependency wherein the deviation in each point is known [ru
International Nuclear Information System (INIS)
Yu-Dong, Chen; Li, Li; Yi, Zhang; Jian-Ming, Hu
2009-01-01
In the study of complex networks (systems), the scaling phenomenon of flow fluctuations refers to a certain power-law between the mean flux (activity) (F i ) of the i-th node and its variance σ i as σ i α (F i ) α . Such scaling laws are found to be prevalent both in natural and man-made network systems, but the understanding of their origins still remains limited. This paper proposes a non-stationary Poisson process model to give an analytical explanation of the non-universal scaling phenomenon: the exponent α varies between 1/2 and 1 depending on the size of sampling time window and the relative strength of the external/internal driven forces of the systems. The crossover behaviour and the relation of fluctuation scaling with pseudo long range dependence are also accounted for by the model. Numerical experiments show that the proposed model can recover the multi-scaling phenomenon. (general)
A nonstationary Markov transition model for computing the relative risk of dementia before death
Yu, Lei; Griffith, William S.; Tyas, Suzanne L.; Snowdon, David A.; Kryscio, Richard J.
2010-01-01
This paper investigates the long-term behavior of the k-step transition probability matrix for a nonstationary discrete time Markov chain in the context of modeling transitions from intact cognition to dementia with mild cognitive impairment (MCI) and global impairment (GI) as intervening cognitive states. The authors derive formulas for the following absorption statistics: (1) the relative risk of absorption between competing absorbing states, and (2) the mean and variance of the number of visits among the transient states before absorption. Since absorption is not guaranteed, sufficient conditions are discussed to ensure that the substochastic matrix associated with transitions among transient states converges to zero in limit. Results are illustrated with an application to the Nun Study, a cohort of 678 participants, 75 to 107 years of age, followed longitudinally with up to ten cognitive assessments over a fifteen-year period. PMID:20087848
Robust suppression of nonstationary power-line interference in electrocardiogram signals
International Nuclear Information System (INIS)
Li, Guojun; Zeng, Xiaopin; Zhou, Yu; Liu, Guojin; Zhou, Xichuan; Zhou, Xiaona
2012-01-01
It is a challenge to suppress time-varying power-line interference (PLI) with various levels in electrocardiogram (ECG) signals. Most previous attempts of tracking and suppressing the nonstationary PLI signal are based on the least-squares (LS) algorithm. This makes these methods susceptible to QRS complex in suppressing a low-level PLI signal which is frequently coupled in battery-operated ECG equipment. To address the limitation of LS-based methods, this study presents a robust PLI suppression system based on a robust extension of the Kalman filter. In addition, we used an improved version of empirical mode decomposition to further attenuate the QRS complex. Experiments show that our system could effectively suppress the PLI while preserving meaningful ECG components at various interference levels. (paper)
Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows
Gay-Balmaz, François; Holm, Darryl D.
2018-06-01
Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.
Is the Labour Force Participation Rate Non-Stationary in Romania?
Directory of Open Access Journals (Sweden)
Tiwari Aviral Kumar
2015-01-01
Full Text Available The purpose of this paper is to test hysteresis of the Romanian labour force participation rate, by using time series data, with quarterly frequency, covering the period 1999Q1-2013Q4. The main results reveal that the Romanian labour force participation rate is a nonlinear process and has a partial unit root (i.e. it is stationary in the first regime and non-stationary in the second one, the main breaking point being registered around year 2005. In this context, the value of using unemployment rate as an indicator for capturing joblessness in this country is debatable. Starting from 2005, the participation rate has not followed long-term changes in unemployment rate, the disturbances having permanent effects on labour force participation rate.
Project Lifespan-based Nonstationary Hydrologic Design Methods for Changing Environment
Xiong, L.
2017-12-01
Under changing environment, we must associate design floods with the design life period of projects to ensure the hydrologic design is really relevant to the operation of the hydrologic projects, because the design value for a given exceedance probability over the project life period would be significantly different from that over other time periods of the same length due to the nonstationarity of probability distributions. Several hydrologic design methods that take the design life period of projects into account have been proposed in recent years, i.e. the expected number of exceedances (ENE), design life level (DLL), equivalent reliability (ER), and average design life level (ADLL). Among the four methods to be compared, both the ENE and ER methods are return period-based methods, while DLL and ADLL are risk/reliability- based methods which estimate design values for given probability values of risk or reliability. However, the four methods can be unified together under a general framework through a relationship transforming the so-called representative reliability (RRE) into the return period, i.e. m=1/1(1-RRE), in which we compute the return period m using the representative reliability RRE.The results of nonstationary design quantiles and associated confidence intervals calculated by ENE, ER and ADLL were very similar, since ENE or ER was a special case or had a similar expression form with respect to ADLL. In particular, the design quantiles calculated by ENE and ADLL were the same when return period was equal to the length of the design life. In addition, DLL can yield similar design values if the relationship between DLL and ER/ADLL return periods is considered. Furthermore, ENE, ER and ADLL had good adaptability to either an increasing or decreasing situation, yielding not too large or too small design quantiles. This is important for applications of nonstationary hydrologic design methods in actual practice because of the concern of choosing the emerging
Steiner-Khamsi, Gita; Appleton, Margaret; Vellani, Shezleen
2018-01-01
The media analysis is situated in the larger body of studies that explore the varied reasons why different policy actors advocate for international large-scale student assessments (ILSAs) and adds to the research on the fast advance of the global education industry. The analysis of "The Economist," "Financial Times," and…
Aber, J. Lawrence; Morris, Pamela; Wolf, Sharon; Berg, Juliette
2016-01-01
This article examines the impacts of Opportunity New York City-Family Rewards, the first holistic conditional cash transfer (CCT) program evaluated in the United States, on parental financial investments in children, and high school students' academic time use, motivations and self-beliefs, and achievement outcomes. Family Rewards, launched by the…
DiMasi, Joseph A; Smith, Zachary; Getz, Kenneth A
2018-05-10
The extent to which new drug developers can benefit financially from shorter development times has implications for development efficiency and innovation incentives. We provided a real-world example of such gains by using recent estimates of drug development costs and returns. Time and fee data were obtained on 5 single-source manufacturing projects. Time and fees were modeled for these projects as if the drug substance and drug product processes had been contracted separately from 2 vendors. The multi-vendor model was taken as the base case, and financial impacts from single-source contracting were determined relative to the base case. The mean and median after-tax financial benefits of shorter development times from single-source contracting were $44.7 million and $34.9 million, respectively (2016 dollars). The after-tax increases in sponsor fees from single-source contracting were small in comparison (mean and median of $0.65 million and $0.25 million). For the data we examined, single-source contracting yielded substantial financial benefits over multi-source contracting, even after accounting for somewhat higher sponsor fees. Copyright © 2018 Elsevier HS Journals, Inc. All rights reserved.
Rink, Floor; Ryan, Michelle K; Stoker, Janka I
2012-01-01
In two scenario-based studies, we found that women and men evaluate glass-cliff positions (i.e., precarious leadership positions at organizations in crisis) differently depending on the social and financial resources available. Female and male participants evaluated a hypothetical leadership position in which they would have both social and financial resources, financial resources but no social resources, or social resources but no financial resources. Women evaluated the position without social resources most negatively, whereas men evaluated the position without financial resources most negatively. In study 2, we found that women and men considered different issues when evaluating these leadership positions. Women's evaluations and expected levels of influence as leaders depended on the degree to which they expected to be accepted by subordinates. In contrast, men's evaluations and expected levels of acceptance by subordinates depended on the degree to which they expected to be influential in the position. Our findings have implications for the understanding of the glass-cliff phenomenon and gendered leadership stereotypes.
Sextos, Anastasios G.
2014-01-01
timely during economic recession, where the academic priorities are rapidly changing. In the light of this unfavourable and unstable financial environment, a critical overview of the strengths, the weaknesses, the opportunities and the threats of this effort is presented herein, hopefully contributing to the discussion on the future of higher education in the time of crisis.
Directory of Open Access Journals (Sweden)
Porshnev Sergey
2017-01-01
Full Text Available This work devoted to researching of mathematical model of non-stationary queuing system (NQS. Arrival rate in studied NQS λ(t is similar to rate which observed in practice in a real access control system of objects of mass events. Dependence of number of serviced requests from time was calculated. It is proven that the ratio value of served requests at the beginning of event to all served requests described by a deterministic function, depending on the average service rate μ¯$\\bar \\mu $ and the maximum value of the arrival rate function λ(t.
Enhancement of Non-Stationary Speech using Harmonic Chirp Filters
DEFF Research Database (Denmark)
Nørholm, Sidsel Marie; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2015-01-01
In this paper, the issue of single channel speech enhancement of non-stationary voiced speech is addressed. The non-stationarity of speech is well known, but state of the art speech enhancement methods assume stationarity within frames of 20–30 ms. We derive optimal distortionless filters that take...... the non-stationarity nature of voiced speech into account via linear constraints. This is facilitated by imposing a harmonic chirp model on the speech signal. As an implicit part of the filter design, the noise statistics are also estimated based on the observed signal and parameters of the harmonic chirp...... model. Simulations on real speech show that the chirp based filters perform better than their harmonic counterparts. Further, it is seen that the gain of using the chirp model increases when the estimated chirp parameter is big corresponding to periods in the signal where the instantaneous fundamental...
Likelihood inference for a nonstationary fractional autoregressive model
DEFF Research Database (Denmark)
Johansen, Søren; Ørregård Nielsen, Morten
2010-01-01
This paper discusses model-based inference in an autoregressive model for fractional processes which allows the process to be fractional of order d or d-b. Fractional differencing involves infinitely many past values and because we are interested in nonstationary processes we model the data X1......,...,X_{T} given the initial values X_{-n}, n=0,1,..., as is usually done. The initial values are not modeled but assumed to be bounded. This represents a considerable generalization relative to all previous work where it is assumed that initial values are zero. For the statistical analysis we assume...... the conditional Gaussian likelihood and for the probability analysis we also condition on initial values but assume that the errors in the autoregressive model are i.i.d. with suitable moment conditions. We analyze the conditional likelihood and its derivatives as stochastic processes in the parameters, including...
Nonstationary Transient Vibroacoustic Response of a Beam Structure
Caimi, R. E.; Margasahayam, R. N.; Nayfeh, Jamal F.
1997-01-01
This study consists of an investigation into the nonstationary transient response of the Verification Test Article (VETA) when subjected to random acoustic excitation. The goal is to assess excitation models that can be used in the design of structures and equipment when knowledge of the structure and the excitation is limited. The VETA is an instrumented cantilever beam that was exposed to acoustic loading during five Space Shuttle launches. The VETA analytical structural model response is estimated using the direct averaged power spectral density and the normalized pressure spectra methods. The estimated responses are compared to the measured response of the VETA. These comparisons are discussed with a focus on prediction conservatism and current design practice.
Martingales, nonstationary increments, and the efficient market hypothesis
McCauley, Joseph L.; Bassler, Kevin E.; Gunaratne, Gemunu H.
2008-06-01
We discuss the deep connection between nonstationary increments, martingales, and the efficient market hypothesis for stochastic processes x(t) with arbitrary diffusion coefficients D(x,t). We explain why a test for a martingale is generally a test for uncorrelated increments. We explain why martingales look Markovian at the level of both simple averages and 2-point correlations. But while a Markovian market has no memory to exploit and cannot be beaten systematically, a martingale admits memory that might be exploitable in higher order correlations. We also use the analysis of this paper to correct a misstatement of the ‘fair game’ condition in terms of serial correlations in Fama’s paper on the EMH. We emphasize that the use of the log increment as a variable in data analysis generates spurious fat tails and spurious Hurst exponents.
Gravitational entropy of nonstationary black holes and spherical shells
International Nuclear Information System (INIS)
Hiscock, W.A.
1989-01-01
The problem of defining the gravitational entropy of a nonstationary black hole is considered in a simple model consisting of a spherical shell which collapses into a preexisting black hole. The second law of black-hole mechanics strongly suggests identifying one-quarter of the area of the event horizon as the gravitational entropy of the system. It is, however, impossible to accurately locate the position of the global event horizon using only local measurements. In order to maintain a local thermodynamics, it is suggested that the entropy of the black hole be identified with one-quarter the area of the apparent horizon. The difference between the event-horizon entropy (to the extent it can be determined) and the apparent-horizon entropy may then be interpreted as the gravitational entropy of the collapsing shell. The total (event-horizon) gravitational entropy evolves in a smooth (C 0 ) fashion, even in the presence of δ-functional shells of matter
Simulation of nonstationary phenomena in atmospheric-pressure glow discharge
Korolev, Yu. D.; Frants, O. B.; Nekhoroshev, V. O.; Suslov, A. I.; Kas'yanov, V. S.; Shemyakin, I. A.; Bolotov, A. V.
2016-06-01
Nonstationary processes in atmospheric-pressure glow discharge manifest themselves in spontaneous transitions from the normal glow discharge into a spark. In the experiments, both so-called completed transitions in which a highly conductive constricted channel arises and incomplete transitions accompanied by the formation of a diffuse channel are observed. A model of the positive column of a discharge in air is elaborated that allows one to interpret specific features of the discharge both in the stationary stage and during its transition into a spark and makes it possible to calculate the characteristic oscillatory current waveforms for completed transitions into a spark and aperiodic ones for incomplete transitions. The calculated parameters of the positive column in the glow discharge mode agree well with experiment. Data on the densities of the most abundant species generated in the discharge (such as atomic oxygen, metastable nitrogen molecules, ozone, nitrogen oxides, and negative oxygen ions) are presented.
Simulation of nonstationary phenomena in atmospheric-pressure glow discharge
International Nuclear Information System (INIS)
Korolev, Yu. D.; Frants, O. B.; Nekhoroshev, V. O.; Suslov, A. I.; Kas’yanov, V. S.; Shemyakin, I. A.; Bolotov, A. V.
2016-01-01
Nonstationary processes in atmospheric-pressure glow discharge manifest themselves in spontaneous transitions from the normal glow discharge into a spark. In the experiments, both so-called completed transitions in which a highly conductive constricted channel arises and incomplete transitions accompanied by the formation of a diffuse channel are observed. A model of the positive column of a discharge in air is elaborated that allows one to interpret specific features of the discharge both in the stationary stage and during its transition into a spark and makes it possible to calculate the characteristic oscillatory current waveforms for completed transitions into a spark and aperiodic ones for incomplete transitions. The calculated parameters of the positive column in the glow discharge mode agree well with experiment. Data on the densities of the most abundant species generated in the discharge (such as atomic oxygen, metastable nitrogen molecules, ozone, nitrogen oxides, and negative oxygen ions) are presented.
Non-stationary vibrations of a thin viscoelastic orthotropic beam
Czech Academy of Sciences Publication Activity Database
Adámek, V.; Valeš, František; Tikal, B.
2009-01-01
Roč. 71, č. 12 (2009), e2569-e2576 ISSN 0362-546X R&D Projects: GA ČR(CZ) GA101/07/0946 Institutional research plan: CEZ:AV0Z20760514 Keywords : thin beam * non-stationary vibration * analytical solution Subject RIV: BI - Acoustics Impact factor: 1.487, year: 2009 http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V0Y-4WB3N8S-4&_user=640952&_rdoc=1&_fmt=&_orig=search&_sort=d&_docanchor=&view=c&_searchStrId=1156243286&_rerunOrigin= google &_acct=C000034318&_version=1&_urlVersion=0&_userid=640952&md5=ce096901a3382058455e822a20645820
Directory of Open Access Journals (Sweden)
Igor Masten
2011-12-01
Full Text Available
Times New Roman', serif;">This paper provides an empirical analysis of the role of financial development and financial integration in the growth dynamics of transition countries. We focus on the role of financial integration in determining the impact of financial development on growth, distinguishing “normal times” from periods of financial crises. In addition to confirming the significant positive effect on growth exerted by financial development and financial integration, our estimates show that a higher degree of financial openness tends to reduce the contractionary effect of financial crises, by cushioning the effect on the domestic supply of credit. Consequently, the high reliance on international capital flows by transition countries does not necessarily increase their financial fragility. This implies that financial protectionism is a self-defeating policy, at least for transition countries.
Directory of Open Access Journals (Sweden)
Aileen Timmons
Full Text Available Although cancer patients may incur a wide range of cancer-related out-of-pocket costs and experience reduced income, the consequences of this financial burden are poorly understood. We investigated: financial adjustments needed to cope with the cancer-related financial burden; financial distress (defined as a reaction to the state of personal finances; and factors that increase risk of financial difficulties. Two sets of semi-structured face-to-face interviews were conducted with 20 patients with breast, lung and prostate cancer and 21 hospital-based oncology social workers (OSWs in Ireland, which has a mixed public-private healthcare system. Participants were asked about: strategies to cope with the cancer-related financial burden; the impact of the financial burden on the family budget, other aspects of daily life, and wellbeing. OSWs were also asked about patient groups they thought were more likely to experience financial difficulties. The two interview sets were analysed separately using a thematic approach. Financial adjustments included: using savings; borrowing money; relying on family and friends for direct and indirect financial help; and cutting back on household spending. Financial distress was common. Financial difficulties were more likely for patients who were older or younger, working at diagnosis, lacked social support, had dependent children, had low income or had few savings. These issues often interacted with one another. As has been seen in predominantly publically and predominantly privately-funded healthcare settings, a complex mixed public-private healthcare system does not always provide adequate financial protection post-cancer. Our findings highlight the need for a broader set of metrics to measure the financial impact of cancer (and to assess financial protection in health more generally; these should include: out-of-pocket direct medical and non-medical costs; changes in income; financial adjustments (including
Timmons, Aileen; Gooberman-Hill, Rachael; Sharp, Linda
2013-01-01
Although cancer patients may incur a wide range of cancer-related out-of-pocket costs and experience reduced income, the consequences of this financial burden are poorly understood. We investigated: financial adjustments needed to cope with the cancer-related financial burden; financial distress (defined as a reaction to the state of personal finances); and factors that increase risk of financial difficulties. Two sets of semi-structured face-to-face interviews were conducted with 20 patients with breast, lung and prostate cancer and 21 hospital-based oncology social workers (OSWs) in Ireland, which has a mixed public-private healthcare system. Participants were asked about: strategies to cope with the cancer-related financial burden; the impact of the financial burden on the family budget, other aspects of daily life, and wellbeing. OSWs were also asked about patient groups they thought were more likely to experience financial difficulties. The two interview sets were analysed separately using a thematic approach. Financial adjustments included: using savings; borrowing money; relying on family and friends for direct and indirect financial help; and cutting back on household spending. Financial distress was common. Financial difficulties were more likely for patients who were older or younger, working at diagnosis, lacked social support, had dependent children, had low income or had few savings. These issues often interacted with one another. As has been seen in predominantly publically and predominantly privately-funded healthcare settings, a complex mixed public-private healthcare system does not always provide adequate financial protection post-cancer. Our findings highlight the need for a broader set of metrics to measure the financial impact of cancer (and to assess financial protection in health more generally); these should include: out-of-pocket direct medical and non-medical costs; changes in income; financial adjustments (including financial coping
Rink, Floor; Ryan, Michelle K.; Stoker, Janka I.
2012-01-01
In two scenario-based studies, we found that women and men evaluate glass-cliff positions (i.e., precarious leadership positions at organizations in crisis) differently depending on the social and financial resources available. Female and male participants evaluated a hypothetical leadership
Rink, Floor; Ryan, Michelle K.; Stoker, Janka I.
In two scenario-based studies, we found that women and men evaluate glass-cliff positions (i.e., precarious leadership positions at organizations in crisis) differently depending on the social and financial resources available. Female and male participants evaluated a hypothetical leadership
Noback, Inge; Broersma, Lourens; Van Dijk, Jouke
2013-01-01
The aim of this study is to gain insight into the gender-specific career advancement of about 10,000 middle- and top-level managers in a Dutch financial services company. Our results indicate that women earn less, work at lower job levels, but show slightly higher career mobility than men. However,
F. Gerard Adams
2009-01-01
The world financial crisis of 2008 is a consequence of new financial technologies, new accounting methods and new international linkages. These developments have come at a time when governments have returned to an old-fashioned freemarket philosophy. This paper links the systemic financial/economic crisis of 2008 to the new economy developments, globalisation and policy philosophy perspectives of recent decades. It raises the question of how to re-establish confidence once traditional thinkin...
Song, Paula H; Smith, Dean G; Wheeler, John R C
2008-01-01
Not-for-profit (NFP) hospitals' accumulations of financial assets have been growing steadily over the past 10 years. Surprisingly, little is known about how much investment reserves represent and how they are handled among NFP hospitals. The purpose of this study is to evaluate investment strategies in financial assets among NFP hospitals. Specifically, this article seeks to explore how NFP hospitals allocate and manage financial assets, how much risk hospitals employ in their investment strategies, and the risk and return trade-off under contrasting market conditions. Using two years of survey data from the Common fund Benchmarks Study for Health Care Institutions for fiscal years 2002 and 2003, we analyze NFP hospitals' investment strategies by comparing asset size, investment management characteristics, board characteristics, asset allocation, levels of risk, and annual returns. Univariate regression analysis is used to evaluate the relationship between risk and return. NFP hospitals have sizeable long-term financial assets, averaging over $558 million in 2002 and $634 million in 2003. Two thirds of these funds are invested in long-term operating funds followed by defined benefit pension funds and insurance reserves; management of these funds is primarily outsourced. NFP hospitals allocate, on average, 50% of their operating fund assets to equities. During the stock market downturn in 2002, each 1% investment in equities was significantly associated with a -0.18% decrease in annual returns. In contrast, the relationship is almost exactly opposite--consistent with the relationship typically associated with risk and return--in 2003. NFP hospitals with heavy reliance on investment income to boost total profit margins may have difficulty adjusting to periods of low performance. Evaluation of the performance and financial condition of the hospital must account for the size and composition of financial assets.
Directory of Open Access Journals (Sweden)
V. K. Bityukov
2016-01-01
Full Text Available Analytical study of the processes of heat conduction is one of the main topics of modern engineering research in engineering, energy, nuclear industry, process chemical, construction, textile, food, geological and other industries. Suffice to say that almost all processes in one degree or another are related to change in the temperature condition and the transfer of warmth. It should also be noted that engineering studies of the kinetics of a range of physical and chemical processes are similar to the problems of stationary and nonstationary heat transfer. These include the processes of diffusions, sedimentation, viscous flow, slowing down the neutrons, flow of fluids through a porous medium, electric fluctuations, adsorption, drying, burning, etc. There are various methods for solving the classical boundary value problems of nonstationary heat conduction and problems of the generalized type: the method of separation of variables (Fourier method method; the continuation method; the works solutions; the Duhamel's method; the integral transformations method; the operating method; the method of green's functions (stationary and non-stationary thermal conductivity; the reflection method (method source. In this paper, based on the consistent application of the Laplace transform on the dimensionless time θ and finite sine integral transformation in the spatial coordinates X and Y solves the problem of unsteady temperature distribution on the mechanism of heat conduction in a parallelepiped with boundary conditions of first kind. As a result we have the analytical solution of the temperature distribution in the parallelepiped to a conductive mode free convection, when one of the side faces of the parallelepiped is maintained at a constant temperature, and the others with the another same constant temperature.
International Development Research Centre (IDRC) Digital Library (Canada)
Financial Statements and accompanying notes provided on .... to good governance principles. there is the risk that ...... responsibilities of the centre's internal auditor includes reviewing internal controls, including accounting and financial.
Classification of risks in the process of financial planning
Directory of Open Access Journals (Sweden)
A.V. Overchuk
2017-12-01
Full Text Available The essence of the concept «risk» in the process of financial planning is studied. The classification of risks was conducted. The article provides the full enough and detailed system of classification of risks in the process of financial planning. The author researches and provides the factors, which directly influence upon the size of risks, which accompany the process of financial planning. A complete set of isolated independent features was determined for each risk type. It was found out that a part of features depends only on the risk type and the other part is determined by the character of a risky situation. The article substantiates the presence of indeterminacy typical for dynamic and non-stationary environment and the risks of different nature and strength of influence on the efficiency of financial planning, which cause the necessity to develop and implement the effective system of financial planning at an enterprise.
Janečková, Alena
2011-01-01
1 Abstract/ Financial derivatives The purpose of this thesis is to provide an introduction to financial derivatives which has been, from the legal perspective, described in a not satisfactory manner as quite little literature that can be found about this topic. The main objectives of this thesis are to define the term "financial derivatives" and its particular types and to analyse legal nature of these financial instruments. The last objective is to try to draft future law regulation of finan...
DEFF Research Database (Denmark)
Harrod, Steven; Kelton, W. David
2006-01-01
Nonstationary Poisson processes are appropriate in many applications, including disease studies, transportation, finance, and social policy. The authors review the risks of ignoring nonstationarity in Poisson processes and demonstrate three algorithms for generation of Poisson processes...
DEFF Research Database (Denmark)
Kock, Anders Bredahl
2016-01-01
We show that the adaptive Lasso is oracle efficient in stationary and nonstationary autoregressions. This means that it estimates parameters consistently, selects the correct sparsity pattern, and estimates the coefficients belonging to the relevant variables at the same asymptotic efficiency...
Approximate calculation method for integral of mean square value of nonstationary response
International Nuclear Information System (INIS)
Aoki, Shigeru; Fukano, Azusa
2010-01-01
The response of the structure subjected to nonstationary random vibration such as earthquake excitation is nonstationary random vibration. Calculating method for statistical characteristics of such a response is complicated. Mean square value of the response is usually used to evaluate random response. Integral of mean square value of the response corresponds to total energy of the response. In this paper, a simplified calculation method to obtain integral of mean square value of the response is proposed. As input excitation, nonstationary white noise and nonstationary filtered white noise are used. Integrals of mean square value of the response are calculated for various values of parameters. It is found that the proposed method gives exact value of integral of mean square value of the response.
International Nuclear Information System (INIS)
Ricour, Olivia; Marguier, Marina; Lartigau, Thierry
2013-01-01
The mission of RTE, the French electricity Transportation grid, a public service assignment, is to balance the electricity supply and demand in real time. This report presents RTE's financial results for 2012: increase of investments for services to clients, performance results, financial balance, stability of the economical model. RTE's regulated economical model, main financial indicators, 2007-2012 investments, 2012 investments by category, 2012 turnover, 2012 costs structure, taxes, financial balance sheet at the end of 2012, and the share of electricity transport in the electricity price are presented in appendixes
O'Hare, Bernadette; Makuta, Innocent; Bar-Zeev, Naor; Chiwaula, Levison; Cobham, Alex
2014-04-01
This paper sets out to estimate the cost of illicit financial flows (IFF) in terms of the amount of time it could take to reach the fourth Millennium Development Goal (MDG) in 34 African countries. We have calculated the percentage increase in gross domestic product (GDP) if IFFs were curtailed using IFF/GDP ratios. We applied the income (GDP) elasticity of child mortality to the increase in GDP to estimate the reduction in time to reach the fourth MDG in 34 African countries. children aged under five years. 34 countries in SSA. Reduction in time to reach the first indicator of the fourth MDG, under-five mortality rate in the absence of IFF. We found that in the 34 SSA countries, six countries will achieve their fourth MDG target at the current rates of decline. In the absence of IFF, 16 countries would reach their fourth MDG target by 2015 and there would be large reductions for all other countries. This drain on development is facilitated by financial secrecy in other jurisdictions. Rich and poor countries alike must stem the haemorrhage of IFF by taking decisive steps towards improving financial transparency.
Makuta, Innocent; Bar-Zeev, Naor; Chiwaula, Levison; Cobham, Alex
2014-01-01
Objectives This paper sets out to estimate the cost of illicit financial flows (IFF) in terms of the amount of time it could take to reach the fourth Millennium Development Goal (MDG) in 34 African countries. Design We have calculated the percentage increase in gross domestic product (GDP) if IFFs were curtailed using IFF/GDP ratios. We applied the income (GDP) elasticity of child mortality to the increase in GDP to estimate the reduction in time to reach the fourth MDG in 34 African countries. Participants children aged under five years. Settings 34 countries in SSA. Main outcome measures Reduction in time to reach the first indicator of the fourth MDG, under-five mortality rate in the absence of IFF. Results We found that in the 34 SSA countries, six countries will achieve their fourth MDG target at the current rates of decline. In the absence of IFF, 16 countries would reach their fourth MDG target by 2015 and there would be large reductions for all other countries. Conclusions This drain on development is facilitated by financial secrecy in other jurisdictions. Rich and poor countries alike must stem the haemorrhage of IFF by taking decisive steps towards improving financial transparency. PMID:24334911
Casarin, Roberto; Squazzoni, Flaminio
2013-01-01
This paper looks at the relationship between negative news and stock markets in times of global crisis, such as the 2008/2009 period. We analysed one year of front page banner headlines of three financial newspapers, the Wall Street Journal, Financial Times, and Il Sole24ore to examine the influence of bad news both on stock market volatility and dynamic correlation. Our results show that the press and markets influenced each other in generating market volatility and in particular, that the Wall Street Journal had a crucial effect both on the volatility and correlation between the US and foreign markets. We also found significant differences between newspapers in their interpretation of the crisis, with the Financial Times being significantly pessimistic even in phases of low market volatility. Our results confirm the reflexive nature of stock markets. When the situation is uncertain and unpredictable, market behaviour may even reflect qualitative, big picture, and subjective information such as streamers in a newspaper, whose economic and informative value is questionable. PMID:23861791
Directory of Open Access Journals (Sweden)
Roberto Casarin
Full Text Available This paper looks at the relationship between negative news and stock markets in times of global crisis, such as the 2008/2009 period. We analysed one year of front page banner headlines of three financial newspapers, the Wall Street Journal, Financial Times, and Il Sole24ore to examine the influence of bad news both on stock market volatility and dynamic correlation. Our results show that the press and markets influenced each other in generating market volatility and in particular, that the Wall Street Journal had a crucial effect both on the volatility and correlation between the US and foreign markets. We also found significant differences between newspapers in their interpretation of the crisis, with the Financial Times being significantly pessimistic even in phases of low market volatility. Our results confirm the reflexive nature of stock markets. When the situation is uncertain and unpredictable, market behaviour may even reflect qualitative, big picture, and subjective information such as streamers in a newspaper, whose economic and informative value is questionable.
Directory of Open Access Journals (Sweden)
Orlov Alexey
2016-01-01
Full Text Available This article presents results of development of the mathematical model of nonstationary separation processes occurring in gas centrifuge cascades for separation of multicomponent isotope mixtures. This model was used for the calculation parameters of gas centrifuge cascade for separation of germanium isotopes. Comparison of obtained values with results of other authors revealed that developed mathematical model is adequate to describe nonstationary separation processes in gas centrifuge cascades for separation of multicomponent isotope mixtures.
Orlov Alexey; Ushakov Anton; Sovach Victor
2016-01-01
This article presents results of development of the mathematical model of nonstationary separation processes occurring in gas centrifuge cascades for separation of multicomponent isotope mixtures. This model was used for the calculation parameters of gas centrifuge cascade for separation of germanium isotopes. Comparison of obtained values with results of other authors revealed that developed mathematical model is adequate to describe nonstationary separation processes in gas centrifuge casca...
Orlov, Aleksey Alekseevich; Ushakov, Anton; Sovach, Victor
2017-01-01
The article presents results of development of a mathematical model of nonstationary hydraulic processes in gas centrifuge cascade for separation of multicomponent isotope mixtures. This model was used for the calculation parameters of gas centrifuge cascade for separation of silicon isotopes. Comparison of obtained values with results of other authors revealed that developed mathematical model is adequate to describe nonstationary hydraulic processes in gas centrifuge cascades for separation...
International Nuclear Information System (INIS)
Morel, Romain; Cochran, Ian; Zou, Sani; Spencer, Thomas
2015-05-01
In light of the transition to a low-carbon, climate-resilient growth model, fiscal and macro-economic frameworks need to take into consideration and adjust for long-term climate objectives. This paper presents the reasons why both the financial sector and its governance bodies (IFGRIs) have interest in integrating climate change issues in their risk and stability assessment framework. 'Mainstreaming' climate change is a rational answer to the threat imposed on their respective mandates by increasing greenhouse gas emissions and policies that are likely to be implemented to achieve long-term mitigation and adaptation objectives. Securing global financial and economic stability and scaling up low-carbon, climate-resilient investments are not conflicting, but rather mutually reinforcing objectives. This premise can provide a good starting point for discussions between policy-makers and practitioners in the financial sector and the climate change domain. A well-informed discussion is currently hindered by the seemingly differing mandates, and the lack of institutional and intellectual links between the two agendas. (authors)
Teaching geographical hydrology in a non-stationary world
Hendriks, Martin R.; Karssenberg, Derek
2010-05-01
Understanding hydrological processes in a non-stationary world requires knowledge of hydrological processes and their interactions. Also, one needs to understand the (non-linear) relations between the hydrological system and other parts of our Earth system, such as the climate system, the socio-economic system, and the ecosystem. To provide this knowledge and understanding we think that three components are essential when teaching geographical hydrology. First of all, a student needs to acquire a thorough understanding of classical hydrology. For this, knowledge of the basic hydrological equations, such as the energy equation (Bernoulli), flow equation (Darcy), continuity (or water balance) equation is needed. This, however, is not sufficient to make a student fully understand the interactions between hydrological compartments, or between hydrological subsystems and other parts of the Earth system. Therefore, secondly, a student also needs to be knowledgeable of methods by which the different subsystems can be coupled; in general, numerical models are used for this. A major disadvantage of numerical models is their complexity. A solution may be to use simpler models, provided that a student really understands how hydrological processes function in our real, non-stationary world. The challenge for a student then lies in understanding the interactions between the subsystems, and to be able to answer questions such as: what is the effect of a change in vegetation or land use on runoff? Thirdly, knowledge of field hydrology is of utmost importance. For this a student needs to be trained in the field. Fieldwork is very important as a student is confronted in the field with spatial and temporal variability, as well as with real life uncertainties, rather than being lured into believing the world as presented in hydrological textbooks and models, e.g. the world under study is homogeneous, isotropic, or lumped (averaged). Also, students in the field learn to plan and
Bi-spectrum based-EMD applied to the non-stationary vibration signals for bearing faults diagnosis.
Saidi, Lotfi; Ali, Jaouher Ben; Fnaiech, Farhat
2014-09-01
Empirical mode decomposition (EMD) has been widely applied to analyze vibration signals behavior for bearing failures detection. Vibration signals are almost always non-stationary since bearings are inherently dynamic (e.g., speed and load condition change over time). By using EMD, the complicated non-stationary vibration signal is decomposed into a number of stationary intrinsic mode functions (IMFs) based on the local characteristic time scale of the signal. Bi-spectrum, a third-order statistic, helps to identify phase coupling effects, the bi-spectrum is theoretically zero for Gaussian noise and it is flat for non-Gaussian white noise, consequently the bi-spectrum analysis is insensitive to random noise, which are useful for detecting faults in induction machines. Utilizing the advantages of EMD and bi-spectrum, this article proposes a joint method for detecting such faults, called bi-spectrum based EMD (BSEMD). First, original vibration signals collected from accelerometers are decomposed by EMD and a set of IMFs is produced. Then, the IMF signals are analyzed via bi-spectrum to detect outer race bearing defects. The procedure is illustrated with the experimental bearing vibration data. The experimental results show that BSEMD techniques can effectively diagnosis bearing failures. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Financial Literacy and Financial Behaviour
Sayinzoga, Aussi; Bulte, Erwin H.; Lensink, Robert
2016-01-01
We organise a field experiment with smallholder farmers in Rwanda to measure the impact of financial literacy training on financial knowledge and behaviour. The training increased financial literacy of participants, changed their savings and borrowing behaviour and had a positive effect on the
Liu, Xin; Wang, Hongkai; Yan, Zhuangzhi
2016-11-01
Dynamic fluorescence molecular tomography (FMT) plays an important role in drug delivery research. However, the majority of current reconstruction methods focus on solving the stationary FMT problems. If the stationary reconstruction methods are applied to the time-varying fluorescence measurements, the reconstructed results may suffer from a high level of artifacts. In addition, based on the stationary methods, only one tomographic image can be obtained after scanning one circle projection data. As a result, the movement of fluorophore in imaged object may not be detected due to the relative long data acquisition time (typically >1 min). In this paper, we apply extended kalman filter (EKF) technique to solve the non-stationary fluorescence tomography problem. Especially, to improve the EKF reconstruction performance, the generalized inverse of kalman gain is calculated by a second-order iterative method. The numerical simulation, phantom, and in vivo experiments are performed to evaluate the performance of the method. The experimental results indicate that by using the proposed EKF-based second-order iterative (EKF-SOI) method, we cannot only clearly resolve the time-varying distributions of fluorophore within imaged object, but also greatly improve the reconstruction time resolution (~2.5 sec/frame) which makes it possible to detect the movement of fluorophore during the imaging processes.
Directory of Open Access Journals (Sweden)
Yoo-Geun Ham
2016-01-01
Full Text Available This study introduces a modified version of the incremental analysis updates (IAU, called the nonstationary IAU (NIAU method, to improve the assimilation accuracy of the IAU while keeping the continuity of the analysis. Similar to the IAU, the NIAU is designed to add analysis increments at every model time step to improve the continuity in the intermittent data assimilation. However, unlike the IAU, the NIAU procedure uses time-evolved forcing using the forward operator as corrections to the model. The solution of the NIAU is superior to that of the forward IAU, of which analysis is performed at the beginning of the time window for adding the IAU forcing, in terms of the accuracy of the analysis field. It is because, in the linear systems, the NIAU solution equals that in an intermittent data assimilation method at the end of the assimilation interval. To have the filtering property in the NIAU, a forward operator to propagate the increment is reconstructed with only dominant singular vectors. An illustration of those advantages of the NIAU is given using the simple 40-variable Lorenz model.
A unique Fock quantization for fields in non-stationary spacetimes
International Nuclear Information System (INIS)
Cortez, Jerónimo; Marugán, Guillermo A. Mena; Olmedo, Javier; Velhinho, José M.
2010-01-01
In curved spacetimes, the lack of criteria for the construction of a unique quantization is a fundamental problem undermining the significance of the predictions of quantum field theory. Inequivalent quantizations lead to different physics. Recently, however, some uniqueness results have been obtained for fields in non-stationary settings. In particular, for vacua that are invariant under the background symmetries, a unitary implementation of the classical evolution suffices to pick up a unique Fock quantization in the case of Klein-Gordon fields with time-dependent mass, propagating in a static spacetime whose spatial sections are three-spheres. In fact, the field equation can be reinterpreted as describing the propagation in a Friedmann-Robertson-Walker spacetime after a suitable scaling of the field by a function of time. For this class of fields, we prove here an even stronger result about the Fock quantization: the uniqueness persists when one allows for linear time-dependent transformations of the field in order to account for a scaling by background functions. In total, paying attention to the dynamics, there exists a preferred choice of quantum field, and only one SO(4)-invariant Fock representation for it that respects the standard probabilistic interpretation along the evolution. The result has relevant implications e.g. in cosmology
International Nuclear Information System (INIS)
Verley, Gatien; Lacoste, David; Chétrite, Raphaël
2011-01-01
In this paper, we present a general derivation of a modified fluctuation-dissipation theorem (MFDT) valid near an arbitrary non-stationary state for a system obeying Markovian dynamics. We show that the method for deriving modified fluctuation-dissipation theorems near non-equilibrium stationary states used by Prost et al (2009 Phys. Rev. Lett. 103 090601) is generalizable to non-stationary states. This result follows from both standard linear response theory and from a transient fluctuation theorem, analogous to the Hatano–Sasa relation. We show that this modified fluctuation-dissipation theorem can be interpreted at the trajectory level using the notion of stochastic trajectory entropy, in a way which is similar to what has been done recently in the case of the MFDT near non-equilibrium steady states (NESS). We illustrate this framework with two solvable examples: the first example corresponds to a Brownian particle in a harmonic trap subjected to a quench of temperature and to a time-dependent stiffness; the second example is a classic model of coarsening systems, namely the 1D Ising model with Glauber dynamics
International Nuclear Information System (INIS)
Cao, Z.J.; Tsui, B.M.
1993-01-01
Conventional single-orbit cone beam tomography presents special problems. They include incomplete sampling and inadequate three-dimensional (3D) reconstruction algorithm. The commonly used Feldkamp reconstruction algorithm simply extends the two-dimensional (2D) fan beam algorithm to 3D cone beam geometry. A truly 3D reconstruction formulation has been derived for the single-orbit cone beam SPECT based on the 3D Fourier slice theorem. In the formulation, a nonstationary filter which depends on the distance from the central plane of the cone beam was derived. The filter is applied to the 2D projection data in directions along and normal to the axis-of-rotation. The 3D reconstruction algorithm with the nonstationary filter was evaluated using both computer simulation and experimental measurements. Significant improvement in image quality was demonstrated in terms of decreased artifacts and distortions in cone beam reconstructed images. However, compared with the Feldkamp algorithm, a five-fold increase in processing time is required. Further improvement in image quality needs complete sampling in frequency space
Financial Economy and Financial System: Basis of Structural Interconnection
Directory of Open Access Journals (Sweden)
Khorosheva Olena I.
2014-02-01
Full Text Available The goal of the article lies in identification of grounds of interconnection of the financial economy and financial system. The study was conducted with consideration of main provisions of the theory of finance and concept of financial economy, which is a set of means used in the process of reproduction of finance by their owner for formation and / or maintenance of the own system of values in the viable state. For the first time ever the structure of the financial system is identified as an aggregate of financial economies and financial market. The article justifies a necessity of expansion of boundaries of perception of the state financial economy, which is offered to include public financial economy of the state level and the set of financial economies of the state as a subject of economic activity. Such an approach forms a base for justification of the synthesis of participation of the state in financial relations as the owner and as the basic macro-economic regulator. Prospects of further study in this direction are: development of classification of financial economies; revelation of specific features of impact of shadow finance on development of the national financial economy; and assessment of possibilities of inclusion of structured financial products into the system of values of financial economies in Ukraine.
Jothi, A Lenin
2009-01-01
Financial services, particularly banking and insurance services is the prominent sector for the development of a nation. After the liberalisation of financial sector in India, the scope of getting career opportunities has been widened. It is heartening to note that various universities in India have introduced professional courses on banking and insurance. A new field of applied mathematics has come into prominence under the name of Financial Mathematics. Financial mathematics has attained much importance in the recent years because of the role played by mathematical concepts in decision - m
International Nuclear Information System (INIS)
Man'ko, V.I.; Markov, M.A.
1984-01-01
This chapter considers the process of creation of particles with maximally big masses (maximons, intermediate bosons) in the nonstationary Universe within the framework of neutral and charged scalar field theory. The conclusions of the matter creation model for real particles (resonances) and hypothetical particles (maximons, friedmons, intermediate bosons) are analyzed. It is determined that if the mechanism of maximon's creation exists, then these particles must be stable. The maximons could be the final states of decaying black holes. A possible mechanism of cosmic ray creation as a result of ''vacuum'' generation of known unstable particles is discussed. The limits upon the mass and the life time of intermediate bosons are calculated. It is demonstrated that the creation of masses greater than 10 GeV, and with life times less than 10- 24 sec and quantity of elementary particles greater than 100 are in contradiction with the particle creation mechanism and the experimental mass density in the Universe. The formalism of the examined method and its vacuum properties are discussed in an appendix
Energy Technology Data Exchange (ETDEWEB)
Vehauc, A; Spasojevic, D [Institute of nuclear sciences Boris Kidric, Vinca, Beograd (Yugoslavia)
1970-03-15
Nonstationary temperature field in the fuel element was examined for spatial and time distribution of the specific power generated in the fuel element. Analytical method was developed for calculating the temperature variation in the fuel element of a nuclear reactor for a typical shape of the heat generation function. The method is based on series expansion of the temperature field by self functions and application of Laplace transformation in time coordinate. For numerical calculation of the temperature distribution a computer code was developed based on the proposed method and applied on the ZUSE-Z-23 computer. Razmatrano je nestacionarno temperatursko polje u preseku sipke gorivnog elementa za slucaj prostorne i vremenske raspodele specificne generacije snage u gorivnom elementu. Razradjen je analii postupak odredjivanja promene temperature u gorivu nuklearnog reaktora za tipican oblik funkcije generacije toplote. Postupak se zasniva na razvoju temperaturskog polja po sopstvenim funkcijama i primeni Laplasove transformacije po vremenskoj koordinati. Za efektivno nalazenje temperaturskog polja, postupak je programiran za digitalnu racunsku masinu ZUSE-Z-23 (author)
International Nuclear Information System (INIS)
Feng, Ke; Wang, KeSheng; Zhang, Mian; Ni, Qing; Zuo, Ming J
2017-01-01
The planetary gearbox, due to its unique mechanical structures, is an important rotating machine for transmission systems. Its engineering applications are often in non-stationary operational conditions, such as helicopters, wind energy systems, etc. The unique physical structures and working conditions make the vibrations measured from planetary gearboxes exhibit a complex time-varying modulation and therefore yield complicated spectral structures. As a result, traditional signal processing methods, such as Fourier analysis, and the selection of characteristic fault frequencies for diagnosis face serious challenges. To overcome this drawback, this paper proposes a signal selection scheme for fault-emphasized diagnostics based upon two order tracking techniques. The basic procedures for the proposed scheme are as follows. (1) Computed order tracking is applied to reveal the order contents and identify the order(s) of interest. (2) Vold–Kalman filter order tracking is used to extract the order(s) of interest—these filtered order(s) constitute the so-called selected vibrations. (3) Time domain statistic indicators are applied to the selected vibrations for faulty information-emphasized diagnostics. The proposed scheme is explained and demonstrated in a signal simulation model and experimental studies and the method proves to be effective for planetary gearbox fault diagnosis. (paper)
A Review of ENSO Influence on the North Atlantic. A Non-Stationary Signal
Directory of Open Access Journals (Sweden)
Belén Rodríguez-Fonseca
2016-06-01
Full Text Available The atmospheric seasonal cycle of the North Atlantic region is dominated by meridional movements of the circulation systems: from the tropics, where the West African Monsoon and extreme tropical weather events take place, to the extratropics, where the circulation is dominated by seasonal changes in the jetstream and extratropical cyclones. Climate variability over the North Atlantic is controlled by various mechanisms. Atmospheric internal variability plays a crucial role in the mid-latitudes. However, El Niño-Southern Oscillation (ENSO is still the main source of predictability in this region situated far away from the Pacific. Although the ENSO influence over tropical and extra-tropical areas is related to different physical mechanisms, in both regions this teleconnection seems to be non-stationary in time and modulated by multidecadal changes of the mean flow. Nowadays, long observational records (greater than 100 years and modeling projects (e.g., CMIP permit detecting non-stationarities in the influence of ENSO over the Atlantic basin, and further analyzing its potential mechanisms. The present article reviews the ENSO influence over the Atlantic region, paying special attention to the stability of this teleconnection over time and the possible modulators. Evidence is given that the ENSO–Atlantic teleconnection is weak over the North Atlantic. In this regard, the multidecadal ocean variability seems to modulate the presence of teleconnections, which can lead to important impacts of ENSO and to open windows of opportunity for seasonal predictability.
Milner, Alison J; Niven, Heather; LaMontagne, Anthony D
2015-09-21
Previous research showed an increase in Australian suicide rates during the Global Financial Crisis (GFC). There has been no research investigating whether suicide rates by occupational class changed during the GFC. The aim of this study was to investigate whether the GFC-associated increase in suicide rates in employed Australians may have masked changes by occupational class. Negative binomial regression models were used to investigate Rate Ratios (RRs) in suicide by occupational class. Years of the GFC (2007, 2008, 2009) were compared to the baseline years 2001-2006. There were widening disparities between a number of the lower class occupations and the highest class occupations during the years 2007, 2008, and 2009 for males, but less evidence of differences for females. Occupational disparities in suicide rates widened over the GFC period. There is a need for programs to be responsive to economic downturns, and to prioritise the occupational groups most affected.
Gerlich, Nikolas; Rostek, Stefan
2015-09-01
We derive a heuristic method to estimate the degree of self-similarity and serial correlation in financial time series. Especially, we propagate the use of a tailor-made selection of different estimation techniques that are used in various fields of time series analysis but until now have not consequently found their way into the finance literature. Following the idea of portfolio diversification, we show that considerable improvements with respect to robustness and unbiasedness can be achieved by using a basket of estimation methods. With this methodological toolbox at hand, we investigate real market data to show that noticeable deviations from the assumptions of constant self-similarity and absence of serial correlation occur during certain periods. On the one hand, this may shed a new light on seemingly ambiguous scientific findings concerning serial correlation of financial time series. On the other hand, a proven time-changing degree of self-similarity may help to explain high-volatility clusters of stock price indices.
Modeling fire spatial non-stationary in Portugal using GWR and GAMLSS
Sá, Ana C. L.; Amaral Turkman, Maria A.; Bistinas, Ioannis; Pereira, José M. C.
2014-05-01
Portuguese wildfires are responsible for large environmental, ecological and socio-economic impacts and, in the last decade, vegetation fires consumed on average 140.000ha/year. Portugal has a unique fires-atlas of burnt scar perimeters covering the 1975-2009 period, which allows the assessment of the fire most affected areas. It's crucial to understand the influence of the main drivers of forest fires and its spatial distribution in order to set new management strategies to reduce its impacts. Thus, this study aims at evaluating the spatial stationarity of the fire-environment relationship using two statistical approaches: Geographically Weighted Regression (GWR) and Generalized Additive Models for Location, Scale and Shape (GAMLSS). Analysis was performed using a regular 2kmx2km cell size grid, a total of 21293 observations overlaying the mainland of Portugal. Fire incidence was determined as the number of times each grid cell burned in the 35 years period. For the GWR analysis the group of environmental variables selected as predictors are: ignition source (population density (PD)); vegetation (proportion of forest and shrubland (FORSHR)); and weather (total precipitation of the coldest quarter (PCQ). Results showed that the fire-environment relationship is non-stationary, thus the coefficient estimates of all the predictors vary spatially, both in magnitude and sign. The most statistically significant predictor is FORSHR, followed by the PCQ. Despite the relationship between fire incidence and PD is non-stationary, only 9% of the observations are statistically significant at a 95% level of confidence. When compared with the Ordinary Least Squares (OLS) global model, 53% of the R2 statistic is above the 26% global estimated value, meaning a better explanation of the fire incidence variance with the local model approach. Using the same environmental variables, fire incidence was also modeled using GAMLSS to characterize nonstationarities in fire incidence. It is
Network structure of multivariate time series.
Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito
2015-10-21
Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.
Financial Liberalization and Financial Fragility
Enrica Detragiache; Asli Demirgüç-Kunt
1998-01-01
The authors study the empirical relationship between banking crises and financial liberalization using a panel of data for 53 countries for 1980-95. They find that banking crises are more likely to occur in liberalized financial systems. But financial liberalization's impact on a fragile banking sector is weaker where the institutional environment is strong--especially where there is respect for the rule of law, a low level of corruption, and good contract enforcement. They examine evidence o...
Liquidity management through financial planning
Kameníková Katarína
2001-01-01
One of the basic goals of financial management is to provide financial property and capital for running of the firm, as well as for its development, that means provide optimal firm´s liquidity.To improve liquidity is possible provide through various ways. In present time there is increasing importance of financial planning., where planning of liquidity presents one of its integral part. Therefore I deal in presented paper with possible liquidity improvement through calculation of financial pl...
International Development Research Centre (IDRC) Digital Library (Canada)
users make on the basis of the financial information. .... IDRC's brand and reputation could impact partner- .... building and to provide internal services in support of the ...... maintains books of accounts, information systems, and financial and management controls that .... The significant accounting policies of the Centre are: a.
Climate Informed Low Flow Frequency Analysis Using Nonstationary Modeling
Liu, D.; Guo, S.; Lian, Y.
2014-12-01
Stationarity is often assumed for frequency analysis of low flows in water resources management and planning. However, many studies have shown that flow characteristics, particularly the frequency spectrum of extreme hydrologic events,were modified by climate change and human activities and the conventional frequency analysis without considering the non-stationary characteristics may lead to costly design. The analysis presented in this paper was based on the more than 100 years of daily flow data from the Yichang gaging station 44 kilometers downstream of the Three Gorges Dam. The Mann-Kendall trend test under the scaling hypothesis showed that the annual low flows had significant monotonic trend, whereas an abrupt change point was identified in 1936 by the Pettitt test. The climate informed low flow frequency analysis and the divided and combined method are employed to account for the impacts from related climate variables and the nonstationarities in annual low flows. Without prior knowledge of the probability density function for the gaging station, six distribution functions including the Generalized Extreme Values (GEV), Pearson Type III, Gumbel, Gamma, Lognormal, and Weibull distributions have been tested to find the best fit, in which the local likelihood method is used to estimate the parameters. Analyses show that GEV had the best fit for the observed low flows. This study has also shown that the climate informed low flow frequency analysis is able to exploit the link between climate indices and low flows, which would account for the dynamic feature for reservoir management and provide more accurate and reliable designs for infrastructure and water supply.
H2 emission from non-stationary magnetized bow shocks
Tram, L. N.; Lesaffre, P.; Cabrit, S.; Gusdorf, A.; Nhung, P. T.
2018-01-01
When a fast moving star or a protostellar jet hits an interstellar cloud, the surrounding gas gets heated and illuminated: a bow shock is born that delineates the wake of the impact. In such a process, the new molecules that are formed and excited in the gas phase become accessible to observations. In this paper, we revisit models of H2 emission in these bow shocks. We approximate the bow shock by a statistical distribution of planar shocks computed with a magnetized shock model. We improve on previous works by considering arbitrary bow shapes, a finite irradiation field and by including the age effect of non-stationary C-type shocks on the excitation diagram and line profiles of H2. We also examine the dependence of the line profiles on the shock velocity and on the viewing angle: we suggest that spectrally resolved observations may greatly help to probe the dynamics inside the bow shock. For reasonable bow shapes, our analysis shows that low-velocity shocks largely contribute to H2 excitation diagram. This can result in an observational bias towards low velocities when planar shocks are used to interpret H2 emission from an unresolved bow. We also report a large magnetization bias when the velocity of the planar model is set independently. Our 3D models reproduce excitation diagrams in BHR 71 and Orion bow shocks better than previous 1D models. Our 3D model is also able to reproduce the shape and width of the broad H2 1-0S(1) line profile in an Orion bow shock (Brand et al. 1989).
Some strange numerical solutions of the non-stationary Navier-Stokes equations in pipes
Energy Technology Data Exchange (ETDEWEB)
Rummler, B.
2001-07-01
A general class of boundary-pressure-driven flows of incompressible Newtonian fluids in three-dimensional pipes with known steady laminar realizations is investigated. Considering the laminar velocity as a 3D-vector-function of the cross-section-circle arguments, we fix the scale for the velocity by the L{sub 2}-norm of the laminar velocity. The usual new variables are introduced to get dimension-free Navier-Stokes equations. The characteristic physical and geometrical quantities are subsumed in the energetic Reynolds number Re and a parameter {psi}, which involves the energetic ratio and the directions of the boundary-driven part and the pressure-driven part of the laminar flow. The solution of non-stationary dimension-free Navier-Stokes equations is sought in the form u=u{sub L}+u, where u{sub L} is the scaled laminar velocity and periodical conditions in center-line-direction are prescribed for u. An autonomous system (S) of ordinary differential equations for the time-dependent coefficients of the spatial Stokes eigenfunction is got by application of the Galerkin-method to the dimension-free Navier-Stokes equations for u. The finite-dimensional approximations u{sub N({lambda}}{sub )} of u are defined in the usual way. (orig.)
International Nuclear Information System (INIS)
Lin, S.; Li, Y.; Liu, C.; Wang, H.; Zhang, N.; Cui, W.; Neuber, A.
2015-01-01
This paper presents a statistical theory for the initial onset of multipactor breakdown in coaxial transmission lines, taking both the nonuniform electric field and random electron emission velocity into account. A general numerical method is first developed to construct the joint probability density function based on the approximate equation of the electron trajectory. The nonstationary dynamics of the multipactor process on both surfaces of coaxial lines are modelled based on the probability of various impacts and their corresponding secondary emission. The resonant assumption of the classical theory on the independent double-sided and single-sided impacts is replaced by the consideration of their interaction. As a result, the time evolutions of the electron population for exponential growth and absorption on both inner and outer conductor, in response to the applied voltage above and below the multipactor breakdown level, are obtained to investigate the exact mechanism of multipactor discharge in coaxial lines. Furthermore, the multipactor threshold predictions of the presented model are compared with experimental results using measured secondary emission yield of the tested samples which shows reasonable agreement. Finally, the detailed impact scenario reveals that single-surface multipactor is more likely to occur with a higher outer to inner conductor radius ratio
Financial Literacy, Financial Education, and Economic Outcomes
Hastings, Justine S.; Madrian, Brigitte C.; Skimmyhorn, William L.
2013-01-01
In this article, we review the literature on financial literacy, financial education, and consumer financial outcomes. We consider how financial literacy is measured in the current literature and examine how well the existing literature addresses whether financial education improves financial literacy or personal financial outcomes. We discuss the…
International Nuclear Information System (INIS)
Gil, E; Orini, M; Bailón, R; Laguna, P; Vergara, J M; Mainardi, L
2010-01-01
In this paper we assessed the possibility of using the pulse rate variability (PRV) extracted from the photoplethysmography signal as an alternative measurement of the HRV signal in non-stationary conditions. The study is based on analysis of the changes observed during a tilt table test in the heart rate modulation of 17 young subjects. First, the classical indices of HRV analysis were compared to the indices from PRV in intervals where stationarity was assumed. Second, the time-varying spectral properties of both signals were compared by time-frequency (TF) and TF coherence analysis. Third, the effect of replacing PRV with HRV in the assessment of the changes of the autonomic modulation of the heart rate was considered. Time-invariant HRV and PRV indices showed no statistically significant differences (p > 0.05) and high correlation (>0.97). Time-frequency analysis revealed that the TF spectra of both signals were highly correlated (0.99 ± 0.01); the difference between the instantaneous power, in the LF and HF bands, obtained from HRV and PRV was small (<10 −3 s −2 ) and their temporal patterns were highly correlated (0.98 ± 0.04 and 0.95 ± 0.06 in the LF and HF bands, respectively) and TF coherence in the LF and HF bands was high (0.97 ± 0.04 and 0.89 ± 0.08, respectively). Finally, the instantaneous power in the LF band was observed to significantly increase during head-up tilt by both HRV and PRV analysis. These results suggest that although some differences in the time-varying spectral indices extracted from HRV and PRV exist, mainly in the HF band associated with respiration, PRV could be used as a surrogate of HRV during non-stationary conditions, at least during the tilt table test
DEFF Research Database (Denmark)
Åström, Helena Lisa Alexandra; Friis Hansen, P.; Garrè, Luca
2014-01-01
Urban flooding introduces significant risk to society. Non-stationarity leads to increased uncertainty and this is challenging to include in actual decision-making. The primary objective of this study was to develop a risk assessment and decision support framework for pluvial urban flood risk under...... non-stationary conditions using an influence diagram (ID) which is a Bayesian network (BN) extended with decision and utility nodes. Non-stationarity is considered to be the influence of climate change where extreme precipitation patterns change over time. The overall risk is quantified in monetary...... terms expressed as expected annual damage. The network is dynamic in as much as it assesses risk at different points in time. The framework provides means for decision-makers to assess how different decisions on flood adaptation affect the risk now and in the future. The result from the ID was extended...
Detection of Partial Demagnetization Fault in PMSMs Operating under Nonstationary Conditions
DEFF Research Database (Denmark)
Wang, Chao; Delgado Prieto, Miguel; Romeral, Luis
2016-01-01
Demagnetization fault detection of in-service Permanent Magnet Synchronous Machines (PMSMs) is a challenging task because most PMSMs operate under nonstationary circumstances in industrial applications. A novel approach based on tracking characteristic orders of stator current using Vold-Kalman F......Demagnetization fault detection of in-service Permanent Magnet Synchronous Machines (PMSMs) is a challenging task because most PMSMs operate under nonstationary circumstances in industrial applications. A novel approach based on tracking characteristic orders of stator current using Vold......-Kalman Filter is proposed to detect the partial demagnetization fault in PMSMs running at nonstationary conditions. Amplitude of envelope of the fault characteristic orders is used as fault indictor. Experimental results verify the superiority of the proposed method on partial demagnetization online fault...... detection of PMSMs under various speed and load conditions....
Directory of Open Access Journals (Sweden)
Xiang Zeng
2016-06-01
Full Text Available Abstract We prove some almost sure central limit theorems for the maxima of strongly dependent nonstationary Gaussian vector sequences under some mild conditions. The results extend the ASCLT to nonstationary Gaussian vector sequences and give substantial improvements for the weight sequence obtained by Lin et al. (Comput. Math. Appl. 62(2:635-640, 2011.