The Short-Time Behaviour of VIX Implied Volatilities in a Multifactor Stochastic Volatility Framework

DEFF Research Database (Denmark)

Barletta, Andrea; Nicolato, Elisa; Pagliarani, Stefano

error bounds for VIX futures, options and implied volatilities. In particular, we derive exact asymptotic results for VIX implied volatilities, and their sensitivities, in the joint limit of short time-to-maturity and small log-moneyness. The obtained expansions are explicit, based on elementary...... approximations of equity (SPX) options. However, the generalizations needed to cover the case of VIX options are by no means straightforward as the dynamics of the underlying VIX futures are not explicitly known. To illustrate the accuracy of our technique, we provide numerical implementations for a selection...... functions and they neatly uncover how the VIX skew depends on the specific choice of the volatility and the vol-of-vol processes. Our results are based on perturbation techniques applied to the infinitesimal generator of the underlying process. This methodology has been previously adopted to derive...

A multiscale extension of the Margrabe formula under stochastic volatility

International Nuclear Information System (INIS)

Kim, Jeong-Hoon; Park, Chang-Rae

2017-01-01

Highlights: • Fast-mean-reverting stochastic volatility model is chosen to extend the classical Margrabe formula. • The resultant formula is explicitly given by the greeks of Margrabe price itself. • We show how the stochastic volatility corrects the Margrabe price behavior. - Abstract: The pricing of financial derivatives based on stochastic volatility models has been a popular subject in computational finance. Although exact or approximate closed form formulas of the prices of many options under stochastic volatility have been obtained so that the option prices can be easily computed, such formulas for exchange options leave much to be desired. In this paper, we consider two different risky assets with two different scales of mean-reversion rate of volatility and use asymptotic analysis to extend the classical Margrabe formula, which corresponds to a geometric Brownian motion model, and obtain a pricing formula under a stochastic volatility. The resultant formula can be computed easily, simply by taking derivatives of the Margrabe price itself. Based on the formula, we show how the stochastic volatility corrects the Margrabe price behavior depending on the moneyness and the correlation coefficient between the two asset prices.

Estimation of Stochastic Volatility Models by Nonparametric Filtering

DEFF Research Database (Denmark)

Kanaya, Shin; Kristensen, Dennis

2016-01-01

/estimated volatility process replacing the latent process. Our estimation strategy is applicable to both parametric and nonparametric stochastic volatility models, and can handle both jumps and market microstructure noise. The resulting estimators of the stochastic volatility model will carry additional biases...... and variances due to the first-step estimation, but under regularity conditions we show that these vanish asymptotically and our estimators inherit the asymptotic properties of the infeasible estimators based on observations of the volatility process. A simulation study examines the finite-sample properties...

Oil and stock market volatility: A multivariate stochastic volatility perspective

International Nuclear Information System (INIS)

Vo, Minh

2011-01-01

This paper models the volatility of stock and oil futures markets using the multivariate stochastic volatility structure in an attempt to extract information intertwined in both markets for risk prediction. It offers four major findings. First, the stock and oil futures prices are inter-related. Their correlation follows a time-varying dynamic process and tends to increase when the markets are more volatile. Second, conditioned on the past information, the volatility in each market is very persistent, i.e., it varies in a predictable manner. Third, there is inter-market dependence in volatility. Innovations that hit either market can affect the volatility in the other market. In other words, conditioned on the persistence and the past volatility in their respective markets, the past volatility of the stock (oil futures) market also has predictive power over the future volatility of the oil futures (stock) market. Finally, the model produces more accurate Value-at-Risk estimates than other benchmarks commonly used in the financial industry. - Research Highlights: → This paper models the volatility of stock and oil futures markets using the multivariate stochastic volatility model. → The correlation between the two markets follows a time-varying dynamic process which tends to increase when the markets are more volatile. → The volatility in each market is very persistent. → Innovations that hit either market can affect the volatility in the other market. → The model produces more accurate Value-at-Risk estimates than other benchmarks commonly used in the financial industry.

Maximum likelihood approach for several stochastic volatility models

International Nuclear Information System (INIS)

Camprodon, Jordi; Perelló, Josep

2012-01-01

Volatility measures the amplitude of price fluctuations. Despite it being one of the most important quantities in finance, volatility is not directly observable. Here we apply a maximum likelihood method which assumes that price and volatility follow a two-dimensional diffusion process where volatility is the stochastic diffusion coefficient of the log-price dynamics. We apply this method to the simplest versions of the expOU, the OU and the Heston stochastic volatility models and we study their performance in terms of the log-price probability, the volatility probability, and its Mean First-Passage Time. The approach has some predictive power on the future returns amplitude by only knowing the current volatility. The assumed models do not consider long-range volatility autocorrelation and the asymmetric return-volatility cross-correlation but the method still yields very naturally these two important stylized facts. We apply the method to different market indices and with a good performance in all cases. (paper)

On Volatility Induced Stationarity for Stochastic Differential Equations

DEFF Research Database (Denmark)

Albin, J.M.P.; Astrup Jensen, Bjarne; Muszta, Anders

2006-01-01

This article deals with stochastic differential equations with volatility induced stationarity. We study of theoretical properties of such equations, as well as numerical aspects, together with a detailed study of three examples.......This article deals with stochastic differential equations with volatility induced stationarity. We study of theoretical properties of such equations, as well as numerical aspects, together with a detailed study of three examples....

On changes of measure in stochastic volatility models

Directory of Open Access Journals (Sweden)

Bernard Wong

2006-01-01

models. This had led many researchers to “assume the condition away,” even though the condition is not innocuous, and nonsensical results can occur if it is in fact not satisfied. We provide an applicable theorem to check the conditions for a general class of Markovian stochastic volatility models. As an example we will also provide a detailed analysis of the Stein and Stein and Heston stochastic volatility models.

Regime-switching stochastic volatility. Evidence from the crude oil market

International Nuclear Information System (INIS)

Vo, Minh T.

2009-01-01

This paper incorporates regime-switching into the stochastic volatility (SV) framework in an attempt to explain the behavior of crude oil prices in order to forecast their volatility. More specifically, it models the volatility of oil return as a stochastic volatility process whose mean is subject to shifts in regime. The shift is governed by a two-state first-order Markov process. The Bayesian Markov Chain Monte Carlo method is used to estimate the models. The main findings are: first, there is clear evidence of regime-switching in the oil market. Ignoring it will lead to a false impression that the volatility is highly persistent and therefore highly predictable. Second, incorporating regime-switching into the SV framework significantly enhances the forecasting power of the SV model. Third, the regime-switching stochastic volatility model does a good job in capturing major events affecting the oil market. (author)

Bias-reduced estimation of long memory stochastic volatility

DEFF Research Database (Denmark)

Frederiksen, Per; Nielsen, Morten Ørregaard

We propose to use a variant of the local polynomial Whittle estimator to estimate the memory parameter in volatility for long memory stochastic volatility models with potential nonstation- arity in the volatility process. We show that the estimator is asymptotically normal and capable of obtaining...

The Pricing of Options on Assets with Stochastic Volatilities.

OpenAIRE

Hull, John C; White, Alan D

1987-01-01

One option-pricing problem which has hitherto been unsolved is the pricing of European call on an asset which has a stochastic volatility. This paper examines this problem. The option price is determined in series form for the case in which the stochastic volatility is independent of the stock price. Numerical solutions are also produced for the case in which the volatility is correlated with the stock price. It is found that the Black-Scholes price frequently overprices options and that the ...

Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange

Science.gov (United States)

Takaishi, Tetsuya

2018-06-01

The realized stochastic volatility model has been introduced to estimate more accurate volatility by using both daily returns and realized volatility. The main advantage of the model is that no special bias-correction factor for the realized volatility is required a priori. Instead, the model introduces a bias-correction parameter responsible for the bias hidden in realized volatility. We empirically investigate the bias-correction parameter for realized volatilities calculated at various sampling frequencies for six stocks on the Tokyo Stock Exchange, and then show that the dynamic behavior of the bias-correction parameter as a function of sampling frequency is qualitatively similar to that of the Hansen-Lunde bias-correction factor although their values are substantially different. Under the stochastic diffusion assumption of the return dynamics, we investigate the accuracy of estimated volatilities by examining the standardized returns. We find that while the moments of the standardized returns from low-frequency realized volatilities are consistent with the expectation from the Gaussian variables, the deviation from the expectation becomes considerably large at high frequencies. This indicates that the realized stochastic volatility model itself cannot completely remove bias at high frequencies.

Some recent developments in stochastic volatility modelling

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Nicolato, Elisa; Shephard, N.

2002-01-01

This paper reviews and puts in context some of our recent work on stochastic volatility (SV) modelling for financial economics. Here our main focus is on: (i) the relationship between subordination and SV, (ii) OU based volatility models, (iii) exact option pricing, (iv) realized power variation...

Stochastic Volatility and DSGE Models

DEFF Research Database (Denmark)

Andreasen, Martin Møller

This paper argues that a specification of stochastic volatility commonly used to analyze the Great Moderation in DSGE models may not be appropriate, because the level of a process with this specification does not have conditional or unconditional moments. This is unfortunate because agents may...

Estimation of Dynamic Panel Data Models with Stochastic Volatility Using Particle Filters

Directory of Open Access Journals (Sweden)

Wen Xu

2016-10-01

Full Text Available Time-varying volatility is common in macroeconomic data and has been incorporated into macroeconomic models in recent work. Dynamic panel data models have become increasingly popular in macroeconomics to study common relationships across countries or regions. This paper estimates dynamic panel data models with stochastic volatility by maximizing an approximate likelihood obtained via Rao-Blackwellized particle filters. Monte Carlo studies reveal the good and stable performance of our particle filter-based estimator. When the volatility of volatility is high, or when regressors are absent but stochastic volatility exists, our approach can be better than the maximum likelihood estimator which neglects stochastic volatility and generalized method of moments (GMM estimators.

Empirical Analysis of Stochastic Volatility Model by Hybrid Monte Carlo Algorithm

International Nuclear Information System (INIS)

Takaishi, Tetsuya

2013-01-01

The stochastic volatility model is one of volatility models which infer latent volatility of asset returns. The Bayesian inference of the stochastic volatility (SV) model is performed by the hybrid Monte Carlo (HMC) algorithm which is superior to other Markov Chain Monte Carlo methods in sampling volatility variables. We perform the HMC simulations of the SV model for two liquid stock returns traded on the Tokyo Stock Exchange and measure the volatilities of those stock returns. Then we calculate the accuracy of the volatility measurement using the realized volatility as a proxy of the true volatility and compare the SV model with the GARCH model which is one of other volatility models. Using the accuracy calculated with the realized volatility we find that empirically the SV model performs better than the GARCH model.

Estimation of stochastic volatility by using Ornstein-Uhlenbeck type models

Science.gov (United States)

Mariani, Maria C.; Bhuiyan, Md Al Masum; Tweneboah, Osei K.

2018-02-01

In this study, we develop a technique for estimating the stochastic volatility (SV) of a financial time series by using Ornstein-Uhlenbeck type models. Using the daily closing prices from developed and emergent stock markets, we conclude that the incorporation of stochastic volatility into the time varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. Furthermore, our estimation algorithm is feasible with large data sets and have good convergence properties.

Stochastic volatility and multi-dimensional modeling in the European energy market

Energy Technology Data Exchange (ETDEWEB)

Vos, Linda

2012-07-01

In energy prices there is evidence for stochastic volatility. Stochastic volatility has effect on the price of path-dependent options and therefore has to be modeled properly. We introduced a multi-dimensional non-Gaussian stochastic volatility model with leverage which can be used in energy pricing. It captures special features of energy prices like price spikes, mean-reversion, stochastic volatility and inverse leverage. Moreover it allows modeling dependencies between different commodities.The derived forward price dynamics based on this multi-variate spot price model, provides a very flexible structure. It includes cotango, backwardation and hump shape forward curves.Alternatively energy prices could be modeled by a 2-factor model consisting of a non-Gaussian stable CARMA process and a non-stationary trend models by a Levy process. Also this model is able to capture special features like price spikes, mean reversion and the low frequency dynamics in the market. An robust L1-filter is introduced to filter out the states of the CARMA process. When applying to German electricity EEX exchange data an overall negative risk-premium is found. However close to delivery a positive risk-premium is observed.(Author)

An Empirical Application of a Two-Factor Model of Stochastic Volatility

Czech Academy of Sciences Publication Activity Database

Kuchyňka, Alexandr

2008-01-01

Roč. 17, č. 3 (2008), s. 243-253 ISSN 1210-0455 R&D Projects: GA ČR GA402/07/1113; GA MŠk(CZ) LC06075 Institutional research plan: CEZ:AV0Z10750506 Keywords : stochastic volatility * Kalman filter Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2008/E/kuchynka-an empirical application of a two-factor model of stochastic volatility.pdf

Index Option Pricing Models with Stochastic Volatility and Stochastic Interest Rates

NARCIS (Netherlands)

Jiang, G.J.; van der Sluis, P.J.

2000-01-01

This paper specifies a multivariate stochastic volatility (SV) model for the S&P500 index and spot interest rate processes. We first estimate the multivariate SV model via the efficient method of moments (EMM) technique based on observations of underlying state variables, and then investigate the

News Impact Curve for Stochastic Volatility Models

OpenAIRE

Makoto Takahashi; Yasuhiro Omori; Toshiaki Watanabe

2012-01-01

This paper proposes a new method to compute the news impact curve for stochastic volatility (SV) models. The new method incorporates the joint movement of return and volatility, which has been ignored by the extant literature, by simply adding a couple of steps to the Bayesian MCMC estimation procedures for SV models. This simple procedure is versatile and applicable to various SV type models. Contrary to the monotonic news impact functions in the extant literature, the new method gives a U-s...

Jumps and stochastic volatility in oil prices: Time series evidence

International Nuclear Information System (INIS)

Larsson, Karl; Nossman, Marcus

2011-01-01

In this paper we examine the empirical performance of affine jump diffusion models with stochastic volatility in a time series study of crude oil prices. We compare four different models and estimate them using the Markov Chain Monte Carlo method. The support for a stochastic volatility model including jumps in both prices and volatility is strong and the model clearly outperforms the others in terms of a superior fit to data. Our estimation method allows us to obtain a detailed study of oil prices during two periods of extreme market stress included in our sample; the Gulf war and the recent financial crisis. We also address the economic significance of model choice in two option pricing applications. The implied volatilities generated by the different estimated models are compared and we price a real option to develop an oil field. Our findings indicate that model choice can have a material effect on the option values.

A low-bias simulation scheme for the SABR stochastic volatility model

NARCIS (Netherlands)

B. Chen (Bin); C.W. Oosterlee (Cornelis); J.A.M. van der Weide

2012-01-01

htmlabstractThe Stochastic Alpha Beta Rho Stochastic Volatility (SABR-SV) model is widely used in the financial industry for the pricing of fixed income instruments. In this paper we develop an lowbias simulation scheme for the SABR-SV model, which deals efficiently with (undesired)

On cross-currency models with stochastic volatility and correlated interest rates

NARCIS (Netherlands)

Grzelak, L.A.; Oosterlee, C.W.

2010-01-01

We construct multi-currency models with stochastic volatility and correlated stochastic interest rates with a full matrix of correlations. We first deal with a foreign exchange (FX) model of Heston-type, in which the domestic and foreign interest rates are generated by the short-rate process of

Asymptotic Behavior of the Stock Price Distribution Density and Implied Volatility in Stochastic Volatility Models

International Nuclear Information System (INIS)

Gulisashvili, Archil; Stein, Elias M.

2010-01-01

We study the asymptotic behavior of distribution densities arising in stock price models with stochastic volatility. The main objects of our interest in the present paper are the density of time averages of the squared volatility process and the density of the stock price process in the Stein-Stein and the Heston model. We find explicit formulas for leading terms in asymptotic expansions of these densities and give error estimates. As an application of our results, sharp asymptotic formulas for the implied volatility in the Stein-Stein and the Heston model are obtained.

Optimal investment models with stochastic volatility: the time ...

African Journals Online (AJOL)

Therefore, a transform is primordial to express the value function in terms of a semilinear PDE with quadratic growth on the derivative term. Some proofs for the existence of smooth solution to this equation have been provided for this equation by Pham [11]. In that paper they illustrated some common stochastic volatility ...

Large deviations and stochastic volatility with jumps: asymptotic implied volatility for affine models

OpenAIRE

Antoine Jacquier; Martin Keller-Ressel; Aleksandar Mijatovic

2011-01-01

Let $\\sigma_t(x)$ denote the implied volatility at maturity $t$ for a strike $K=S_0 e^{xt}$, where $x\\in\\bbR$ and $S_0$ is the current value of the underlying. We show that $\\sigma_t(x)$ has a uniform (in $x$) limit as maturity $t$ tends to infinity, given by the formula $\\sigma_\\infty(x)=\\sqrt{2}(h^*(x)^{1/2}+(h^*(x)-x)^{1/2})$, for $x$ in some compact neighbourhood of zero in the class of affine stochastic volatility models. The function $h^*$ is the convex dual of the limiting cumulant gen...

Decoupling the short- and long-term behavior of stochastic volatility

DEFF Research Database (Denmark)

Bennedsen, Mikkel; Lunde, Asger; Pakkanen, Mikko

behavior) from long memory and persistence (long-term behavior) in a simple and parsimonious way, which allows us to successfully model volatility at all intraday time scales. Our prime model is based on the so-called Brownian semistationary process and we derive a number of theoretical properties...... measures of close to two thousand individual US equities, we find that both roughness and persistence appear to be universal properties of volatility. Inspired by the empirical findings, we introduce a new class of continuous-time stochastic volatility models, capable of decoupling roughness (short-term...

Extreme-Strike and Small-time Asymptotics for Gaussian Stochastic Volatility Models

OpenAIRE

Zhang, Xin

2016-01-01

Asymptotic behavior of implied volatility is of our interest in this dissertation. For extreme strike, we consider a stochastic volatility asset price model in which the volatility is the absolute value of a continuous Gaussian process with arbitrary prescribed mean and covariance. By exhibiting a Karhunen-Loève expansion for the integrated variance, and using sharp estimates of the density of a general second-chaos variable, we derive asymptotics for the asset price density for large or smal...

Value-at-Risk for South-East Asian Stock Markets: Stochastic Volatility vs. GARCH

Directory of Open Access Journals (Sweden)

Paul Bui Quang

2018-04-01

Full Text Available This study compares the performance of several methods to calculate the Value-at-Risk of the six main ASEAN stock markets. We use filtered historical simulations, GARCH models, and stochastic volatility models. The out-of-sample performance is analyzed by various backtesting procedures. We find that simpler models fail to produce sufficient Value-at-Risk forecasts, which appears to stem from several econometric properties of the return distributions. With stochastic volatility models, we obtain better Value-at-Risk forecasts compared to GARCH. The quality varies over forecasting horizons and across markets. This indicates that, despite a regional proximity and homogeneity of the markets, index volatilities are driven by different factors.

Option Pricing with Stochastic Volatility and Jump Diffusion Processes

Directory of Open Access Journals (Sweden)

Radu Lupu

2006-03-01

Full Text Available Option pricing by the use of Black Scholes Merton (BSM model is based on the assumption that asset prices have a lognormal distribution. In spite of the use of these models on a large scale, both by practioners and academics, the assumption of lognormality is rejected by the history of returns. The objective of this article is to present the methods that developed after the Black Scholes Merton environment and deals with the option pricing model adjustment to the empirical properties of asset returns. The main models that appeared after BSM allowed for special changes of the returns that materialized in jump-diffusion and stochastic volatility processes. The article presents the foundations of risk neutral options evaluation and the empirical evidence that fed the amendment of the lognormal assumption in the first part and shows the evaluation procedure under the assumption of stock prices following the jump-diffusion process and the stochastic volatility process.

Smooth Solutions to Optimal Investment Models with Stochastic Volatilities and Portfolio Constraints

International Nuclear Information System (INIS)

Pham, H.

2002-01-01

This paper deals with an extension of Merton's optimal investment problem to a multidimensional model with stochastic volatility and portfolio constraints. The classical dynamic programming approach leads to a characterization of the value function as a viscosity solution of the highly nonlinear associated Bellman equation. A logarithmic transformation expresses the value function in terms of the solution to a semilinear parabolic equation with quadratic growth on the derivative term. Using a stochastic control representation and some approximations, we prove the existence of a smooth solution to this semilinear equation. An optimal portfolio is shown to exist, and is expressed in terms of the classical solution to this semilinear equation. This reduction is useful for studying numerical schemes for both the value function and the optimal portfolio. We illustrate our results with several examples of stochastic volatility models popular in the financial literature

AN EXAMINATION OF THE LEVERAGE EFFECT IN THE ISE WITH STOCHASTIC VOLATILITY MODEL

Directory of Open Access Journals (Sweden)

YELİZ YALÇIN

2013-06-01

Full Text Available The purpose of this paper is the asses the leverage effect of the Istanbul Stock Exchange within the Stochastic Volatility framework in the period 01.01.1990 – 11.08.2006. The relationship between risk and return is a well established phenomenon in Financial Econometerics. Both positive and negative relationship has been reported in the empirical literature. That use the conditional variance the empirical evidence provided in this paper from the Stochastic Volatility is to be negative feed back effect and statistically insignificant leverage effect.

A DG approach to the numerical solution of the Stein-Stein stochastic volatility option pricing model

Science.gov (United States)

Hozman, J.; Tichý, T.

2017-12-01

Stochastic volatility models enable to capture the real world features of the options better than the classical Black-Scholes treatment. Here we focus on pricing of European-style options under the Stein-Stein stochastic volatility model when the option value depends on the time, on the price of the underlying asset and on the volatility as a function of a mean reverting Orstein-Uhlenbeck process. A standard mathematical approach to this model leads to the non-stationary second-order degenerate partial differential equation of two spatial variables completed by the system of boundary and terminal conditions. In order to improve the numerical valuation process for a such pricing equation, we propose a numerical technique based on the discontinuous Galerkin method and the Crank-Nicolson scheme. Finally, reference numerical experiments on real market data illustrate comprehensive empirical findings on options with stochastic volatility.

Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models

NARCIS (Netherlands)

S. Peiris (Shelton); M. Asai (Manabu); M.J. McAleer (Michael)

2016-01-01

textabstractIn recent years fractionally differenced processes have received a great deal of attention due to its flexibility in financial applications with long memory. This paper considers a class of models generated by Gegenbauer polynomials, incorporating the long memory in stochastic volatility

Volatility in energy prices

International Nuclear Information System (INIS)

Duffie, D.

1999-01-01

This chapter with 58 references reviews the modelling and empirical behaviour of volatility in energy prices. Constant volatility and stochastic volatility are discussed. Markovian models of stochastic volatility are described and the different classes of Markovian stochastic volatility model are examined including auto-regressive volatility, option implied and forecasted volatility, Garch volatility, Egarch volatility, multivariate Garch volatility, and stochastic volatility and dynamic hedging policies. Other volatility models and option hedging are considered. The performance of several stochastic volatility models as applied to heating oil, light oil, natural gas, electricity and light crude oil are compared

A closed form solution for vulnerable options with Heston’s stochastic volatility

International Nuclear Information System (INIS)

Lee, Min-Ku; Yang, Sung-Jin; Kim, Jeong-Hoon

2016-01-01

Over-the-counter stock markets in the world have been growing rapidly and vulnerability to default risks of option holders traded in the over-the-counter markets became an important issue, in particular, since the global finance crisis and Eurozone crisis. This paper studies the pricing of European-type vulnerable options when the underlying asset follows the Heston dynamics. In this paper, we obtain a closed form analytic formula of the option price as a stochastic volatility extension of the classical Heston formula and find how the stochastic volatility effect on the Black–Scholes price as well as on the decreasing speed of the option price with credit risk depends on moneyness.

Volatility Degree Forecasting of Stock Market by Stochastic Time Strength Neural Network

Directory of Open Access Journals (Sweden)

Haiyan Mo

2013-01-01

Full Text Available In view of the applications of artificial neural networks in economic and financial forecasting, a stochastic time strength function is introduced in the backpropagation neural network model to predict the fluctuations of stock price changes. In this model, stochastic time strength function gives a weight for each historical datum and makes the model have the effect of random movement, and then we investigate and forecast the behavior of volatility degrees of returns for the Chinese stock market indexes and some global market indexes. The empirical research is performed in testing the prediction effect of SSE, SZSE, HSI, DJIA, IXIC, and S&P 500 with different selected volatility degrees in the established model.

A Hull and White Formula for a General Stochastic Volatility Jump-Diffusion Model with Applications to the Study of the Short-Time Behavior of the Implied Volatility

Directory of Open Access Journals (Sweden)

Elisa Alòs

2008-01-01

Full Text Available We obtain a Hull and White type formula for a general jump-diffusion stochastic volatility model, where the involved stochastic volatility process is correlated not only with the Brownian motion driving the asset price but also with the asset price jumps. Towards this end, we establish an anticipative Itô's formula, using Malliavin calculus techniques for Lévy processes on the canonical space. As an application, we show that the dependence of the volatility process on the asset price jumps has no effect on the short-time behavior of the at-the-money implied volatility skew.

CO_2 volatility impact on energy portfolio choice: A fully stochastic LCOE theory analysis

International Nuclear Information System (INIS)

Lucheroni, Carlo; Mari, Carlo

2017-01-01

Highlights: • Stochastic LCOE theory is an extension of the levelized cost of electricity analysis. • The fully stochastic analysis include stochastic processes for fossil fuels prices and CO_2 prices. • The nuclear asset is risky through uncertainty about construction times and it is used as a hedge. • Volatility of CO_2 prices has a strong influence on CO_2 emissions reduction. - Abstract: Market based pricing of CO_2 was designed to control CO_2 emissions by means of the price level, since high CO_2 price levels discourage emissions. In this paper, it will be shown that the level of uncertainty on CO_2 market prices, i.e. the volatility of CO_2 prices itself, has a strong influence not only on generation portfolio risk management but also on CO_2 emissions abatement. A reduction of emissions can be obtained when rational power generation capacity investors decide that the capacity expansion cost risk induced jointly by CO_2 volatility and fossil fuels prices volatility can be efficiently hedged adding to otherwise fossil fuel portfolios some nuclear power as a carbon free asset. This intriguing effect will be discussed using a recently introduced economic analysis tool, called stochastic LCOE theory. The stochastic LCOE theory used here was designed to investigate diversification effects on energy portfolios. In previous papers this theory was used to study diversification effects on portfolios composed of carbon risky fossil technologies and a carbon risk-free nuclear technology in a risk-reward trade-off frame. In this paper the stochastic LCOE theory will be extended to include uncertainty about nuclear power plant construction times, i.e. considering nuclear risky as well, this being the main uncertainty source of financial risk in nuclear technology. Two measures of risk will be used, standard deviation and CVaR deviation, to derive efficient frontiers for generation portfolios. Frontier portfolios will be analyzed in their implications on emissions

GPU Computing in Bayesian Inference of Realized Stochastic Volatility Model

International Nuclear Information System (INIS)

Takaishi, Tetsuya

2015-01-01

The realized stochastic volatility (RSV) model that utilizes the realized volatility as additional information has been proposed to infer volatility of financial time series. We consider the Bayesian inference of the RSV model by the Hybrid Monte Carlo (HMC) algorithm. The HMC algorithm can be parallelized and thus performed on the GPU for speedup. The GPU code is developed with CUDA Fortran. We compare the computational time in performing the HMC algorithm on GPU (GTX 760) and CPU (Intel i7-4770 3.4GHz) and find that the GPU can be up to 17 times faster than the CPU. We also code the program with OpenACC and find that appropriate coding can achieve the similar speedup with CUDA Fortran

Modeling energy price dynamics: GARCH versus stochastic volatility

International Nuclear Information System (INIS)

Chan, Joshua C.C.; Grant, Angelia L.

2016-01-01

We compare a number of GARCH and stochastic volatility (SV) models using nine series of oil, petroleum product and natural gas prices in a formal Bayesian model comparison exercise. The competing models include the standard models of GARCH(1,1) and SV with an AR(1) log-volatility process, as well as more flexible models with jumps, volatility in mean, leverage effects, and t distributed and moving average innovations. We find that: (1) SV models generally compare favorably to their GARCH counterparts; (2) the jump component and t distributed innovations substantially improve the performance of the standard GARCH, but are unimportant for the SV model; (3) the volatility feedback channel seems to be superfluous; (4) the moving average component markedly improves the fit of both GARCH and SV models; and (5) the leverage effect is important for modeling crude oil prices—West Texas Intermediate and Brent—but not for other energy prices. Overall, the SV model with moving average innovations is the best model for all nine series. - Highlights: • We compare a variety of GARCH and SV models for fitting nine series of energy prices. • We find that SV models generally compare favorably to their GARCH counterparts. • The SV model with moving average innovations is the best model for all nine series.

Estimation of stochastic volatility with long memory for index prices of FTSE Bursa Malaysia KLCI

Energy Technology Data Exchange (ETDEWEB)

Chen, Kho Chia; Kane, Ibrahim Lawal; Rahman, Haliza Abd [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310, Johor Bahru (Malaysia); Bahar, Arifah [UTM Centre for Industrial and Applied Mathematics (UTM-CIAM), Universiti Teknologi Malaysia, 81310, Johor Bahru and Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310, Johor Bahru (Malaysia); Ting, Chee-Ming [Center for Biomedical Engineering, Universiti Teknologi Malaysia, 81310, Johor Bahru (Malaysia)

2015-02-03

In recent years, modeling in long memory properties or fractionally integrated processes in stochastic volatility has been applied in the financial time series. A time series with structural breaks can generate a strong persistence in the autocorrelation function, which is an observed behaviour of a long memory process. This paper considers the structural break of data in order to determine true long memory time series data. Unlike usual short memory models for log volatility, the fractional Ornstein-Uhlenbeck process is neither a Markovian process nor can it be easily transformed into a Markovian process. This makes the likelihood evaluation and parameter estimation for the long memory stochastic volatility (LMSV) model challenging tasks. The drift and volatility parameters of the fractional Ornstein-Unlenbeck model are estimated separately using the least square estimator (lse) and quadratic generalized variations (qgv) method respectively. Finally, the empirical distribution of unobserved volatility is estimated using the particle filtering with sequential important sampling-resampling (SIR) method. The mean square error (MSE) between the estimated and empirical volatility indicates that the performance of the model towards the index prices of FTSE Bursa Malaysia KLCI is fairly well.

Estimation of stochastic volatility with long memory for index prices of FTSE Bursa Malaysia KLCI

Science.gov (United States)

Chen, Kho Chia; Bahar, Arifah; Kane, Ibrahim Lawal; Ting, Chee-Ming; Rahman, Haliza Abd

2015-02-01

In recent years, modeling in long memory properties or fractionally integrated processes in stochastic volatility has been applied in the financial time series. A time series with structural breaks can generate a strong persistence in the autocorrelation function, which is an observed behaviour of a long memory process. This paper considers the structural break of data in order to determine true long memory time series data. Unlike usual short memory models for log volatility, the fractional Ornstein-Uhlenbeck process is neither a Markovian process nor can it be easily transformed into a Markovian process. This makes the likelihood evaluation and parameter estimation for the long memory stochastic volatility (LMSV) model challenging tasks. The drift and volatility parameters of the fractional Ornstein-Unlenbeck model are estimated separately using the least square estimator (lse) and quadratic generalized variations (qgv) method respectively. Finally, the empirical distribution of unobserved volatility is estimated using the particle filtering with sequential important sampling-resampling (SIR) method. The mean square error (MSE) between the estimated and empirical volatility indicates that the performance of the model towards the index prices of FTSE Bursa Malaysia KLCI is fairly well.

Estimation of stochastic volatility with long memory for index prices of FTSE Bursa Malaysia KLCI

International Nuclear Information System (INIS)

Chen, Kho Chia; Kane, Ibrahim Lawal; Rahman, Haliza Abd; Bahar, Arifah; Ting, Chee-Ming

2015-01-01

In recent years, modeling in long memory properties or fractionally integrated processes in stochastic volatility has been applied in the financial time series. A time series with structural breaks can generate a strong persistence in the autocorrelation function, which is an observed behaviour of a long memory process. This paper considers the structural break of data in order to determine true long memory time series data. Unlike usual short memory models for log volatility, the fractional Ornstein-Uhlenbeck process is neither a Markovian process nor can it be easily transformed into a Markovian process. This makes the likelihood evaluation and parameter estimation for the long memory stochastic volatility (LMSV) model challenging tasks. The drift and volatility parameters of the fractional Ornstein-Unlenbeck model are estimated separately using the least square estimator (lse) and quadratic generalized variations (qgv) method respectively. Finally, the empirical distribution of unobserved volatility is estimated using the particle filtering with sequential important sampling-resampling (SIR) method. The mean square error (MSE) between the estimated and empirical volatility indicates that the performance of the model towards the index prices of FTSE Bursa Malaysia KLCI is fairly well

The world price of jump and volatility risk

NARCIS (Netherlands)

Driessen, J.J.A.G.; Maenhout, P.

2013-01-01

We study international integration of markets for jump and volatility risk, using index option data for the main global markets. To explain the cross-section of expected option returns we focus on return-based multi-factor models. For each market separately, we provide evidence that volatility and

Bayesian estimation of realized stochastic volatility model by Hybrid Monte Carlo algorithm

International Nuclear Information System (INIS)

Takaishi, Tetsuya

2014-01-01

The hybrid Monte Carlo algorithm (HMCA) is applied for Bayesian parameter estimation of the realized stochastic volatility (RSV) model. Using the 2nd order minimum norm integrator (2MNI) for the molecular dynamics (MD) simulation in the HMCA, we find that the 2MNI is more efficient than the conventional leapfrog integrator. We also find that the autocorrelation time of the volatility variables sampled by the HMCA is very short. Thus it is concluded that the HMCA with the 2MNI is an efficient algorithm for parameter estimations of the RSV model

Estimating Stochastic Volatility Models using Prediction-based Estimating Functions

DEFF Research Database (Denmark)

Lunde, Asger; Brix, Anne Floor

to the performance of the GMM estimator based on conditional moments of integrated volatility from Bollerslev and Zhou (2002). The case where the observed log-price process is contaminated by i.i.d. market microstructure (MMS) noise is also investigated. First, the impact of MMS noise on the parameter estimates from......In this paper prediction-based estimating functions (PBEFs), introduced in Sørensen (2000), are reviewed and PBEFs for the Heston (1993) stochastic volatility model are derived. The finite sample performance of the PBEF based estimator is investigated in a Monte Carlo study, and compared...... to correctly account for the noise are investigated. Our Monte Carlo study shows that the estimator based on PBEFs outperforms the GMM estimator, both in the setting with and without MMS noise. Finally, an empirical application investigates the possible challenges and general performance of applying the PBEF...

Stochastic reactive power market with volatility of wind power considering voltage security

International Nuclear Information System (INIS)

Kargarian, A.; Raoofat, M.

2011-01-01

While wind power generation is growing rapidly around the globe; its stochastic nature affects the system operation in many different aspects. In this paper, the impact of wind power volatility on the reactive power market is taken into account. The paper presents a novel stochastic method for optimal reactive power market clearing considering voltage security and volatile nature of the wind. The proposed optimization algorithm uses a multiobjective nonlinear programming technique to minimize market payment and simultaneously maximize voltage security margin. Considering a set of probable wind speeds, in the first stage, the proposed algorithm seeks to minimize expected system payment which is summation of reactive power payment and transmission loss cost. The object of the second stage is maximization of expected voltage security margin to increase the system loadability and security. Finally, in the last stage, a multiobjective function is presented to schedule the stochastic reactive power market using results of two previous stages. The proposed algorithm is applied to IEEE 14-bus test system. As a benchmark, Monte Carlo Simulation method is utilized to simulate the actual market of given period of time to evaluate results of the proposed algorithm, and satisfactory results are achieved. -- Highlights: →The paper proposes a new algorithm for stochastic reactive power market clearing. →The stochastic nature of the wind which impacts the system operation and market clearing process, is taken into account. →The paper suggests an expected voltage stability margin and optimizes it in conjunction with expected total market payment. →To clear the market with two mentioned objective functions, a three-stage multiobjective nonlinear programming is implemented. →Also, a simple method is suggested to determine a suitable priority coefficient between two individual objective functions.

A Generic Decomposition Formula for Pricing Vanilla Options under Stochastic Volatility Models

Directory of Open Access Journals (Sweden)

Raúl Merino

2015-01-01

Full Text Available We obtain a decomposition of the call option price for a very general stochastic volatility diffusion model, extending a previous decomposition formula for the Heston model. We realize that a new term arises when the stock price does not follow an exponential model. The techniques used for this purpose are nonanticipative. In particular, we also see that equivalent results can be obtained by using Functional Itô Calculus. Using the same generalizing ideas, we also extend to nonexponential models the alternative call option price decomposition formula written in terms of the Malliavin derivative of the volatility process. Finally, we give a general expression for the derivative of the implied volatility under both the anticipative and the nonanticipative cases.

Pricing European option with transaction costs under the fractional long memory stochastic volatility model

Science.gov (United States)

Wang, Xiao-Tian; Wu, Min; Zhou, Ze-Min; Jing, Wei-Shu

2012-02-01

This paper deals with the problem of discrete time option pricing using the fractional long memory stochastic volatility model with transaction costs. Through the 'anchoring and adjustment' argument in a discrete time setting, a European call option pricing formula is obtained.

Valuing a gas-fired power plant: A comparison of ordinary linear models, regime-switching approaches, and models with stochastic volatility

International Nuclear Information System (INIS)

Heydari, Somayeh; Siddiqui, Afzal

2010-01-01

Energy prices are often highly volatile with unexpected spikes. Capturing these sudden spikes may lead to more informed decision-making in energy investments, such as valuing gas-fired power plants, than ignoring them. In this paper, non-linear regime-switching models and models with mean-reverting stochastic volatility are compared with ordinary linear models. The study is performed using UK electricity and natural gas daily spot prices and suggests that with the aim of valuing a gas-fired power plant with and without operational flexibility, non-linear models with stochastic volatility, specifically for logarithms of electricity prices, provide better out-of-sample forecasts than both linear models and regime-switching models.

Multifactor analysis of multiscaling in volatility return intervals.

Science.gov (United States)

Wang, Fengzhong; Yamasaki, Kazuko; Havlin, Shlomo; Stanley, H Eugene

2009-01-01

We study the volatility time series of 1137 most traded stocks in the U.S. stock markets for the two-year period 2001-2002 and analyze their return intervals tau , which are time intervals between volatilities above a given threshold q . We explore the probability density function of tau , P_(q)(tau) , assuming a stretched exponential function, P_(q)(tau) approximately e;(-tau;(gamma)) . We find that the exponent gamma depends on the threshold in the range between q=1 and 6 standard deviations of the volatility. This finding supports the multiscaling nature of the return interval distribution. To better understand the multiscaling origin, we study how gamma depends on four essential factors, capitalization, risk, number of trades, and return. We show that gamma depends on the capitalization, risk, and return but almost does not depend on the number of trades. This suggests that gamma relates to the portfolio selection but not on the market activity. To further characterize the multiscaling of individual stocks, we fit the moments of tau , mu_(m) identical with(tautau);(m);(1m) , in the range of 10portfolio optimization.

Multifactor analysis of multiscaling in volatility return intervals

Science.gov (United States)

Wang, Fengzhong; Yamasaki, Kazuko; Havlin, Shlomo; Stanley, H. Eugene

2009-01-01

We study the volatility time series of 1137 most traded stocks in the U.S. stock markets for the two-year period 2001-2002 and analyze their return intervals τ , which are time intervals between volatilities above a given threshold q . We explore the probability density function of τ , Pq(τ) , assuming a stretched exponential function, Pq(τ)˜e-τγ . We find that the exponent γ depends on the threshold in the range between q=1 and 6 standard deviations of the volatility. This finding supports the multiscaling nature of the return interval distribution. To better understand the multiscaling origin, we study how γ depends on four essential factors, capitalization, risk, number of trades, and return. We show that γ depends on the capitalization, risk, and return but almost does not depend on the number of trades. This suggests that γ relates to the portfolio selection but not on the market activity. To further characterize the multiscaling of individual stocks, we fit the moments of τ , μm≡⟨(τ/⟨τ⟩)m⟩1/m , in the range of 10portfolio optimization.

The Pricing of European Options Under the Constant Elasticity of Variance with Stochastic Volatility

Science.gov (United States)

Bock, Bounghun; Choi, Sun-Yong; Kim, Jeong-Hoon

This paper considers a hybrid risky asset price model given by a constant elasticity of variance multiplied by a stochastic volatility factor. A multiscale analysis leads to an asymptotic pricing formula for both European vanilla option and a Barrier option near the zero elasticity of variance. The accuracy of the approximation is provided in a rigorous manner. A numerical experiment for implied volatilities shows that the hybrid model improves some of the well-known models in view of fitting the data for different maturities.

Volatility Discovery

DEFF Research Database (Denmark)

Dias, Gustavo Fruet; Scherrer, Cristina; Papailias, Fotis

The price discovery literature investigates how homogenous securities traded on different markets incorporate information into prices. We take this literature one step further and investigate how these markets contribute to stochastic volatility (volatility discovery). We formally show...... that the realized measures from homogenous securities share a fractional stochastic trend, which is a combination of the price and volatility discovery measures. Furthermore, we show that volatility discovery is associated with the way that market participants process information arrival (market sensitivity......). Finally, we compute volatility discovery for 30 actively traded stocks in the U.S. and report that Nyse and Arca dominate Nasdaq....

Range-based volatility, expected stock returns, and the low volatility anomaly

Science.gov (United States)

2017-01-01

One of the foundations of financial economics is the idea that rational investors will discount stocks with more risk (volatility), which will result in a positive relation between risk and future returns. However, the empirical evidence is mixed when determining how volatility is related to future returns. In this paper, we examine this relation using a range-based measure of volatility, which is shown to be theoretically, numerically, and empirically superior to other measures of volatility. In a variety of tests, we find that range-based volatility is negatively associated with expected stock returns. These results are robust to time-series multifactor models as well as cross-sectional tests. Our findings contribute to the debate about the direction of the relationship between risk and return and confirm the presence of the low volatility anomaly, or the anomalous finding that low volatility stocks outperform high volatility stocks. In other tests, we find that the lower returns associated with range-based volatility are driven by stocks with lottery-like characteristics. PMID:29190652

Range-based volatility, expected stock returns, and the low volatility anomaly.

Science.gov (United States)

Blau, Benjamin M; Whitby, Ryan J

2017-01-01

One of the foundations of financial economics is the idea that rational investors will discount stocks with more risk (volatility), which will result in a positive relation between risk and future returns. However, the empirical evidence is mixed when determining how volatility is related to future returns. In this paper, we examine this relation using a range-based measure of volatility, which is shown to be theoretically, numerically, and empirically superior to other measures of volatility. In a variety of tests, we find that range-based volatility is negatively associated with expected stock returns. These results are robust to time-series multifactor models as well as cross-sectional tests. Our findings contribute to the debate about the direction of the relationship between risk and return and confirm the presence of the low volatility anomaly, or the anomalous finding that low volatility stocks outperform high volatility stocks. In other tests, we find that the lower returns associated with range-based volatility are driven by stocks with lottery-like characteristics.

Range-based volatility, expected stock returns, and the low volatility anomaly.

Directory of Open Access Journals (Sweden)

Benjamin M Blau

Full Text Available One of the foundations of financial economics is the idea that rational investors will discount stocks with more risk (volatility, which will result in a positive relation between risk and future returns. However, the empirical evidence is mixed when determining how volatility is related to future returns. In this paper, we examine this relation using a range-based measure of volatility, which is shown to be theoretically, numerically, and empirically superior to other measures of volatility. In a variety of tests, we find that range-based volatility is negatively associated with expected stock returns. These results are robust to time-series multifactor models as well as cross-sectional tests. Our findings contribute to the debate about the direction of the relationship between risk and return and confirm the presence of the low volatility anomaly, or the anomalous finding that low volatility stocks outperform high volatility stocks. In other tests, we find that the lower returns associated with range-based volatility are driven by stocks with lottery-like characteristics.

Bayesian Option Pricing Framework with Stochastic Volatility for FX Data

Directory of Open Access Journals (Sweden)

Ying Wang

2016-12-01

Full Text Available The application of stochastic volatility (SV models in the option pricing literature usually assumes that the market has sufficient option data to calibrate the model’s risk-neutral parameters. When option data are insufficient or unavailable, market practitioners must estimate the model from the historical returns of the underlying asset and then transform the resulting model into its risk-neutral equivalent. However, the likelihood function of an SV model can only be expressed in a high-dimensional integration, which makes the estimation a highly challenging task. The Bayesian approach has been the classical way to estimate SV models under the data-generating (physical probability measure, but the transformation from the estimated physical dynamic into its risk-neutral counterpart has not been addressed. Inspired by the generalized autoregressive conditional heteroskedasticity (GARCH option pricing approach by Duan in 1995, we propose an SV model that enables us to simultaneously and conveniently perform Bayesian inference and transformation into risk-neutral dynamics. Our model relaxes the normality assumption on innovations of both return and volatility processes, and our empirical study shows that the estimated option prices generate realistic implied volatility smile shapes. In addition, the volatility premium is almost flat across strike prices, so adding a few option data to the historical time series of the underlying asset can greatly improve the estimation of option prices.

Joint Pricing of VIX and SPX Options with Stochastic Volatility and Jump models

DEFF Research Database (Denmark)

Kokholm, Thomas; Stisen, Martin

2015-01-01

to existing literature, we derive numerically simpler VIX option and futures pricing formulas in the case of the SVJ model. Moreover, the paper is the first to study the pricing performance of three widely used models to SPX options and VIX derivatives.......With the existence of active markets for volatility derivatives and options on the underlying instrument, the need for models that are able to price these markets consistently has increased. Although pricing formulas for VIX and vanilla options are now available for commonly employed models...... and variance (SVJJ) are jointly calibrated to market quotes on SPX and VIX options together with VIX futures. The full flexibility of having jumps in both returns and volatility added to a stochastic volatility model is essential. Moreover, we find that the SVJJ model with the Feller condition imposed...

The Risk-Return Tradeoff and Leverage Effect in a Stochastic Volatility-in-Mean Model

DEFF Research Database (Denmark)

Christensen, Bent Jesper; Posedel, Petra

We study the risk premium and leverage effect in the S&P500 market using the stochastic volatility-in-mean model of Barndor¤-Nielsen & Shephard (2001). The Merton (1973, 1980) equilibrium asset pricing condition linking the conditional mean and conditional variance of discrete time returns is rei...

The Shape and Term Structure of the Index Option Smirk: Why Multifactor Stochastic Volatility Models Work so Well

DEFF Research Database (Denmark)

Christoffersen, Peter; Heston, Steven; Jacobs, Kris

variation in the smirk, the model also provides more flexible modeling of the volatility term structure. Our empirical results indicate that the model improves on the benchmark Heston model by 24% in-sample and 23% out-of-sample. The better fit results from improvements in the modeling of the term structure...... dimension as well as the moneyness dimension....

Multi-factor authentication using quantum communication

Science.gov (United States)

Hughes, Richard John; Peterson, Charles Glen; Thrasher, James T.; Nordholt, Jane E.; Yard, Jon T.; Newell, Raymond Thorson; Somma, Rolando D.

2018-02-06

Multi-factor authentication using quantum communication ("QC") includes stages for enrollment and identification. For example, a user enrolls for multi-factor authentication that uses QC with a trusted authority. The trusted authority transmits device factor information associated with a user device (such as a hash function) and user factor information associated with the user (such as an encrypted version of a user password). The user device receives and stores the device factor information and user factor information. For multi-factor authentication that uses QC, the user device retrieves its stored device factor information and user factor information, then transmits the user factor information to the trusted authority, which also retrieves its stored device factor information. The user device and trusted authority use the device factor information and user factor information (more specifically, information such as a user password that is the basis of the user factor information) in multi-factor authentication that uses QC.

Multifactor Authentication: Its Time Has Come

Directory of Open Access Journals (Sweden)

Jim Reno

2013-08-01

Full Text Available Transactions of any value must be authenticated to help prevent online crime. Even seemingly innocent interactions, such as social media postings, can have serious consequences if used fraudulently. A key problem in modern online interactions is establishing the identity of the user without alienating the user. Historically, almost all online authentications have been implemented using simple passwords, but increasingly these methods are under attack. Multifactor authentication requires the presentation of two or more of the three authentication factor types: “What you know”, “What you have”, and “What you are”. After presentation, each factor must be validated by the other party for authentication to occur. Multifactor authentication is a potential solution to the authentication problem, and it is beginning to be implemented at websites operated by well-known companies. This article surveys the different mechanisms used to implement multifactor authentication. How a site chooses to implement multifactor authentication affects security as well as the overall user experience.

Pricing stock options under stochastic volatility and interest rates with efficient method of moments estimation

NARCIS (Netherlands)

Jiang, George J.; Sluis, Pieter J. van der

1999-01-01

While the stochastic volatility (SV) generalization has been shown to improve the explanatory power over the Black-Scholes model, empirical implications of SV models on option pricing have not yet been adequately tested. The purpose of this paper is to first estimate a multivariate SV model using

Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models

Directory of Open Access Journals (Sweden)

Shelton Peiris

2017-12-01

Full Text Available This paper considers a flexible class of time series models generated by Gegenbauer polynomials incorporating the long memory in stochastic volatility (SV components in order to develop the General Long Memory SV (GLMSV model. We examine the corresponding statistical properties of this model, discuss the spectral likelihood estimation and investigate the finite sample properties via Monte Carlo experiments. We provide empirical evidence by applying the GLMSV model to three exchange rate return series and conjecture that the results of out-of-sample forecasts adequately confirm the use of GLMSV model in certain financial applications.

On multilevel RBF collocation to solve nonlinear PDEs arising from endogenous stochastic volatility models

Science.gov (United States)

Bastani, Ali Foroush; Dastgerdi, Maryam Vahid; Mighani, Abolfazl

2018-06-01

The main aim of this paper is the analytical and numerical study of a time-dependent second-order nonlinear partial differential equation (PDE) arising from the endogenous stochastic volatility model, introduced in [Bensoussan, A., Crouhy, M. and Galai, D., Stochastic equity volatility related to the leverage effect (I): equity volatility behavior. Applied Mathematical Finance, 1, 63-85, 1994]. As the first step, we derive a consistent set of initial and boundary conditions to complement the PDE, when the firm is financed by equity and debt. In the sequel, we propose a Newton-based iteration scheme for nonlinear parabolic PDEs which is an extension of a method for solving elliptic partial differential equations introduced in [Fasshauer, G. E., Newton iteration with multiquadrics for the solution of nonlinear PDEs. Computers and Mathematics with Applications, 43, 423-438, 2002]. The scheme is based on multilevel collocation using radial basis functions (RBFs) to solve the resulting locally linearized elliptic PDEs obtained at each level of the Newton iteration. We show the effectiveness of the resulting framework by solving a prototypical example from the field and compare the results with those obtained from three different techniques: (1) a finite difference discretization; (2) a naive RBF collocation and (3) a benchmark approximation, introduced for the first time in this paper. The numerical results confirm the robustness, higher convergence rate and good stability properties of the proposed scheme compared to other alternatives. We also comment on some possible research directions in this field.

Multi-factor authentication

Science.gov (United States)

Hamlet, Jason R; Pierson, Lyndon G

2014-10-21

Detection and deterrence of spoofing of user authentication may be achieved by including a cryptographic fingerprint unit within a hardware device for authenticating a user of the hardware device. The cryptographic fingerprint unit includes an internal physically unclonable function ("PUF") circuit disposed in or on the hardware device, which generates a PUF value. Combining logic is coupled to receive the PUF value, combines the PUF value with one or more other authentication factors to generate a multi-factor authentication value. A key generator is coupled to generate a private key and a public key based on the multi-factor authentication value while a decryptor is coupled to receive an authentication challenge posed to the hardware device and encrypted with the public key and coupled to output a response to the authentication challenge decrypted with the private key.

Entropy measure of credit risk in highly correlated markets

Science.gov (United States)

Gottschalk, Sylvia

2017-07-01

We compare the single and multi-factor structural models of corporate default by calculating the Jeffreys-Kullback-Leibler divergence between their predicted default probabilities when asset correlations are either high or low. Single-factor structural models assume that the stochastic process driving the value of a firm is independent of that of other companies. A multi-factor structural model, on the contrary, is built on the assumption that a single firm's value follows a stochastic process correlated with that of other companies. Our main results show that the divergence between the two models increases in highly correlated, volatile, and large markets, but that it is closer to zero in small markets, when asset correlations are low and firms are highly leveraged. These findings suggest that during periods of financial instability, when asset volatility and correlations increase, one of the models misreports actual default risk.

A discontinuous Galerkin method for numerical pricing of European options under Heston stochastic volatility

Science.gov (United States)

Hozman, J.; Tichý, T.

2016-12-01

The paper is based on the results from our recent research on multidimensional option pricing problems. We focus on European option valuation when the price movement of the underlying asset is driven by a stochastic volatility following a square root process proposed by Heston. The stochastic approach incorporates a new additional spatial variable into this model and makes it very robust, i.e. it provides a framework to price a variety of options that is closer to reality. The main topic is to present the numerical scheme arising from the concept of discontinuous Galerkin methods and applicable to the Heston option pricing model. The numerical results are presented on artificial benchmarks as well as on reference market data.

A Guide to the Multifactored Evaluation (MFE).

Science.gov (United States)

Ohio Coalition for the Education of Children with Disabilities, Marion.

This guide provides Ohio parents of children with disabilities with information on multifactored evaluations. It begins by discussing the Intervention Assistance Team and what occurs at the assistance team meeting. It also explains that to begin the multifactored evaluation process, the parent must complete a "Request for Parent Consent for…

Portfolio Optimization under Local-Stochastic Volatility: Coefficient Taylor Series Approximations & Implied Sharpe Ratio

OpenAIRE

Lorig, Matthew; Sircar, Ronnie

2015-01-01

We study the finite horizon Merton portfolio optimization problem in a general local-stochastic volatility setting. Using model coefficient expansion techniques, we derive approximations for the both the value function and the optimal investment strategy. We also analyze the `implied Sharpe ratio' and derive a series approximation for this quantity. The zeroth-order approximation of the value function and optimal investment strategy correspond to those obtained by Merton (1969) when the risky...

Stochastic price modeling of high volatility, mean-reverting, spike-prone commodities: The Australian wholesale spot electricity market

International Nuclear Information System (INIS)

Higgs, Helen; Worthington, Andrew

2008-01-01

It is commonly known that wholesale spot electricity markets exhibit high price volatility, strong mean-reversion and frequent extreme price spikes. This paper employs a basic stochastic model, a mean-reverting model and a regime-switching model to capture these features in the Australian national electricity market (NEM), comprising the interconnected markets of New South Wales, Queensland, South Australia and Victoria. Daily spot prices from 1 January 1999 to 31 December 2004 are employed. The results show that the regime-switching model outperforms the basic stochastic and mean-reverting models. Electricity prices are also found to exhibit stronger mean-reversion after a price spike than in the normal period, and price volatility is more than fourteen times higher in spike periods than in normal periods. The probability of a spike on any given day ranges between 5.16% in NSW and 9.44% in Victoria

Equilibrium Asset and Option Pricing under Jump-Diffusion Model with Stochastic Volatility

Directory of Open Access Journals (Sweden)

Xinfeng Ruan

2013-01-01

Full Text Available We study the equity premium and option pricing under jump-diffusion model with stochastic volatility based on the model in Zhang et al. 2012. We obtain the pricing kernel which acts like the physical and risk-neutral densities and the moments in the economy. Moreover, the exact expression of option valuation is derived by the Fourier transformation method. We also discuss the relationship of central moments between the physical measure and the risk-neutral measure. Our numerical results show that our model is more realistic than the previous model.

Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility

Czech Academy of Sciences Publication Activity Database

Baruník, Jozef; Kukačka, Jiří

2015-01-01

Roč. 15, č. 6 (2015), s. 959-973 ISSN 1469-7688 R&D Projects: GA ČR GA402/09/0965; GA ČR GA13-32263S EU Projects: European Commission 612955 - FINMAP Institutional support: RVO:67985556 Keywords : Stochastic cusp catastrophe model * Realized volatility * Bifurcations * Stock market crash Subject RIV: AH - Economics Impact factor: 0.794, year: 2015 http://library.utia.cas.cz/separaty/2014/E/barunik-0434202.pdf

Quantifying credit portfolio losses under multi-factor models

NARCIS (Netherlands)

G. Colldeforns-Papiol (Gemma); L. Ortiz Gracia (Luis); C.W. Oosterlee (Kees)

2018-01-01

textabstractIn this work, we investigate the challenging problem of estimating credit risk measures of portfolios with exposure concentration under the multi-factor Gaussian and multi-factor t-copula models. It is well-known that Monte Carlo (MC) methods are highly demanding from the computational

Stochastic model of financial markets reproducing scaling and memory in volatility return intervals

Science.gov (United States)

Gontis, V.; Havlin, S.; Kononovicius, A.; Podobnik, B.; Stanley, H. E.

2016-11-01

We investigate the volatility return intervals in the NYSE and FOREX markets. We explain previous empirical findings using a model based on the interacting agent hypothesis instead of the widely-used efficient market hypothesis. We derive macroscopic equations based on the microscopic herding interactions of agents and find that they are able to reproduce various stylized facts of different markets and different assets with the same set of model parameters. We show that the power-law properties and the scaling of return intervals and other financial variables have a similar origin and could be a result of a general class of non-linear stochastic differential equations derived from a master equation of an agent system that is coupled by herding interactions. Specifically, we find that this approach enables us to recover the volatility return interval statistics as well as volatility probability and spectral densities for the NYSE and FOREX markets, for different assets, and for different time-scales. We find also that the historical S&P500 monthly series exhibits the same volatility return interval properties recovered by our proposed model. Our statistical results suggest that human herding is so strong that it persists even when other evolving fluctuations perturbate the financial system.

Multi- factor volatility of security at Charles Schwab Corporation ...

African Journals Online (AJOL)

This paper examined the rate of returns required by investors who invested at Charles Schwab (Discount Brokerage firm) from 30th September, 1987 to 29th August, 1997. The methodology adapted involved the use of a multi-factor stochastic model; APT. The study shows a low systematic risk of the security. There was ...

Measuring multifactor productivity growth

Czech Academy of Sciences Publication Activity Database

Wölfl, A.; Hájková, Dana

-, 2007/5 (2007), s. 1-45 Institutional research plan: CEZ:AV0Z70850503 Keywords : multifactor productivity growth * GDP growth * measuring Subject RIV: AH - Economics http://www.oecd.org/dataoecd/61/17/39522985.pdf

Photon-counting multifactor optical encryption and authentication

International Nuclear Information System (INIS)

Pérez-Cabré, E; Millán, M S; Mohammed, E A; Saadon, H L

2015-01-01

The multifactor optical encryption authentication method [Opt. Lett., 31 721-3 (2006)] reinforces optical security by allowing the simultaneous authentication of up to four factors. In this work, the photon-counting imaging technique is applied to the multifactor encrypted function so that a sparse phase-only distribution is generated for the encrypted data. The integration of both techniques permits an increased capacity for signal hiding with simultaneous data reduction for better fulfilling the general requirements of protection, storage and transmission. Cryptanalysis of the proposed method is carried out in terms of chosen-plaintext and chosen-ciphertext attacks. Although the multifactor authentication process is not substantially altered by those attacks, its integration with the photon-counting imaging technique prevents from possible partial disclosure of any encrypted factor, thus increasing the security level of the overall process. Numerical experiments and results are provided and discussed. (paper)

Essays on nonparametric econometrics of stochastic volatility

NARCIS (Netherlands)

Zu, Y.

2012-01-01

Volatility is a concept that describes the variation of financial returns. Measuring and modelling volatility dynamics is an important aspect of financial econometrics. This thesis is concerned with nonparametric approaches to volatility measurement and volatility model validation.

Pricing of American Put Option under a Jump Diffusion Process with Stochastic Volatility in an Incomplete Market

Directory of Open Access Journals (Sweden)

Shuang Li

2014-01-01

Full Text Available We study the pricing of American options in an incomplete market in which the dynamics of the underlying risky asset is driven by a jump diffusion process with stochastic volatility. By employing a risk-minimization criterion, we obtain the Radon-Nikodym derivative for the minimal martingale measure and consequently a linear complementarity problem (LCP for American option price. An iterative method is then established to solve the LCP problem for American put option price. Our numerical results show that the model and numerical scheme are robust in capturing the feature of incomplete finance market, particularly the influence of market volatility on the price of American options.

Estimation and analysis of multifactor productivity in truck transportation : 1987 - 2003

Science.gov (United States)

2009-02-01

The analysis has three objectives: 1) to estimate multifactor : productivity (MFP) in truck transportation during : 1987-2003; 2) to examine changes in multifactor productivity : in U.S. truck transportation, over time, and : to compare these changes...

Numerical Simulation of the Heston Model under Stochastic Correlation

Directory of Open Access Journals (Sweden)

Long Teng

2017-12-01

Full Text Available Stochastic correlation models have become increasingly important in financial markets. In order to be able to price vanilla options in stochastic volatility and correlation models, in this work, we study the extension of the Heston model by imposing stochastic correlations driven by a stochastic differential equation. We discuss the efficient algorithms for the extended Heston model by incorporating stochastic correlations. Our numerical experiments show that the proposed algorithms can efficiently provide highly accurate results for the extended Heston by including stochastic correlations. By investigating the effect of stochastic correlations on the implied volatility, we find that the performance of the Heston model can be proved by including stochastic correlations.

Volatility Mean Reversion and the Market Price of Volatility Risk

NARCIS (Netherlands)

Boswijk, H.P.

2001-01-01

This paper analyzes sources of derivative pricing errors in a stochastic volatility model estimated on stock return data. It is shown that such pricing errors may reflect the existence of a market price of volatility risk, but also may be caused by estimation errors due to a slow mean reversion in

Latent Integrated Stochastic Volatility, Realized Volatility, and Implied Volatility: A State Space Approach

DEFF Research Database (Denmark)

Bach, Christian; Christensen, Bent Jesper

process is downward biased. Implied volatility performs better than any of the alternative realized measures when forecasting future integrated volatility. The results are largely similar across the stock market (S&P 500), bond market (30-year U.S. T-bond), and foreign currency exchange market ($/£ )....

Virtual volatility

Science.gov (United States)

Silva, A. Christian; Prange, Richard E.

2007-03-01

We introduce the concept of virtual volatility. This simple but new measure shows how to quantify the uncertainty in the forecast of the drift component of a random walk. The virtual volatility also is a useful tool in understanding the stochastic process for a given portfolio. In particular, and as an example, we were able to identify mean reversion effect in our portfolio. Finally, we briefly discuss the potential practical effect of the virtual volatility on an investor asset allocation strategy.

"An Asymptotic Expansion Approach to Currency Options with a Market Model of Interest Rates under Stochastic Volatility Processes of Spot Exchange Rates"

OpenAIRE

Akihiko Takahashi; Kohta Takehara

2007-01-01

This paper proposes an asymptotic expansion scheme of currency options with a libor market model of interest rates and stochastic volatility models of spot exchange rates. In particular, we derive closed-form approximation formulas for the density functions of the underlying assets and for pricing currency options based on the third order asymptotic expansion scheme; we do not model a foreign exchange rate's variance such as in Heston[1993], but its volatility that follows a general time-inho...

Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities

DEFF Research Database (Denmark)

Bollerslev, Tim; Gibson, Michael; Zhou, Hao

experiment confirms that the procedure works well in practice. Implementing the procedure with actual S&P500 option-implied volatilities and high-frequency five-minute-based realized volatilities indicates significant temporal dependencies in the estimated stochastic volatility risk premium, which we in turn...

Nonparametric methods for volatility density estimation

NARCIS (Netherlands)

Es, van Bert; Spreij, P.J.C.; Zanten, van J.H.

2009-01-01

Stochastic volatility modelling of financial processes has become increasingly popular. The proposed models usually contain a stationary volatility process. We will motivate and review several nonparametric methods for estimation of the density of the volatility process. Both models based on

Pricing Volatility Referenced Assets

Directory of Open Access Journals (Sweden)

Alan De Genaro Dario

2006-12-01

Full Text Available Volatility swaps are contingent claims on future realized volatility. Variance swaps are similar instruments on future realized variance, the square of future realized volatility. Unlike a plain vanilla option, whose volatility exposure is contaminated by its asset price dependence, volatility and variance swaps provide a pure exposure to volatility alone. This article discusses the risk-neutral valuation of volatility and variance swaps based on the framework outlined in the Heston (1993 stochastic volatility model. Additionally, the Heston (1993 model is calibrated for foreign currency options traded at BMF and its parameters are used to price swaps on volatility and variance of the BRL / USD exchange rate.

Change of time methods in quantitative finance

CERN Document Server

Swishchuk, Anatoliy

2016-01-01

This book is devoted to the history of Change of Time Methods (CTM), the connections of CTM to stochastic volatilities and finance, fundamental aspects of the theory of CTM, basic concepts, and its properties. An emphasis is given on many applications of CTM in financial and energy markets, and the presented numerical examples are based on real data. The change of time method is applied to derive the well-known Black-Scholes formula for European call options, and to derive an explicit option pricing formula for a European call option for a mean-reverting model for commodity prices. Explicit formulas are also derived for variance and volatility swaps for financial markets with a stochastic volatility following a classical and delayed Heston model. The CTM is applied to price financial and energy derivatives for one-factor and multi-factor alpha-stable Levy-based models. Readers should have a basic knowledge of probability and statistics, and some familiarity with stochastic processes, such as Brownian motion, ...

GARCH Option Valuation: Theory and Evidence

DEFF Research Database (Denmark)

Christoffersen, Peter; Jacobs, Kris; Ornthanalai, Chayawat

We survey the theory and empirical evidence on GARCH option valuation models. Our treatment includes the range of functional forms available for the volatility dynamic, multifactor models, nonnormal shock distributions as well as style of pricing kernels typically used. Various strategies...... for empirical implementation are laid out and we also discuss the links between GARCH and stochastic volatility models. In the appendix we provide Matlab computer code for option pricing via Monte Carlo simulation for nonaffine models as well as Fourier inversion for affine models....

Recent advances in ambit stochastics with a view towards tempo-spatial stochastic volatility/intermittency

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole E.; Benth, Fred Espen; Veraart, Almut

Ambit stochastics is the name for the theory and applications of ambit fields and ambit processes and constitutes a new research area in stochastics for tempo-spatial phenomena. This paper gives an overview of the main findings in ambit stochastics up to date and establishes new results on genera...

Understanding Interest Rate Volatility

DEFF Research Database (Denmark)

Volker, Desi

This thesis is the result of my Ph.D. studies at the Department of Finance of the Copenhagen Business School. It consists of three essays covering topics related to the term structure of interest rates, monetary policy and interest rate volatility. The rst essay, \\Monetary Policy Uncertainty...... and Interest Rates", examines the role of monetary policy uncertainty on the term structure of interest rates. The second essay, \\A Regime-Switching A ne Term Structure Model with Stochastic Volatility" (co-authored with Sebastian Fux), investigates the ability of the class of regime switching models...... with and without stochastic volatility to capture the main stylized features of U.S. interest rates. The third essay, \\Variance Risk Premia in the Interest Rate Swap Market", investigates the time-series and cross-sectional properties of the compensation demanded for holding interest rate variance risk. The essays...

On the effects of world stock market and oil price shocks on food prices: An empirical investigation based on TVP-VAR models with stochastic volatility

International Nuclear Information System (INIS)

Jebabli, Ikram; Arouri, Mohamed; Teulon, Frédéric

2014-01-01

Transmission of price shocks from one market to another one has long been investigated in the economic literature. However, studies have namely dealt with the relationship between financial and energy markets. With the recent changes in market conditions, investors, policy-makers and interest groups are giving special attention to food market. This paper aims at analyzing shock transmission between international food, energy and financial markets and to provide some insights into the volatility behavior during the past years and discuss its implications for portfolio management. To do this, we present a new time varying parameter VAR (TVP-VAR) model with stochastic volatility approach which provides extreme flexibility with a parsimonious specification. We resort also to a generalized vector autoregressive framework in which forecast-error variance decompositions are invariant to the variable ordering for the assessment of total and directional volatility spillovers. Our main findings suggest that volatility spillovers increase considerably during crisis and, namely after mid-2008, when stock markets become net transmitter of volatility shocks while crude oil becomes a net receiver. Shocks to crude oil or MSCI markets have immediate and short-term impacts on food markets which are emphasized during the financial crisis period. Moreover, we show that augmenting a diversified portfolio of food commodities with crude oil or stocks significantly increases its risk-adjusted performance. - Highlights: • We study shock transmission between food, energy and financial markets. • We use a new time-varying parameter VAR model with stochastic volatility. • There is volatility spillover from oil and stock markets to food. • Volatility spillovers increase considerably during crisis, namely after mid-2008. • Augmenting a portfolio of foods with oil or stocks increases its performance

Homotopy Analysis Method for Boundary-Value Problem of Turbo Warrant Pricing under Stochastic Volatility

Directory of Open Access Journals (Sweden)

Hoi Ying Wong

2013-01-01

Full Text Available Turbo warrants are liquidly traded financial derivative securities in over-the-counter and exchange markets in Asia and Europe. The structure of turbo warrants is similar to barrier options, but a lookback rebate will be paid if the barrier is crossed by the underlying asset price. Therefore, the turbo warrant price satisfies a partial differential equation (PDE with a boundary condition that depends on another boundary-value problem (BVP of PDE. Due to the highly complicated structure of turbo warrants, their valuation presents a challenging problem in the field of financial mathematics. This paper applies the homotopy analysis method to construct an analytic pricing formula for turbo warrants under stochastic volatility in a PDE framework.

Medical imaging technology shock and volatility of macro economics: Analysis using a three-sector dynamical stochastic general equilibrium REC model.

Science.gov (United States)

Han, Shurong; Huang, Yeqing

2017-07-07

The study analysed the medical imaging technology business cycle from 1981 to 2009 and found that the volatility of consumption in Chinese medical imaging business was higher than that of the developed countries. The volatility of gross domestic product (GDP) and the correlation between consumption and GDP is also higher than that of the developed countries. Prior to the early 1990s the volatility of consumption is even higher than GDP. This fact makes it difficult to explain the volatile market using the standard one sector real economic cycle (REC) model. Contrary to the other domestic studies, this study considers a three-sector dynamical stochastic general equilibrium REC model. In this model there are two consumption sectors, whereby one is labour intensive and another is capital intensive. The more capital intensive investment sector only introduces technology shocks in the medical imaging market. Our response functions and Monte-Carlo simulation results show that the model can explain 90% of the volatility of consummation relative to GDP, and explain the correlation between consumption and GDP. The results demonstrated the significant correlation between the technological reform in medical imaging and volatility in the labour market on Chinese macro economy development.

Testing for a Common Volatility Process and Information Spillovers in Bivariate Financial Time Series Models

NARCIS (Netherlands)

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),

Humps in the volatility structure of the crude oil futures market: New evidence

International Nuclear Information System (INIS)

Chiarella, Carl; Kang, Boda; Nikitopoulos, Christina Sklibosios; Tô, Thuy-Duong

2013-01-01

This paper analyses the volatility structure of commodity derivatives markets. The model encompasses hump-shaped, unspanned stochastic volatility, which entails a finite-dimensional affine model for the commodity futures curve and quasi-analytical prices for options on commodity futures. Using an extensive database of crude oil futures and futures options spanning 21 years, we find the presence of hump-shaped, partially spanned stochastic volatility in the crude oil market. The hump shaped feature is more pronounced when the market is more volatile, and delivers better pricing as well as hedging performance under various dynamic factor hedging schemes. - Highlights: • This paper analyses the volatility structure of commodity derivatives markets. • 21-years of data on crude oil futures and futures options is used. • The crude oil futures market has hump-shaped, unspanned stochastic volatility. • The hump shaped feature is more pronounced when the market is more volatile. • Hump shape delivers better pricing and hedging compared to exponential decay

Volatile decision dynamics: experiments, stochastic description, intermittency control and traffic optimization

Science.gov (United States)

Helbing, Dirk; Schönhof, Martin; Kern, Daniel

2002-06-01

The coordinated and efficient distribution of limited resources by individual decisions is a fundamental, unsolved problem. When individuals compete for road capacities, time, space, money, goods, etc, they normally make decisions based on aggregate rather than complete information, such as TV news or stock market indices. In related experiments, we have observed a volatile decision dynamics and far-from-optimal payoff distributions. We have also identified methods of information presentation that can considerably improve the overall performance of the system. In order to determine optimal strategies of decision guidance by means of user-specific recommendations, a stochastic behavioural description is developed. These strategies manage to increase the adaptibility to changing conditions and to reduce the deviation from the time-dependent user equilibrium, thereby enhancing the average and individual payoffs. Hence, our guidance strategies can increase the performance of all users by reducing overreaction and stabilizing the decision dynamics. These results are highly significant for predicting decision behaviour, for reaching optimal behavioural distributions by decision support systems and for information service providers. One of the promising fields of application is traffic optimization.

Electricity price modeling with stochastic time change

International Nuclear Information System (INIS)

Borovkova, Svetlana; Schmeck, Maren Diane

2017-01-01

In this paper, we develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. This technique allows us to incorporate the characteristic features of electricity prices (such as seasonal volatility, time varying mean reversion and seasonally occurring price spikes) into the model in an elegant and economically justifiable way. The stochastic time change introduces stochastic as well as deterministic (e.g., seasonal) features in the price process' volatility and in the jump component. We specify the base process as a mean reverting jump diffusion and the time change as an absolutely continuous stochastic process with seasonal component. The activity rate of the stochastic time change can be related to the factors that influence supply and demand. Here we use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change, and show that this choice leads to realistic price paths. We derive properties of the resulting price process and develop the model calibration procedure. We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths by Monte Carlo simulations. We show that the simulated price process matches the distributional characteristics of the observed electricity prices in periods of both high and low demand. - Highlights: • We develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. • We incorporate the characteristic features of electricity prices, such as seasonal volatility and spikes into the model. • We use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change • We derive properties of the resulting price process and develop the model calibration procedure. • We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths.

Estimation and prediction under local volatility jump-diffusion model

Science.gov (United States)

Kim, Namhyoung; Lee, Younhee

2018-02-01

Volatility is an important factor in operating a company and managing risk. In the portfolio optimization and risk hedging using the option, the value of the option is evaluated using the volatility model. Various attempts have been made to predict option value. Recent studies have shown that stochastic volatility models and jump-diffusion models reflect stock price movements accurately. However, these models have practical limitations. Combining them with the local volatility model, which is widely used among practitioners, may lead to better performance. In this study, we propose a more effective and efficient method of estimating option prices by combining the local volatility model with the jump-diffusion model and apply it using both artificial and actual market data to evaluate its performance. The calibration process for estimating the jump parameters and local volatility surfaces is divided into three stages. We apply the local volatility model, stochastic volatility model, and local volatility jump-diffusion model estimated by the proposed method to KOSPI 200 index option pricing. The proposed method displays good estimation and prediction performance.

Weather Derivatives and Stochastic Modelling of Temperature

Directory of Open Access Journals (Sweden)

Fred Espen Benth

2011-01-01

Full Text Available We propose a continuous-time autoregressive model for the temperature dynamics with volatility being the product of a seasonal function and a stochastic process. We use the Barndorff-Nielsen and Shephard model for the stochastic volatility. The proposed temperature dynamics is flexible enough to model temperature data accurately, and at the same time being analytically tractable. Futures prices for commonly traded contracts at the Chicago Mercantile Exchange on indices like cooling- and heating-degree days and cumulative average temperatures are computed, as well as option prices on them.

Option pricing under stochastic volatility: the exponential Ornstein–Uhlenbeck model

International Nuclear Information System (INIS)

Perelló, Josep; Masoliver, Jaume; Sircar, Ronnie

2008-01-01

We study the pricing problem for a European call option when the volatility of the underlying asset is random and follows the exponential Ornstein–Uhlenbeck model. The random diffusion model proposed is a two-dimensional market process that takes a log-Brownian motion to describe price dynamics and an Ornstein–Uhlenbeck subordinated process describing the randomness of the log-volatility. We derive an approximate option price that is valid when (i) the fluctuations of the volatility are larger than its normal level, (ii) the volatility presents a slow driving force, toward its normal level and, finally, (iii) the market price of risk is a linear function of the log-volatility. We study the resulting European call price and its implied volatility for a range of parameters consistent with daily Dow Jones index data

A Jump-Diffusion Model with Stochastic Volatility and Durations

DEFF Research Database (Denmark)

Wei, Wei; Pelletier, Denis

jumps in two ways: as exogenous sampling intervals, and through the interaction with volatility. We adopt a bivariate Ornstein-Ulenbeck process to model intraday volatility and conditional duration. We develop a MCMC algorithm for the inference on irregularly spaced multivariate processes with jumps...

A Range-Based Multivariate Model for Exchange Rate Volatility

NARCIS (Netherlands)

B. Tims (Ben); R.J. Mahieu (Ronald)

2003-01-01

textabstractIn this paper we present a parsimonious multivariate model for exchange rate volatilities based on logarithmic high-low ranges of daily exchange rates. The multivariate stochastic volatility model divides the log range of each exchange rate into two independent latent factors, which are

The Role of Permanent and Transitory Components in Business Cycle Volatility Moderation

OpenAIRE

Korenok, Oleg; Radchenko, Stanislav

2004-01-01

The paper examines the processes underlying economic fluctuations by investigating the volatility moderation of U.S. economy in the early 1980's. We decompose the volatility decline using a dynamic factor framework into a common stochastic trend, common transitory component and idiosyncratic components. We find that the moderation of business cycle was a result of the moderation in transitory and idiosyncratic components. Our results suggest that important part of stochastic process that driv...

Modelling of volatility in monetary transmission mechanism

Energy Technology Data Exchange (ETDEWEB)

Dobešová, Anna; Klepáč, Václav; Kolman, Pavel [Department of Statistics and Operation Analysis, Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1, 61300, Brno (Czech Republic); Bednářová, Petra [Institute of Technology and Business, Okružní 517/10, 370 01, České Budějovice (Czech Republic)

2015-03-10

The aim of this paper is to compare different approaches to modeling of volatility in monetary transmission mechanism. For this purpose we built time-varying parameter VAR (TVP-VAR) model with stochastic volatility and VAR-DCC-GARCH model with conditional variance. The data from three European countries are included in the analysis: the Czech Republic, Germany and Slovakia. Results show that VAR-DCC-GARCH system captures higher volatility of observed variables but main trends and detected breaks are generally identical in both approaches.

Modelling of volatility in monetary transmission mechanism

International Nuclear Information System (INIS)

Dobešová, Anna; Klepáč, Václav; Kolman, Pavel; Bednářová, Petra

2015-01-01

The aim of this paper is to compare different approaches to modeling of volatility in monetary transmission mechanism. For this purpose we built time-varying parameter VAR (TVP-VAR) model with stochastic volatility and VAR-DCC-GARCH model with conditional variance. The data from three European countries are included in the analysis: the Czech Republic, Germany and Slovakia. Results show that VAR-DCC-GARCH system captures higher volatility of observed variables but main trends and detected breaks are generally identical in both approaches

Cross-sectional returns with volatility regimes from a diverse portfolio of emerging and developed equity indices

Directory of Open Access Journals (Sweden)

Paweł Sakowski

2016-10-01

Full Text Available This article aims to extend evaluation of the classic multifactor model of Carhart (1997 for the case of global equity indices and to expand analysis performed in Sakowski et. al. (2015. Our intention is to test several modifications of these models to take into account different dynamics of equity excess returns between emerging and developed equity indices. Proposed extensions include a volatility regime switching mechanism (using dummy variables and the Markov approach and the fifth risk factor based on realized volatility of index returns. Moreover, instead of using data for stocks of a particular market (which is a common approach in the literature, we check performance of these models for weekly data of 81 world investable equity indices in the period of 2000-2015. Such an approach is proposed to estimate an equity risk premium for a single country. Empirical evidence reveals important differences between results for classical models estimated on single stocks (either in international or US-only frameworks and models evaluated for equity indices. Additionally, we observe substantial discrepancies between results for developed countries and emerging markets. Finally, using weekly data for the last 15 years we illustrate the importance of model risk and data overfitting effects when drawing conclusions upon results of multifactor models.

Volatility smile and stochastic arbitrage returns

OpenAIRE

Sergei Fedotov; Stephanos Panayides

2004-01-01

The purpose of this work is to explore the role that random arbitrage opportunities play in pricing financial derivatives. We use a non-equilibrium model to set up a stochastic portfolio, and for the random arbitrage return, we choose a stationary ergodic random process rapidly varying in time. We exploit the fact that option price and random arbitrage returns change on different time scales which allows us to develop an asymptotic pricing theory involving the central limit theorem for random...

A Range-Based Multivariate Model for Exchange Rate Volatility

OpenAIRE

Tims, Ben; Mahieu, Ronald

2003-01-01

textabstractIn this paper we present a parsimonious multivariate model for exchange rate volatilities based on logarithmic high-low ranges of daily exchange rates. The multivariate stochastic volatility model divides the log range of each exchange rate into two independent latent factors, which are interpreted as the underlying currency specific components. Due to the normality of logarithmic volatilities the model can be estimated conveniently with standard Kalman filter techniques. Our resu...

LEFT-WING ASYMPTOTICS OF THE IMPLIED VOLATILITY IN THE PRESENCE OF ATOMS

OpenAIRE

ARCHIL GULISASHVILI

2015-01-01

The paper considers the asymptotic behavior of the implied volatility in stochastic asset price models with atoms. In such models, the asset price distribution has a singular component at zero. Examples of models with atoms include the constant elasticity of variance (CEV) model, jump-to-default models, and stochastic models described by processes stopped at the first hitting time of zero. For models with atoms, the behavior of the implied volatility at large strikes is similar to that in mod...

Behavioural Biometrics for Multi-factor Authentication in Biomedicine

Czech Academy of Sciences Publication Activity Database

Schlenker, Anna; Šárek, M.

2012-01-01

Roč. 8, č. 5 (2012), s. 19-24 ISSN 1801-5603 Grant - others:GA MŠk(CZ) LM2010005; GA UK(CZ) SVV-2012-264513 Institutional support: RVO:67985807 Keywords : biometric s * anatomical-physiological biometric s * behavioural biometric s * multi-factor authentication * keystroke dynamics * mouse dynamics Subject RIV: IN - Informatics, Computer Science http://www.ejbi.org/img/ejbi/2012/5/Schlenker_en.pdf

A novel Monte Carlo approach to hybrid local volatility models

NARCIS (Netherlands)

A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)

2017-01-01

textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.

Using Artificial Intelligence Techniques to Implement a Multifactor Authentication System

Directory of Open Access Journals (Sweden)

Jackson Phiri

2011-08-01

Full Text Available The recent years have seen a rise in the number of cases of cyber-crime committed through identity theft and fraud. To address this problem, this paper uses adaptive neural-fuzzy inference system, fuzzy logic and artificial neural network to implement a multifactor authentication system through a technique of information fusion. To begin with, the identity attributes are mined using the three corpora from three major sources namely the social networks, a set of questionnaires and application forms from the various services offered both in the real and cyberspace. The statistical information generated by the corpora is then used to compose an identity attribute metric model. The composed identity attributes metrics values classified as biometrics, device metrics and pseudo metrics are then fused at the score level through a technique of information fusion in a multifactor authentication system by using each of the above artificial intelligence technologies and the results compared.

Mellin Transform Method for European Option Pricing with Hull-White Stochastic Interest Rate

Directory of Open Access Journals (Sweden)

Ji-Hun Yoon

2014-01-01

Full Text Available Even though interest rates fluctuate randomly in the marketplace, many option-pricing models do not fully consider their stochastic nature owing to their generally limited impact on option prices. However, stochastic dynamics in stochastic interest rates may have a significant impact on option prices as we take account of issues of maturity, hedging, or stochastic volatility. In this paper, we derive a closed form solution for European options in Black-Scholes model with stochastic interest rate using Mellin transform techniques.

Security enhanced multi-factor biometric authentication scheme using bio-hash function.

Directory of Open Access Journals (Sweden)

Younsung Choi

Full Text Available With the rapid development of personal information and wireless communication technology, user authentication schemes have been crucial to ensure that wireless communications are secure. As such, various authentication schemes with multi-factor authentication have been proposed to improve the security of electronic communications. Multi-factor authentication involves the use of passwords, smart cards, and various biometrics to provide users with the utmost privacy and data protection. Cao and Ge analyzed various authentication schemes and found that Younghwa An's scheme was susceptible to a replay attack where an adversary masquerades as a legal server and a user masquerading attack where user anonymity is not provided, allowing an adversary to execute a password change process by intercepting the user's ID during login. Cao and Ge improved upon Younghwa An's scheme, but various security problems remained. This study demonstrates that Cao and Ge's scheme is susceptible to a biometric recognition error, slow wrong password detection, off-line password attack, user impersonation attack, ID guessing attack, a DoS attack, and that their scheme cannot provide session key agreement. Then, to address all weaknesses identified in Cao and Ge's scheme, this study proposes a security enhanced multi-factor biometric authentication scheme and provides a security analysis and formal analysis using Burrows-Abadi-Needham logic. Finally, the efficiency analysis reveals that the proposed scheme can protect against several possible types of attacks with only a slightly high computational cost.

Security enhanced multi-factor biometric authentication scheme using bio-hash function.

Science.gov (United States)

Choi, Younsung; Lee, Youngsook; Moon, Jongho; Won, Dongho

2017-01-01

With the rapid development of personal information and wireless communication technology, user authentication schemes have been crucial to ensure that wireless communications are secure. As such, various authentication schemes with multi-factor authentication have been proposed to improve the security of electronic communications. Multi-factor authentication involves the use of passwords, smart cards, and various biometrics to provide users with the utmost privacy and data protection. Cao and Ge analyzed various authentication schemes and found that Younghwa An's scheme was susceptible to a replay attack where an adversary masquerades as a legal server and a user masquerading attack where user anonymity is not provided, allowing an adversary to execute a password change process by intercepting the user's ID during login. Cao and Ge improved upon Younghwa An's scheme, but various security problems remained. This study demonstrates that Cao and Ge's scheme is susceptible to a biometric recognition error, slow wrong password detection, off-line password attack, user impersonation attack, ID guessing attack, a DoS attack, and that their scheme cannot provide session key agreement. Then, to address all weaknesses identified in Cao and Ge's scheme, this study proposes a security enhanced multi-factor biometric authentication scheme and provides a security analysis and formal analysis using Burrows-Abadi-Needham logic. Finally, the efficiency analysis reveals that the proposed scheme can protect against several possible types of attacks with only a slightly high computational cost.

Security enhanced multi-factor biometric authentication scheme using bio-hash function

Science.gov (United States)

Lee, Youngsook; Moon, Jongho

2017-01-01

With the rapid development of personal information and wireless communication technology, user authentication schemes have been crucial to ensure that wireless communications are secure. As such, various authentication schemes with multi-factor authentication have been proposed to improve the security of electronic communications. Multi-factor authentication involves the use of passwords, smart cards, and various biometrics to provide users with the utmost privacy and data protection. Cao and Ge analyzed various authentication schemes and found that Younghwa An’s scheme was susceptible to a replay attack where an adversary masquerades as a legal server and a user masquerading attack where user anonymity is not provided, allowing an adversary to execute a password change process by intercepting the user’s ID during login. Cao and Ge improved upon Younghwa An’s scheme, but various security problems remained. This study demonstrates that Cao and Ge’s scheme is susceptible to a biometric recognition error, slow wrong password detection, off-line password attack, user impersonation attack, ID guessing attack, a DoS attack, and that their scheme cannot provide session key agreement. Then, to address all weaknesses identified in Cao and Ge’s scheme, this study proposes a security enhanced multi-factor biometric authentication scheme and provides a security analysis and formal analysis using Burrows-Abadi-Needham logic. Finally, the efficiency analysis reveals that the proposed scheme can protect against several possible types of attacks with only a slightly high computational cost. PMID:28459867

Forecasting prices and price volatility in the Nordic electricity market

International Nuclear Information System (INIS)

2001-01-01

We develop a stochastic model for long term price forecasting in a competitive electricity market environment. It is demonstrated both theoretically and through model simulations that non-stochastic models may give biased forecasts both with respect to price level and volatility. In the paper, the model concept is applied on the restructured Nordic electricity market. It is specially in peak load hours that a stochastic model formulation provides significantly different results than an expected value model. (author)

A Multifactor Secure Authentication System for Wireless Payment

Science.gov (United States)

Sanyal, Sugata; Tiwari, Ayu; Sanyal, Sudip

Organizations are deploying wireless based online payment applications to expand their business globally, it increases the growing need of regulatory requirements for the protection of confidential data, and especially in internet based financial areas. Existing internet based authentication systems often use either the Web or the Mobile channel individually to confirm the claimed identity of the remote user. The vulnerability is that access is based on only single factor authentication which is not secure to protect user data, there is a need of multifactor authentication. This paper proposes a new protocol based on multifactor authentication system that is both secure and highly usable. It uses a novel approach based on Transaction Identification Code and SMS to enforce another security level with the traditional Login/password system. The system provides a highly secure environment that is simple to use and deploy with in a limited resources that does not require any change in infrastructure or underline protocol of wireless network. This Protocol for Wireless Payment is extended as a two way authentications system to satisfy the emerging market need of mutual authentication and also supports secure B2B communication which increases faith of the user and business organizations on wireless financial transaction using mobile devices.

Neuro-Inspired Computing with Stochastic Electronics

KAUST Repository

Naous, Rawan

2016-01-06

The extensive scaling and integration within electronic systems have set the standards for what is addressed to as stochastic electronics. The individual components are increasingly diverting away from their reliable behavior and producing un-deterministic outputs. This stochastic operation highly mimics the biological medium within the brain. Hence, building on the inherent variability, particularly within novel non-volatile memory technologies, paves the way for unconventional neuromorphic designs. Neuro-inspired networks with brain-like structures of neurons and synapses allow for computations and levels of learning for diverse recognition tasks and applications.

MÉTODOS DISCRETOS Y CONTINUOS PARA MODELAR LA DENSIDAD DE PROBABILIDAD DE LA VOLATILIDAD ESTOCÁSTICA DE LOS RENDIMIENTOS DE SERIES FINANCIERAS DISCRETE AND CONTINUOUS METHODS FOR MODELING FINANCIAL SERIES YIELDING STOCHASTIC VOLATILITY PROBABILITY DENSITY

Directory of Open Access Journals (Sweden)

Carlos Alexánder Grajales Correa

2007-07-01

Full Text Available En este trabajo se consideran los rendimientos diarios de un activo financiero con el propósito de modelar y comparar la densidad de probabilidad de la volatilidad estocástica de los retornos. Para tal fin, se proponen los modelos ARCH y sus extensiones, que son en tiempo discreto, así como un modelo empírico de volatilidad estocástica, desarrollado por Paul Wilmott. Para el caso discreto se muestran los modelos que permiten estimar la volatilidad condicional heterocedástica en un instante t del tiempo, t∈[1,T]. En el caso continuo se asocia un proceso de difusión de Itô a la volatilidad estocástica de la serie financiera, lo cual posibilita discretizar dicho proceso y simularlo para obtener densidades de probabilidad empíricas de la volatilidad. Finalmente se ilustran y se comparan los resultados obtenidos con las metodologías expuestas para el caso de las series financieras S&P 500 de EEUU, el Índice de Precios y Cotizaciones de la Bolsa Mexicana de Valores (IPC y el IGBC de Colombia.This work considers daily yields of financial assets in order to model and compare returns stochastic volatility probability density. For such aim, ARCH models and its extensions are proposed - they are in discrete time- as well as an Empirical Stochastic Volatility Model, developed by Paul Wilmott. For the discrete case, models that allow to estimate heteroscedasticity conditional volatility in a time, t, t,t∈[1,T], are shown. In the continuous case, there is an association of an Itô diffusion process to stochastic volatility of the financial series, which allows to write a discretization of this process and to simulate it to obtain empirical probabilistic densities from the volatility. Finally the results are illustrated and compared with methodologies exposed by the case of the financial series S&P 500 of the U.S.A., Index of Prices and Quotations of stock-market Mexican of Values (IPC and IGBC of Colombia.

No-arbitrage, leverage and completeness in a fractional volatility model

Science.gov (United States)

Vilela Mendes, R.; Oliveira, M. J.; Rodrigues, A. M.

2015-02-01

When the volatility process is driven by fractional noise one obtains a model which is consistent with the empirical market data. Depending on whether the stochasticity generators of log-price and volatility are independent or are the same, two versions of the model are obtained with different leverage behaviors. Here, the no-arbitrage and completeness properties of the models are rigorously studied.

Cautionary Note on Reporting Eta-Squared Values from Multifactor ANOVA Designs

Science.gov (United States)

Pierce, Charles A.; Block, Richard A.; Aguinis, Herman

2004-01-01

The authors provide a cautionary note on reporting accurate eta-squared values from multifactor analysis of variance (ANOVA) designs. They reinforce the distinction between classical and partial eta-squared as measures of strength of association. They provide examples from articles published in premier psychology journals in which the authors…

A contribution to the systematics of stochastic volatility models

Czech Academy of Sciences Publication Activity Database

Slanina, František

2010-01-01

Roč. 389, č. 16 (2010), s. 3230-3239 ISSN 0378-4371 R&D Projects: GA MŠk OC09078 Institutional research plan: CEZ:AV0Z10100520 Keywords : fluctuations * econophysics * stochastic differential equations Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 1.521, year: 2010

Aggregate Multi-Factor Productivity: Measurement Issues in OECD Countries

OpenAIRE

Egert, Balazs

2018-01-01

This paper analyses for 34 OECD countries the extent to which the calculation of aggregate multi-factor productivity (MFP) is sensitive to alternative parameterisations. The starting point is the definition of MFP used in previous work in the OECD’s Economics Department (e.g. Johansson et al. 2013). They include alternative MFP measures, with human capital included or excluded, with different measures of Purchasing Power Parity (PPP) exchange rates, using time-varying capital depreciation rat...

Effectiveness of monetary and macroprudential shocks on consumer credit growth and volatility in Turkey

Directory of Open Access Journals (Sweden)

Meltem Gulenay Chadwick

2018-06-01

Full Text Available This paper proposes a panel VAR model to uncover the effect of monetary policy and macroprudential tightening probability on general purpose loans, housing loans, vehicle loans, credit cards and their respective volatilities in Turkey. To conduct our analysis, first, we compare a number of stochastic volatility models using our loan and credit card series in a formal Bayesian model comparison exercise, in order to determine the best volatility model for our series. Second we disclose the latent probability of macroprudential tightening from the binary information of policy episodes, using an instrumental variable probit model estimated by conditional maximum likelihood with heteroscedasticity robust standard errors. Lastly we estimate the dynamic impact of monetary policy and macroprudential measures using a panel VAR, incorporating the latent probability of tightening episodes, credit growth, industrial production growth, loan rates, inflation and credit growth volatilities into the endogenous system of equations. We conclude that macroprudential tightening is effective in dampening credit growth, credit growth volatility and reducing consumer price inflation. Besides, this effect is more prominent when macroprudential tools are administered in coordination with monetary policy. Keywords: Consumer loans, Monetary policy, Macroprudential policy, Stochastic volatility models, Credit growth volatility, IV probit model, Panel VAR model, JEL classification: C54, E44, E52

Stochastic Modelling, Analysis, and Simulations of the Solar Cycle Dynamic Process

Science.gov (United States)

Turner, Douglas C.; Ladde, Gangaram S.

2018-03-01

Analytical solutions, discretization schemes and simulation results are presented for the time delay deterministic differential equation model of the solar dynamo presented by Wilmot-Smith et al. In addition, this model is extended under stochastic Gaussian white noise parametric fluctuations. The introduction of stochastic fluctuations incorporates variables affecting the dynamo process in the solar interior, estimation error of parameters, and uncertainty of the α-effect mechanism. Simulation results are presented and analyzed to exhibit the effects of stochastic parametric volatility-dependent perturbations. The results generalize and extend the work of Hazra et al. In fact, some of these results exhibit the oscillatory dynamic behavior generated by the stochastic parametric additative perturbations in the absence of time delay. In addition, the simulation results of the modified stochastic models influence the change in behavior of the very recently developed stochastic model of Hazra et al.

The Impact of Jump Distributions on the Implied Volatility of Variance

DEFF Research Database (Denmark)

Nicolato, Elisa; Pisani, Camilla; Pedersen, David Sloth

2017-01-01

We consider a tractable affine stochastic volatility model that generalizes the seminal Heston (1993) model by augmenting it with jumps in the instantaneous variance process. In this framework, we consider both realized variance options and VIX options, and we examine the impact of the distribution...... of jumps on the associated implied volatility smile. We provide sufficient conditions for the asymptotic behavior of the implied volatility of variance for small and large strikes. In particular, by selecting alternative jump distributions, we show that one can obtain fundamentally different shapes...

Understanding Interest Rate Volatility

OpenAIRE

Volker, Desi

2016-01-01

This thesis is the result of my Ph.D. studies at the Department of Finance of the Copenhagen Business School. It consists of three essays covering topics related to the term structure of interest rates, monetary policy and interest rate volatility. The rst essay, \\Monetary Policy Uncertainty and Interest Rates", examines the role of monetary policy uncertainty on the term structure of interest rates. The second essay, \\A Regime-Switching A ne Term Structure Model with Stochast...

Effects of Single and Multifactor Treatments with Elevated Temperature, CO2 and Ozone on Oilseed Rape and Barley

DEFF Research Database (Denmark)

Clausen, Sabine Karin; Frenck, Georg; van der Linden, Leon Gareth

2011-01-01

We investigated the effect of elevated [CO2], [O3] and temperature on plant productivity and if these climate factors interacted with each other in multifactor treatments. The climate effects were studied in 14 different cultivars/lines of European spring oilseed rape (Brassica napus L.) and spring...... barley (Hordeum vulgare L.). Seven genotypes of each species were cultivated in six single- and multifactor treatments with ambient or elevated CO2 (385 ppm and 700 ppm), O3 (20 ppb and 60 ppb) and temperature (12/19 °C and 17/24 °C). Growth and production parameters were measured. Elevated CO2 increased....... A significantly decreased yield and thousand grain weight was also seen in barley due to elevated O3. The multifactor combination of elevated CO2, O3 and temperature showed a decrease in growth and production in the two species, though not statistically significant for all parameters. This trend suggests...

Explaining output volatility: The case of taxation

DEFF Research Database (Denmark)

Posch, Olaf

the second moment of output growth rates without (long-run) effects on the first moment. Taking the model to the data, we exploit observed heterogeneity patterns to estimate effects of tax rates on macro volatility using panel estimation, explicitly modeling the unobserved variance process. We find a strong......This paper studies the effects of taxation on output volatility in OECD countries to shed light on the sources of observed heterogeneity over time and across countries. To this end, we derive tax effects on macro aggregates in a stochastic neoclassical model. As a result, taxes are shown to affect...... positive effects....

Models for S&P500 Dynamics: Evidence from Realized Volatility, Daily Returns, and Option Prices

DEFF Research Database (Denmark)

Christoffersen, Peter; Jacobs, Kris; Mimouni, Karim

in the search for alternative specifications. We then estimate the models using maximum likelihood on S&P500 returns. Finally, we employ nonlinear least squares on a panel of option data. In comparison with earlier studies that explicitly solve the filtering problem, we analyze a more comprehensive option data......Most recent empirical option valuation studies build on the affine square root (SQR) stochastic volatility model. The SQR model is a convenient choice, because it yields closed-form solutions for option prices. However, relatively little is known about the resulting biases. We investigate...... alternatives to the SQR model, by comparing its empirical performance with that of five different but equally parsimonious stochastic volatility models. We provide empirical evidence from three different sources. We first use realized volatilities to assess the properties of the SQR model and to guide us...

Effect evaluation of a multifactor community intervention to reduce falls among older persons

NARCIS (Netherlands)

Wijlhuizen, G.J.; Bois, P. du; Dommelen, P. van; Hopman-Rock, M.

2007-01-01

The objective of the study was to evaluate the effectiveness of a multifactor and multimethod community intervention programme to reduce falls among older persons by at least 20%. In a pre-test-post test design, self-reported falls were registered for 10 months in the intervention community and two

Multifactor-Driven Hierarchical Routing on Enterprise Service Bus

Science.gov (United States)

Mi, Xueqiang; Tang, Xinhuai; Yuan, Xiaozhou; Chen, Delai; Luo, Xiangfeng

Message Routing is the foremost functionality on Enterprise Service Bus (ESB), but current ESB products don't provide an expected solution for it, especially in the aspects of runtime route change mechanism and service orchestration model. In order to solve the above drawbacks, this paper proposes a multifactor-driven hierarchical routing (MDHR) model. MDHR defines three layers for message routing on ESB. Message layer gives the original support for message delivery. Application layer can integration or encapsulate some legacy applications or un-standard services. Business layer introduces business model to supplies developers with a business rule configuration, which supports enterprise integration patterns and simplifies the service orchestration on ESB.

Estimation of volatility of selected oil production projects

International Nuclear Information System (INIS)

Costa Lima, Gabriel A.; Suslick, Saul B.

2006-01-01

In oil project valuation and investment decision-making, volatility is a key parameter, but it is difficult to estimate. From a traditional investment viewpoint, volatility reduces project value because it increases its discount rate via a higher risk premium. Contrarily, according to the real-option pricing theory, volatility may aggregate value to the project, since the downside potential is limited whereas the upside is theoretically unbounded. However, the estimation of project volatility is very complicated since there is not a historical series of project values. In such cases, many analysts assume that oil price volatility is equal to that of project. In order to overcome such problems, in this paper an alternative numerical method based on present value of future cash flows and Monte Carlo simulation is proposed to estimate the volatility of projects. This method is applied to estimate the volatility of 12 deep-water offshore oil projects considering that oil price will evolve according to one of two stochastic processes: Geometric Brownian Motion and Mean-Reverting Motion. Results indicate that the volatility of commodity usually undervalue that of project. For the set of offshore projects analyzed in this paper, project volatility is at least 79% higher than that of oil prices and increases dramatically in those cases of high capital expenditures and low price. (author)

The memory of volatility

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Kai R. Wenger

2018-03-01

Full Text Available The focus of the volatility literature on forecasting and the predominance of theconceptually simpler HAR model over long memory stochastic volatility models has led to the factthat the actual degree of memory estimates has rarely been considered. Estimates in the literaturerange roughly between 0.4 and 0.6 - that is from the higher stationary to the lower non-stationaryregion. This difference, however, has important practical implications - such as the existence or nonexistenceof the fourth moment of the return distribution. Inference on the memory order is complicatedby the presence of measurement error in realized volatility and the potential of spurious long memory.In this paper we provide a comprehensive analysis of the memory in variances of international stockindices and exchange rates. On the one hand, we find that the variance of exchange rates is subject tospurious long memory and the true memory parameter is in the higher stationary range. Stock indexvariances, on the other hand, are free of low frequency contaminations and the memory is in the lowernon-stationary range. These results are obtained using state of the art local Whittle methods that allowconsistent estimation in presence of perturbations or low frequency contaminations.

Application of stochastic differential geometry to the term structure of interst rates in developed markets

Energy Technology Data Exchange (ETDEWEB)

Taranenko, Y.; Barnes, C.

1996-12-31

This paper deals with further developments of the new theory that applies stochastic differential geometry (SDG) to dynamics of interest rates. We examine mathematical constraints on the evolution of interest rate volatilities that arise from stochastic differential calculus under assumptions of an arbitrage free evolution of zero coupon bonds and developed markets (i.e., none of the party/factor can drive the whole market). The resulting new theory incorporates the Heath-Jarrow-Morton (HJM) model of interest rates and provides new equations for volatilities which makes the system of equations for interest rates and volatilities complete and self consistent. It results in much smaller amount of volatility data that should be guessed for the SDG model as compared to the HJM model. Limited analysis of the market volatility data suggests that the assumption of the developed market is violated around maturity of two years. Such maturities where the assumptions of the SDG model are violated are suggested to serve as boundaries at which volatilities should be specified independently from the model. Our numerical example with two boundaries (two years and five years) qualitatively resembles the market behavior. Under some conditions solutions of the SDG model become singular that may indicate market crashes. More detail comparison with the data is needed before the theory can be established or refuted.

Empirical method to measure stochasticity and multifractality in nonlinear time series

Science.gov (United States)

Lin, Chih-Hao; Chang, Chia-Seng; Li, Sai-Ping

2013-12-01

An empirical algorithm is used here to study the stochastic and multifractal nature of nonlinear time series. A parameter can be defined to quantitatively measure the deviation of the time series from a Wiener process so that the stochasticity of different time series can be compared. The local volatility of the time series under study can be constructed using this algorithm, and the multifractal structure of the time series can be analyzed by using this local volatility. As an example, we employ this method to analyze financial time series from different stock markets. The result shows that while developed markets evolve very much like an Ito process, the emergent markets are far from efficient. Differences about the multifractal structures and leverage effects between developed and emergent markets are discussed. The algorithm used here can be applied in a similar fashion to study time series of other complex systems.

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

Science.gov (United States)

Abumeri, Galib H.; Chamis, Christos C.

2010-01-01

Complex material behavior is represented by a single equation of product form to account for interaction among the various factors. The factors are selected by the physics of the problem and the environment that the model is to represent. For example, different factors will be required for each to represent temperature, moisture, erosion, corrosion, etc. It is important that the equation represent the physics of the behavior in its entirety accurately. The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the external launch tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points - the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used were obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated. The problem lies in how to represent the divot weight with a single equation. A unique solution to this problem is a multi-factor equation of product form. Each factor is of the following form (1 xi/xf)ei, where xi is the initial value, usually at ambient conditions, xf the final value, and ei the exponent that makes the curve represented unimodal that meets the initial and final values. The exponents are either evaluated by test data or by technical judgment. A minor disadvantage may be the selection of exponents in the absence of any empirical data. This form has been used successfully in describing the foam ejected in simulated space environmental conditions. Seven factors were required

Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk

DEFF Research Database (Denmark)

Usset, Joseph L; Raghavan, Rama; Tyrer, Jonathan P

2016-01-01

and non-obese women. METHODS: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy...... Future work is needed to develop powerful statistical methods able to detect these complex interactions. IMPACT: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC...

Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis

International Nuclear Information System (INIS)

Du Xiaodong; Yu, Cindy L.; Hayes, Dermot J.

2011-01-01

This paper assesses factors that potentially influence the volatility of crude oil prices and the possible linkage between this volatility and agricultural commodity markets. Stochastic volatility models are applied to weekly crude oil, corn, and wheat futures prices from November 1998 to January 2009. Model parameters are estimated using Bayesian Markov Chain Monte Carlo methods. Speculation, scalping, and petroleum inventories are found to be important in explaining the volatility of crude oil prices. Several properties of crude oil price dynamics are established, including mean-reversion, an asymmetry between returns and volatility, volatility clustering, and infrequent compound jumps. We find evidence of volatility spillover among crude oil, corn, and wheat markets after the fall of 2006. This can be largely explained by tightened interdependence between crude oil and these commodity markets induced by ethanol production.

Dynamic Multi-Factor Credit Risk Model with Fat-Tailed Factors

Czech Academy of Sciences Publication Activity Database

Gapko, Petr; Šmíd, Martin

2012-01-01

Roč. 62, č. 2 (2012), s. 125-140 ISSN 0015-1920 R&D Projects: GA ČR GD402/09/H045; GA ČR GA402/09/0965 Grant - others:Univerzita Karlova(CZ) GAUK 46108 Institutional research plan: CEZ:AV0Z10750506 Keywords : credit risk * probability of default * loss given default * credit loss * credit loss distribution * Basel II Subject RIV: AH - Economics Impact factor: 0.340, year: 2012 http://library.utia.cas.cz/separaty/2012/E/smid-dynamic multi-factor credit risk model with fat-tailed factors.pdf

Volatility Spillovers in Capesize Forward Freight Agreement Markets

Directory of Open Access Journals (Sweden)

Xiaoxing Gong

2016-01-01

Full Text Available This paper is to investigate spillovers in the Capesize forward freight agreements (FFAs markets before and after the global financial crisis. The paper chooses four Capesize voyage routes FFAs (C3, C4, C5, and C7, two time-charter routes FFAs (BCIT/C average, BPI T/C average, and spot rates as research subjects, covering the periods 3 January 2006 to 24 December 2015. This paper applies Volatility Spillover Multivariate Stochastic Volatility (VS-MSV model to analyze volatility spillover effects and estimates the parameters via software of Bayesian inference using Gibbs Sampling (BUGS, the deviance information criterion (DIC used for goodness-of-fit model. The results suggest that there are volatility spillover effects in certain Capesize FFAs routes, and the effects from spot rates to FFAs take place before crisis, yet they are bilateral after crisis. With the development of shipping markets, the correlations between FFAs and spot rate are enhanced, and it seems that the effects depend on market information and traders’ behavior. So practitioners could make decisions according to the spillovers.

Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices

Science.gov (United States)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah@Rozita

2014-06-01

Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stable information ratio.

Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices

Energy Technology Data Exchange (ETDEWEB)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita [School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor (Malaysia)

2014-06-19

Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stable information ratio.

Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices

International Nuclear Information System (INIS)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita

2014-01-01

Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stable information ratio

Multifactor Screener in the 2000 National Health Interview Survey Cancer Control Supplement: Uses of Screener Estimates

Science.gov (United States)

Dietary intake estimates derived from the Multifactor Screener are rough estimates of usual intake of fruits and vegetables, fiber, calcium, servings of dairy, and added sugar. These estimates are not as accurate as those from more detailed methods (e.g., 24-hour recalls).

Multi-Factor Authentication: A Survey

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Aleksandr Ometov

2018-01-01

Full Text Available Today, digitalization decisively penetrates all the sides of the modern society. One of the key enablers to maintain this process secure is authentication. It covers many different areas of a hyper-connected world, including online payments, communications, access right management, etc. This work sheds light on the evolution of authentication systems towards Multi-Factor Authentication (MFA starting from Single-Factor Authentication (SFA and through Two-Factor Authentication (2FA. Particularly, MFA is expected to be utilized for human-to-everything interactions by enabling fast, user-friendly, and reliable authentication when accessing a service. This paper surveys the already available and emerging sensors (factor providers that allow for authenticating a user with the system directly or by involving the cloud. The corresponding challenges from the user as well as the service provider perspective are also reviewed. The MFA system based on reversed Lagrange polynomial within Shamir’s Secret Sharing (SSS scheme is further proposed to enable more flexible authentication. This solution covers the cases of authenticating the user even if some of the factors are mismatched or absent. Our framework allows for qualifying the missing factors by authenticating the user without disclosing sensitive biometric data to the verification entity. Finally, a vision of the future trends in MFA is discussed.

Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance

NARCIS (Netherlands)

M. Asai (Manabu); M.J. McAleer (Michael)

2014-01-01

markdownabstract__Abstract__ Modelling covariance structures is known to suffer from the curse of dimensionality. In order to avoid this problem for forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures that accommodates

Bootstrapping pre-averaged realized volatility under market microstructure noise

DEFF Research Database (Denmark)

Hounyo, Ulrich; Goncalves, Sílvia; Meddahi, Nour

The main contribution of this paper is to propose a bootstrap method for inference on integrated volatility based on the pre-averaging approach of Jacod et al. (2009), where the pre-averaging is done over all possible overlapping blocks of consecutive observations. The overlapping nature of the pre......-averaged returns implies that these are kn-dependent with kn growing slowly with the sample size n. This motivates the application of a blockwise bootstrap method. We show that the "blocks of blocks" bootstrap method suggested by Politis and Romano (1992) (and further studied by Bühlmann and Künsch (1995......)) is valid only when volatility is constant. The failure of the blocks of blocks bootstrap is due to the heterogeneity of the squared pre-averaged returns when volatility is stochastic. To preserve both the dependence and the heterogeneity of squared pre-averaged returns, we propose a novel procedure...

Toward an innovative stochastic modeling of electric charges loss through dielectric

Directory of Open Access Journals (Sweden)

Micolau G.

2016-01-01

Full Text Available This paper deals with new stochastic modeling of very low tunneling currents in Non-Volatile Memories. For this purpose, we first develop current measurement method based on Floating Gate technique. In order to reach the long time behavior of electrical dynamic, we aim at using very basic tools (power supply, multimeter... but still having a very good current resolution. Also, our measurement is led in a very particular low-noise environment (underground laboratory allowing to keep the electrical contacts on the device under test as long as possible. After showing the feasibility of such measurements, we present a modeling approach of the charge loss process inside the Non-volatile Memories by using mathematical tool involving long memory effect. The model is based on stochastic counting process with memory effect yielding to a fractional relaxation equation for the charge loss over time. The main interest of the present model lies in the fact that the corresponding inversion problem involves only two parameters that can be carried out efficiently.

An Hilbert space approach for a class of arbitrage free implied volatilities models

OpenAIRE

Brace, A.; Fabbri, G.; Goldys, B.

2007-01-01

We present an Hilbert space formulation for a set of implied volatility models introduced in \\cite{BraceGoldys01} in which the authors studied conditions for a family of European call options, varying the maturing time and the strike price $T$ an $K$, to be arbitrage free. The arbitrage free conditions give a system of stochastic PDEs for the evolution of the implied volatility surface ${\\hat\\sigma}_t(T,K)$. We will focus on the family obtained fixing a strike $K$ and varying $T$. In order to...

Modeling volatility using state space models.

Science.gov (United States)

Timmer, J; Weigend, A S

1997-08-01

In time series problems, noise can be divided into two categories: dynamic noise which drives the process, and observational noise which is added in the measurement process, but does not influence future values of the system. In this framework, we show that empirical volatilities (the squared relative returns of prices) exhibit a significant amount of observational noise. To model and predict their time evolution adequately, we estimate state space models that explicitly include observational noise. We obtain relaxation times for shocks in the logarithm of volatility ranging from three weeks (for foreign exchange) to three to five months (for stock indices). In most cases, a two-dimensional hidden state is required to yield residuals that are consistent with white noise. We compare these results with ordinary autoregressive models (without a hidden state) and find that autoregressive models underestimate the relaxation times by about two orders of magnitude since they do not distinguish between observational and dynamic noise. This new interpretation of the dynamics of volatility in terms of relaxators in a state space model carries over to stochastic volatility models and to GARCH models, and is useful for several problems in finance, including risk management and the pricing of derivative securities. Data sets used: Olsen & Associates high frequency DEM/USD foreign exchange rates (8 years). Nikkei 225 index (40 years). Dow Jones Industrial Average (25 years).

Hedging electricity price volatility using nuclear power

International Nuclear Information System (INIS)

Mari, Carlo

2014-01-01

Highlights: • Nuclear power is an important asset to reduce the volatility of electricity prices. • Unpredictability of fossil fuels and carbon prices makes power prices very volatile. • The dynamics of fossil fuels and carbon prices is described by Brownian motions. • LCOE values, volatilities and correlations are obtained via Monte Carlo simulations. • Optimal portfolios of generating technologies are get using a mean–variance approach. - Abstract: The analysis presented in this paper aims to put in some evidence the role of nuclear power as hedging asset against the volatility of electricity prices. The unpredictability of natural gas and coal market prices as well as the uncertainty in environmental policies may affect power generating costs, thus enhancing volatility in electricity market prices. The nuclear option, allowing to generate electricity without carbon emissions, offers the possibility to reduce the volatility of electricity prices through optimal diversification of power generating technologies. This paper provides a methodological scheme to plan well diversified “portfolios” of generating capacity that minimize the electricity price risk induced by random movements of fossil fuels market prices and by unpredictable fluctuations of carbon credits prices. The analysis is developed within a stochastic environment in which the dynamics of fuel prices as well as the dynamics of carbon credits prices is assumed to evolve in time according to well defined Brownian processes. Starting from market data and using Monte Carlo techniques to simulate generating cost values, the hedging argument is developed by selecting optimal portfolio of power generating technologies using a mean–variance approach

Potential barriers to the application of multi-factor portfolio analysis in public hospitals: evidence from a pilot study in the Netherlands.

Science.gov (United States)

Pavlova, Milena; Tsiachristas, Apostolos; Vermaeten, Gerhard; Groot, Wim

2009-01-01

Portfolio analysis is a business management tool that can assist health care managers to develop new organizational strategies. The application of portfolio analysis to US hospital settings has been frequently reported. In Europe however, the application of this technique has received little attention, especially concerning public hospitals. Therefore, this paper examines the peculiarities of portfolio analysis and its applicability to the strategic management of European public hospitals. The analysis is based on a pilot application of a multi-factor portfolio analysis in a Dutch university hospital. The nature of portfolio analysis and the steps in a multi-factor portfolio analysis are reviewed along with the characteristics of the research setting. Based on these data, a multi-factor portfolio model is developed and operationalized. The portfolio model is applied in a pilot investigation to analyze the market attractiveness and hospital strengths with regard to the provision of three orthopedic services: knee surgery, hip surgery, and arthroscopy. The pilot portfolio analysis is discussed to draw conclusions about potential barriers to the overall adoption of portfolio analysis in the management of a public hospital. Copyright (c) 2008 John Wiley & Sons, Ltd.

The Research of Regression Method for Forecasting Monthly Electricity Sales Considering Coupled Multi-factor

Science.gov (United States)

Wang, Jiangbo; Liu, Junhui; Li, Tiantian; Yin, Shuo; He, Xinhui

2018-01-01

The monthly electricity sales forecasting is a basic work to ensure the safety of the power system. This paper presented a monthly electricity sales forecasting method which comprehensively considers the coupled multi-factors of temperature, economic growth, electric power replacement and business expansion. The mathematical model is constructed by using regression method. The simulation results show that the proposed method is accurate and effective.

Altruism in a volatile world.

Science.gov (United States)

Kennedy, Patrick; Higginson, Andrew D; Radford, Andrew N; Sumner, Seirian

2018-03-15

The evolution of altruism-costly self-sacrifice in the service of others-has puzzled biologists since The Origin of Species. For half a century, attempts to understand altruism have developed around the concept that altruists may help relatives to have extra offspring in order to spread shared genes. This theory-known as inclusive fitness-is founded on a simple inequality termed Hamilton's rule. However, explanations of altruism have typically not considered the stochasticity of natural environments, which will not necessarily favour genotypes that produce the greatest average reproductive success. Moreover, empirical data across many taxa reveal associations between altruism and environmental stochasticity, a pattern not predicted by standard interpretations of Hamilton's rule. Here we derive Hamilton's rule with explicit stochasticity, leading to new predictions about the evolution of altruism. We show that altruists can increase the long-term success of their genotype by reducing the temporal variability in the number of offspring produced by their relatives. Consequently, costly altruism can evolve even if it has a net negative effect on the average reproductive success of related recipients. The selective pressure on volatility-suppressing altruism is proportional to the coefficient of variation in population fitness, and is therefore diminished by its own success. Our results formalize the hitherto elusive link between bet-hedging and altruism, and reveal missing fitness effects in the evolution of animal societies.

Nonlinear stochastic interacting dynamics and complexity of financial gasket fractal-like lattice percolation

Science.gov (United States)

Zhang, Wei; Wang, Jun

2018-05-01

A novel nonlinear stochastic interacting price dynamics is proposed and investigated by the bond percolation on Sierpinski gasket fractal-like lattice, aim to make a new approach to reproduce and study the complexity dynamics of real security markets. Fractal-like lattices correspond to finite graphs with vertices and edges, which are similar to fractals, and Sierpinski gasket is a well-known example of fractals. Fractional ordinal array entropy and fractional ordinal array complexity are introduced to analyze the complexity behaviors of financial signals. To deeper comprehend the fluctuation characteristics of the stochastic price evolution, the complexity analysis of random logarithmic returns and volatility are preformed, including power-law distribution, fractional sample entropy and fractional ordinal array complexity. For further verifying the rationality and validity of the developed stochastic price evolution, the actual security market dataset are also studied with the same statistical methods for comparison. The empirical results show that this stochastic price dynamics can reconstruct complexity behaviors of the actual security markets to some extent.

MULTI-FACTOR ANALYSIS FOR SELECTING LUNAR EXPLORATION SOFT LANDING AREA AND THE BEST CRUISE ROUTE

Directory of Open Access Journals (Sweden)

N. Mou

2018-04-01

Full Text Available Selecting the right soft landing area and planning a reasonable cruise route are the basic tasks of lunar exploration. In this paper, the Von Karman crater in the Antarctic Aitken basin on the back of the moon is used as the study area, and multi-factor analysis is used to evaluate the landing area and cruise route of lunar exploration. The evaluation system mainly includes the factors such as the density of craters, the impact area of craters, the formation of the whole area and the formation of some areas, such as the vertical structure, rock properties and the content of (FeO + TiO2, which can reflect the significance of scientific exploration factor. And the evaluation of scientific exploration is carried out on the basis of safety and feasibility. On the basis of multi-factor superposition analysis, three landing zones A, B and C are selected, and the appropriate cruising route is analyzed through scientific research factors. This study provides a scientific basis for the lunar probe landing and cruise route planning, and it provides technical support for the subsequent lunar exploration.

Multi-Factor Analysis for Selecting Lunar Exploration Soft Landing Area and the best Cruise Route

Science.gov (United States)

Mou, N.; Li, J.; Meng, Z.; Zhang, L.; Liu, W.

2018-04-01

Selecting the right soft landing area and planning a reasonable cruise route are the basic tasks of lunar exploration. In this paper, the Von Karman crater in the Antarctic Aitken basin on the back of the moon is used as the study area, and multi-factor analysis is used to evaluate the landing area and cruise route of lunar exploration. The evaluation system mainly includes the factors such as the density of craters, the impact area of craters, the formation of the whole area and the formation of some areas, such as the vertical structure, rock properties and the content of (FeO + TiO2), which can reflect the significance of scientific exploration factor. And the evaluation of scientific exploration is carried out on the basis of safety and feasibility. On the basis of multi-factor superposition analysis, three landing zones A, B and C are selected, and the appropriate cruising route is analyzed through scientific research factors. This study provides a scientific basis for the lunar probe landing and cruise route planning, and it provides technical support for the subsequent lunar exploration.

New approach of financial volatility duration dynamics by stochastic finite-range interacting voter system.

Science.gov (United States)

Wang, Guochao; Wang, Jun

2017-01-01

We make an approach on investigating the fluctuation behaviors of financial volatility duration dynamics. A new concept of volatility two-component range intensity (VTRI) is developed, which constitutes the maximal variation range of volatility intensity and shortest passage time of duration, and can quantify the investment risk in financial markets. In an attempt to study and describe the nonlinear complex properties of VTRI, a random agent-based financial price model is developed by the finite-range interacting biased voter system. The autocorrelation behaviors and the power-law scaling behaviors of return time series and VTRI series are investigated. Then, the complexity of VTRI series of the real markets and the proposed model is analyzed by Fuzzy entropy (FuzzyEn) and Lempel-Ziv complexity. In this process, we apply the cross-Fuzzy entropy (C-FuzzyEn) to study the asynchrony of pairs of VTRI series. The empirical results reveal that the proposed model has the similar complex behaviors with the actual markets and indicate that the proposed stock VTRI series analysis and the financial model are meaningful and feasible to some extent.

Multi-factor evaluation indicator method for the risk assessment of atmospheric and oceanic hazard group due to the attack of tropical cyclones

Science.gov (United States)

Qi, Peng; Du, Mei

2018-06-01

China's southeast coastal areas frequently suffer from storm surge due to the attack of tropical cyclones (TCs) every year. Hazards induced by TCs are complex, such as strong wind, huge waves, storm surge, heavy rain, floods, and so on. The atmospheric and oceanic hazards cause serious disasters and substantial economic losses. This paper, from the perspective of hazard group, sets up a multi-factor evaluation method for the risk assessment of TC hazards using historical extreme data of concerned atmospheric and oceanic elements. Based on the natural hazard dynamic process, the multi-factor indicator system is composed of nine natural hazard factors representing intensity and frequency, respectively. Contributing to the indicator system, in order of importance, are maximum wind speed by TCs, attack frequency of TCs, maximum surge height, maximum wave height, frequency of gusts ≥ Scale 8, rainstorm intensity, maximum tidal range, rainstorm frequency, then sea-level rising rate. The first four factors are the most important, whose weights exceed 10% in the indicator system. With normalization processing, all the single-hazard factors are superposed by multiplying their weights to generate a superposed TC hazard. The multi-factor evaluation indicator method was applied to the risk assessment of typhoon-induced atmospheric and oceanic hazard group in typhoon-prone southeast coastal cities of China.

Forecasting volatility for options valuation

International Nuclear Information System (INIS)

Belaifa, M.; Morimune, K.

2006-01-01

The petroleum sector plays a neuralgic role in the basement of world economies, and market actors (producers, intermediates, as well as consumers) are continuously subjected to the dynamics of unstable oil market. Huge amounts are being invested along the production chain to make one barrel of crude oil available to the end user. Adding to that are the effect of geopolitical dynamics as well as geological risks as expressed in terms of low chances of successful discoveries. In addition, fiscal regimes and regulations, technology and environmental concerns are also among some of the major factors that contribute to the substantial risk in the oil industry and render the market structure vulnerable to crises. The management of these vulnerabilities require modern tools to reduce risk to a certain level, which unfortunately is a non-zero value. The aim of this paper is, therefore, to provide a modern technique to capture the oil price stochastic volatility that can be implemented to value the exposure of an investor, a company, a corporate or a Government. The paper first analyses the regional dependence on oil prices, through a historical perspective and then looks at the evolution of pricing environment since the large price jumps of the 1970s. The main causes of oil prices volatility are treated in the third part of the paper. The rest of the article deals with volatility models and forecasts used in risk management, with an implication for pricing derivatives. (author)

Dutch Multifactor Fatigue Scale : A New Scale to Measure the Different Aspects of Fatigue After Acquired Brain Injury

NARCIS (Netherlands)

Visser-Keizer, Annemarie C.; Hogenkamp, Antoinette; Westerhof-Evers, Herma J.; Egberink, Iris J. L.; Spikman, Jacoba M.

Objectives: To develop the Dutch Multifactor Fatigue Scale (DMFS), a new scale to assess the nature and impact of fatigue and coping with fatigue in the chronic phase after acquired brain injury (ABI) and to analyze the psychometric properties of this scale in a mixed group of patients with ABI.

Stochastic Averaging and Stochastic Extremum Seeking

CERN Document Server

Liu, Shu-Jun

2012-01-01

Stochastic Averaging and Stochastic Extremum Seeking develops methods of mathematical analysis inspired by the interest in reverse engineering  and analysis of bacterial  convergence by chemotaxis and to apply similar stochastic optimization techniques in other environments. The first half of the text presents significant advances in stochastic averaging theory, necessitated by the fact that existing theorems are restricted to systems with linear growth, globally exponentially stable average models, vanishing stochastic perturbations, and prevent analysis over infinite time horizon. The second half of the text introduces stochastic extremum seeking algorithms for model-free optimization of systems in real time using stochastic perturbations for estimation of their gradients. Both gradient- and Newton-based algorithms are presented, offering the user the choice between the simplicity of implementation (gradient) and the ability to achieve a known, arbitrary convergence rate (Newton). The design of algorithms...

Measurement Invariance of Second-Order Factor Model of the Multifactor Leadership Questionnaire (MLQ) across K-12 Principal Gender

Science.gov (United States)

Xu, Lihua; Wubbena, Zane; Stewart, Trae

2016-01-01

Purpose: The purpose of this paper is to investigate the factor structure and the measurement invariance of the Multifactor Leadership Questionnaire (MLQ) across gender of K-12 school principals (n=6,317) in the USA. Design/methodology/approach: Nine first-order factor models and four second-order factor models were tested using confirmatory…

The Impact of Tax Shocks and Oil Price Volatility on Risk - A Study of North Sea Oilfield Projects

OpenAIRE

Kretzschmar, Gavin Lee; Moles, Peter

2006-01-01

We examine the impact of market volatility and increased fiscal take on risk in strategic natural resource projects. An increase in 2006 UK oilfield taxation is used as a natural experiment for assessing the impact of a fiscal increase on oilfield projects comprising 73% of UK reserves. Stochastic cash flow at risk models combine market volatility and tax-take at the oilfield level to extend earlier North Sea studies. We demonstrate that a 10% Secondary tax increase in a composite UKCS fiscal...

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment.

Science.gov (United States)

De Kauwe, Martin G; Medlyn, Belinda E; Walker, Anthony P; Zaehle, Sönke; Asao, Shinichi; Guenet, Bertrand; Harper, Anna B; Hickler, Thomas; Jain, Atul K; Luo, Yiqi; Lu, Xingjie; Luus, Kristina; Parton, William J; Shu, Shijie; Wang, Ying-Ping; Werner, Christian; Xia, Jianyang; Pendall, Elise; Morgan, Jack A; Ryan, Edmund M; Carrillo, Yolima; Dijkstra, Feike A; Zelikova, Tamara J; Norby, Richard J

2017-09-01

Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such models have only been tested against single-factor experiments. We applied 10 TBMs to the multifactor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2  yr -1 ). Comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single-factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the N cycle models, N availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO 2 -induced water savings to extend the growing season length. Observed interactive (CO 2  × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change. © 2017 John Wiley & Sons Ltd.

Analysis of model implied volatility for jump diffusion models: Empirical evidence from the Nordpool market

International Nuclear Information System (INIS)

Nomikos, Nikos K.; Soldatos, Orestes A.

2010-01-01

In this paper we examine the importance of mean reversion and spikes in the stochastic behaviour of the underlying asset when pricing options on power. We propose a model that is flexible in its formulation and captures the stylized features of power prices in a parsimonious way. The main feature of the model is that it incorporates two different speeds of mean reversion to capture the differences in price behaviour between normal and spiky periods. We derive semi-closed form solutions for European option prices using transform analysis and then examine the properties of the implied volatilities that the model generates. We find that the presence of jumps generates prominent volatility skews which depend on the sign of the mean jump size. We also show that mean reversion reduces the volatility smile as time to maturity increases. In addition, mean reversion induces volatility skews particularly for ITM options, even in the absence of jumps. Finally, jump size volatility and jump intensity mainly affect the kurtosis and thus the curvature of the smile with the former having a more important role in making the volatility smile more pronounced and thus increasing the kurtosis of the underlying price distribution.

Risk score modeling of multiple gene to gene interactions using aggregated-multifactor dimensionality reduction

Directory of Open Access Journals (Sweden)

Dai Hongying

2013-01-01

Full Text Available Abstract Background Multifactor Dimensionality Reduction (MDR has been widely applied to detect gene-gene (GxG interactions associated with complex diseases. Existing MDR methods summarize disease risk by a dichotomous predisposing model (high-risk/low-risk from one optimal GxG interaction, which does not take the accumulated effects from multiple GxG interactions into account. Results We propose an Aggregated-Multifactor Dimensionality Reduction (A-MDR method that exhaustively searches for and detects significant GxG interactions to generate an epistasis enriched gene network. An aggregated epistasis enriched risk score, which takes into account multiple GxG interactions simultaneously, replaces the dichotomous predisposing risk variable and provides higher resolution in the quantification of disease susceptibility. We evaluate this new A-MDR approach in a broad range of simulations. Also, we present the results of an application of the A-MDR method to a data set derived from Juvenile Idiopathic Arthritis patients treated with methotrexate (MTX that revealed several GxG interactions in the folate pathway that were associated with treatment response. The epistasis enriched risk score that pooled information from 82 significant GxG interactions distinguished MTX responders from non-responders with 82% accuracy. Conclusions The proposed A-MDR is innovative in the MDR framework to investigate aggregated effects among GxG interactions. New measures (pOR, pRR and pChi are proposed to detect multiple GxG interactions.

ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models

DEFF Research Database (Denmark)

Creel, Michael; Kristensen, Dennis

and latent variables. We show how the methods can incorporate intra-daily information to improve on the estimation and filtering. In particular, the availability of realized volatility measures help us in learning about parameters and latent states. The method is employed in the estimation of a flexible...

An adaptive stochastic model for financial markets

International Nuclear Information System (INIS)

Hernández, Juan Antonio; Benito, Rosa Marı´a; Losada, Juan Carlos

2012-01-01

An adaptive stochastic model is introduced to simulate the behavior of real asset markets. The model adapts itself by changing its parameters automatically on the basis of the recent historical data. The basic idea underlying the model is that a random variable uniformly distributed within an interval with variable extremes can replicate the histograms of asset returns. These extremes are calculated according to the arrival of new market information. This adaptive model is applied to the daily returns of three well-known indices: Ibex35, Dow Jones and Nikkei, for three complete years. The model reproduces the histograms of the studied indices as well as their autocorrelation structures. It produces the same fat tails and the same power laws, with exactly the same exponents, as in the real indices. In addition, the model shows a great adaptation capability, anticipating the volatility evolution and showing the same volatility clusters observed in the assets. This approach provides a novel way to model asset markets with internal dynamics which changes quickly with time, making it impossible to define a fixed model to fit the empirical observations.

Spectroscopically Enhanced Method and System for Multi-Factor Biometric Authentication

Science.gov (United States)

Pishva, Davar

This paper proposes a spectroscopic method and system for preventing spoofing of biometric authentication. One of its focus is to enhance biometrics authentication with a spectroscopic method in a multifactor manner such that a person's unique ‘spectral signatures’ or ‘spectral factors’ are recorded and compared in addition to a non-spectroscopic biometric signature to reduce the likelihood of imposter getting authenticated. By using the ‘spectral factors’ extracted from reflectance spectra of real fingers and employing cluster analysis, it shows how the authentic fingerprint image presented by a real finger can be distinguished from an authentic fingerprint image embossed on an artificial finger, or molded on a fingertip cover worn by an imposter. This paper also shows how to augment two widely used biometrics systems (fingerprint and iris recognition devices) with spectral biometrics capabilities in a practical manner and without creating much overhead or inconveniencing their users.

Neglected chaos in international stock markets: Bayesian analysis of the joint return-volatility dynamical system

Science.gov (United States)

Tsionas, Mike G.; Michaelides, Panayotis G.

2017-09-01

We use a novel Bayesian inference procedure for the Lyapunov exponent in the dynamical system of returns and their unobserved volatility. In the dynamical system, computation of largest Lyapunov exponent by traditional methods is impossible as the stochastic nature has to be taken explicitly into account due to unobserved volatility. We apply the new techniques to daily stock return data for a group of six countries, namely USA, UK, Switzerland, Netherlands, Germany and France, from 2003 to 2014, by means of Sequential Monte Carlo for Bayesian inference. The evidence points to the direction that there is indeed noisy chaos both before and after the recent financial crisis. However, when a much simpler model is examined where the interaction between returns and volatility is not taken into consideration jointly, the hypothesis of chaotic dynamics does not receive much support by the data ("neglected chaos").

Changes of platelet GMP-140 in diabetic nephropathy and its multi-factor regression analysis

International Nuclear Information System (INIS)

Wang Zizheng; Du Tongxin; Wang Shukui

2001-01-01

The relation of platelet GMP-140 and its related factors with diabetic nephropathy was studied. 144 patients of diabetic mellitus without nephropathy (group without DN, mean suffering duration of 25.5 +- 18.6 months); 80 with diabetic nephropathy (group DN, mean suffering duration of 58.7 +- 31.6 months) and 50 normal controls were chosen in the research. Platelet GMP-140, plasma α 1 -MG, β 2 -MG, and 24 hour urine albumin (ALB), IgG, α 1 -MG, β 2 -MG were detected by RIA, while HBA 1 C via chromatographic separation and FBG, PBG, Ch, TG, HDL, FG via biochemical methods. All the data had been processed with software on computer with t-test and linear regression, and multi-factor analysis were done also. The levels of platelet GMP-140, FG, DBP, TG, HBA 1 C and PBG in group DN were significantly higher than those of group without DN and normal control (P 0.05), while they were higher than those of normal controls. Multi-factor analysis of platelet GMP-140 with TG, DBP and HBA 1 C were performed in 80 patients with DN (P 1 C are the independent factors enhancing the activation of platelets. The disturbance of lipid metabolism in type II diabetic mellitus may also enhance the activation of platelets. Elevation of blood pressure may accelerate the initiation and deterioration of DN in which change of platelet GMP-140 is an independent factor. Elevation of HBA 1 C and blood glucose are related closely to the diabetic nephropathy

Dynamics Model Applied to Pricing Options with Uncertain Volatility

Directory of Open Access Journals (Sweden)

Lorella Fatone

2012-01-01

model is proposed. The data used to test the calibration problem included observations of asset prices over a finite set of (known equispaced discrete time values. Statistical tests were used to estimate the statistical significance of the two parameters of the Black-Scholes model: the volatility and the drift. The effects of these estimates on the option pricing problem were investigated. In particular, the pricing of an option with uncertain volatility in the Black-Scholes framework was revisited, and a statistical significance was associated with the price intervals determined using the Black-Scholes-Barenblatt equations. Numerical experiments involving synthetic and real data were presented. The real data considered were the daily closing values of the S&P500 index and the associated European call and put option prices in the year 2005. The method proposed here for calibrating the Black-Scholes dynamics model could be extended to other science and engineering models that may be expressed in terms of stochastic dynamical systems.

On stochastic integration for volatility modulated Brownian-driven Volterra processes via white noise analysis

DEFF Research Database (Denmark)

E. Barndorff-Nielsen, Ole; Benth, Fred Espen; Szozda, Benedykt

This paper generalizes the integration theory for volatility modulated Brownian-driven Volterra processes onto the space G* of Potthoff-Timpel distributions. Sufficient conditions for integrability of generalized processes are given, regularity results and properties of the integral are discussed...

On stochastic integration for volatility modulated Brownian-driven Volterra processes via white noise analysis

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole E.; Benth, Fred Espen; Szozda, Benedykt

This paper generalizes the integration theory for volatility modulated Brownian-driven Volterra processes onto the space G∗ of Potthoff--Timpel distributions. Sufficient conditions for integrability of generalized processes are given, regularity results and properties of the integral are discusse...

Probabilistic numerical methods for high-dimensional stochastic control and valuation problems on electricity markets

International Nuclear Information System (INIS)

Langrene, Nicolas

2014-01-01

This thesis deals with the numerical solution of general stochastic control problems, with notable applications for electricity markets. We first propose a structural model for the price of electricity, allowing for price spikes well above the marginal fuel price under strained market conditions. This model allows to price and partially hedge electricity derivatives, using fuel forwards as hedging instruments. Then, we propose an algorithm, which combines Monte-Carlo simulations with local basis regressions, to solve general optimal switching problems. A comprehensive rate of convergence of the method is provided. Moreover, we manage to make the algorithm parsimonious in memory (and hence suitable for high dimensional problems) by generalizing to this framework a memory reduction method that avoids the storage of the sample paths. We illustrate this on the problem of investments in new power plants (our structural power price model allowing the new plants to impact the price of electricity). Finally, we study more general stochastic control problems (the control can be continuous and impact the drift and volatility of the state process), the solutions of which belong to the class of fully nonlinear Hamilton-Jacobi-Bellman equations, and can be handled via constrained Backward Stochastic Differential Equations, for which we develop a backward algorithm based on control randomization and parametric optimizations. A rate of convergence between the constraPned BSDE and its discrete version is provided, as well as an estimate of the optimal control. This algorithm is then applied to the problem of super replication of options under uncertain volatilities (and correlations). (author)

Volatility forecasting for interbank offered rate using grey extreme learning machine: The case of China

International Nuclear Information System (INIS)

Liu, Xiaoyong; Fu, Hui

2016-01-01

Interbank Offered rate is the only direct market rate in China’s currency market. Volatility forecasting of China Interbank Offered Rate (IBOR) has a very important theoretical and practical significance for financial asset pricing and financial risk measure or management. However, IBOR is a dynamics and non-steady time series whose developmental changes have stronger random fluctuation, so it is difficult to forecast the volatility of IBOR. This paper offers a hybrid algorithm using grey model and extreme learning machine (ELM) to forecast volatility of IBOR. The proposed algorithm is composed of three phases. In the first, grey model is used to deal with the original IBOR time series by accumulated generating operation (AGO) and weaken the stochastic volatility in original series. And then, a forecasting model is founded by using ELM to analyze the new IBOR series. Lastly, the predictive value of the original IBOR series can be obtained by inverse accumulated generating operation (IAGO). The new model is applied to forecasting Interbank Offered Rate of China. Compared with the forecasting results of BP and classical ELM, the new model is more efficient to forecasting short- and middle-term volatility of IBOR.

Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility

NARCIS (Netherlands)

Bos, Charles S.

2008-01-01

When analysing the volatility related to high frequency financial data, mostly non-parametric approaches based on realised or bipower variation are applied. This article instead starts from a continuous time diffusion model and derives a parametric analog at high frequency for it, allowing

Leverage effect in financial markets: the retarded volatility model.

Science.gov (United States)

Bouchaud, J P; Matacz, A; Potters, M

2001-11-26

We investigate quantitatively the so-called "leverage effect," which corresponds to a negative correlation between past returns and future volatility. For individual stocks this correlation is moderate and decays over 50 days, while for stock indices it is much stronger but decays faster. For individual stocks the magnitude of this correlation has a universal value that can be rationalized in terms of a new "retarded" model which interpolates between a purely additive and a purely multiplicative stochastic process. For stock indices a specific amplification phenomenon seems to be necessary to account for the observed amplitude of the effect.

Stochastic Analysis 2010

CERN Document Server

Crisan, Dan

2011-01-01

"Stochastic Analysis" aims to provide mathematical tools to describe and model high dimensional random systems. Such tools arise in the study of Stochastic Differential Equations and Stochastic Partial Differential Equations, Infinite Dimensional Stochastic Geometry, Random Media and Interacting Particle Systems, Super-processes, Stochastic Filtering, Mathematical Finance, etc. Stochastic Analysis has emerged as a core area of late 20th century Mathematics and is currently undergoing a rapid scientific development. The special volume "Stochastic Analysis 2010" provides a sa

Quality management of airport services – An analysis of the multifactor structure of customer satisfaction

Directory of Open Access Journals (Sweden)

Josip Mikulić

2007-07-01

Full Text Available The purpose of this paper is to get an insight into the multifactor structure of satisfaction of the customers of a Croatian airport. Based on data from the primary research (n=1053, an importance-performance analysis was conducted that resulted in the categorization of airport services into the satisfaction factors according to Kano’s model of quality. Basic factors, performance factors and excitement factors were identified. The results of this analysis enrich the standard information basis which is obtained through customer satisfaction surveys. Furthermore, they represent a valuable resource for decision-making within the domain of service quality management.

Market structure and the stability and volatility of electricity prices

International Nuclear Information System (INIS)

Bask, Mikael; Widerberg, Anna

2009-01-01

By using a novel approach in this paper, (λ,σ 2 )-analysis, we have found that electricity prices most of the time have increased in stability and decreased in volatility when the Nordic power market has expanded and the degree of competition has increased. That electricity prices at Nord Pool have been generated by a stochastic dynamic system that most often has become more stable during the step-wise integration of the Nordic power market means that this market is less sensitive to shocks after the integration process than it was before this process. This is good news

Stochastic and non-stochastic effects - a conceptual analysis

International Nuclear Information System (INIS)

Karhausen, L.R.

1980-01-01

The attempt to divide radiation effects into stochastic and non-stochastic effects is discussed. It is argued that radiation or toxicological effects are contingently related to radiation or chemical exposure. Biological effects in general can be described by general laws but these laws never represent a necessary connection. Actually stochastic effects express contingent, or empirical, connections while non-stochastic effects represent semantic and non-factual connections. These two expressions stem from two different levels of discourse. The consequence of this analysis for radiation biology and radiation protection is discussed. (author)

Volatility smile as relativistic effect

Science.gov (United States)

Kakushadze, Zura

2017-06-01

We give an explicit formula for the probability distribution based on a relativistic extension of Brownian motion. The distribution (1) is properly normalized and (2) obeys the tower law (semigroup property), so we can construct martingales and self-financing hedging strategies and price claims (options). This model is a 1-constant-parameter extension of the Black-Scholes-Merton model. The new parameter is the analog of the speed of light in Special Relativity. However, in the financial context there is no ;speed limit; and the new parameter has the meaning of a characteristic diffusion speed at which relativistic effects become important and lead to a much softer asymptotic behavior, i.e., fat tails, giving rise to volatility smiles. We argue that a nonlocal stochastic description of such (Lévy) processes is inadequate and discuss a local description from physics. The presentation is intended to be pedagogical.

A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits

OpenAIRE

Gui, Jiang; Moore, Jason H.; Williams, Scott M.; Andrews, Peter; Hillege, Hans L.; van der Harst, Pim; Navis, Gerjan; Van Gilst, Wiek H.; Asselbergs, Folkert W.; Gilbert-Diamond, Diane

2013-01-01

We present an extension of the two-class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR) method handles continuous data by modifying MDR's constructive induction algorithm to use a T-test. QMDR replaces the balanced accuracy metric with a T-test statistic as the score to determine the best interaction model. We used a simulation to ide...

Stochastic control with rough paths

International Nuclear Information System (INIS)

Diehl, Joscha; Friz, Peter K.; Gassiat, Paul

2017-01-01

We study a class of controlled differential equations driven by rough paths (or rough path realizations of Brownian motion) in the sense of Lyons. It is shown that the value function satisfies a HJB type equation; we also establish a form of the Pontryagin maximum principle. Deterministic problems of this type arise in the duality theory for controlled diffusion processes and typically involve anticipating stochastic analysis. We make the link to old work of Davis and Burstein (Stoch Stoch Rep 40:203–256, 1992) and then prove a continuous-time generalization of Roger’s duality formula [SIAM J Control Optim 46:1116–1132, 2007]. The generic case of controlled volatility is seen to give trivial duality bounds, and explains the focus in Burstein–Davis’ (and this) work on controlled drift. Our study of controlled rough differential equations also relates to work of Mazliak and Nourdin (Stoch Dyn 08:23, 2008).

Stochastic control with rough paths

Energy Technology Data Exchange (ETDEWEB)

Diehl, Joscha [University of California San Diego (United States); Friz, Peter K., E-mail: friz@math.tu-berlin.de [TU & WIAS Berlin (Germany); Gassiat, Paul [CEREMADE, Université Paris-Dauphine, PSL Research University (France)

2017-04-15

We study a class of controlled differential equations driven by rough paths (or rough path realizations of Brownian motion) in the sense of Lyons. It is shown that the value function satisfies a HJB type equation; we also establish a form of the Pontryagin maximum principle. Deterministic problems of this type arise in the duality theory for controlled diffusion processes and typically involve anticipating stochastic analysis. We make the link to old work of Davis and Burstein (Stoch Stoch Rep 40:203–256, 1992) and then prove a continuous-time generalization of Roger’s duality formula [SIAM J Control Optim 46:1116–1132, 2007]. The generic case of controlled volatility is seen to give trivial duality bounds, and explains the focus in Burstein–Davis’ (and this) work on controlled drift. Our study of controlled rough differential equations also relates to work of Mazliak and Nourdin (Stoch Dyn 08:23, 2008).

Nonvolatile, semivolatile, or volatile: redefining volatile for volatile organic compounds.

Science.gov (United States)

Võ, Uyên-Uyén T; Morris, Michael P

2014-06-01

Although widely used in air quality regulatory frameworks, the term "volatile organic compound" (VOC) is poorly defined. Numerous standardized tests are currently used in regulations to determine VOC content (and thus volatility), but in many cases the tests do not agree with each other, nor do they always accurately represent actual evaporation rates under ambient conditions. The parameters (time, temperature, reference material, column polarity, etc.) used in the definitions and the associated test methods were created without a significant evaluation of volatilization characteristics in real world settings. Not only do these differences lead to varying VOC content results, but occasionally they conflict with one another. An ambient evaporation study of selected compounds and a few formulated products was conducted and the results were compared to several current VOC test methodologies: SCAQMD Method 313 (M313), ASTM Standard Test Method E 1868-10 (E1868), and US. EPA Reference Method 24 (M24). The ambient evaporation study showed a definite distinction between nonvolatile, semivolatile, and volatile compounds. Some low vapor pressure (LVP) solvents, currently considered exempt as VOCs by some methods, volatilize at ambient conditions nearly as rapidly as the traditional high-volatility solvents they are meant to replace. Conversely, bio-based and heavy hydrocarbons did not readily volatilize, though they often are calculated as VOCs in some traditional test methods. The study suggests that regulatory standards should be reevaluated to more accurately reflect real-world emission from the use of VOC containing products. The definition of VOC in current test methods may lead to regulations that exclude otherwise viable alternatives or allow substitutions of chemicals that may limit the environmental benefits sought in the regulation. A study was conducted to examine volatility of several compounds and a few formulated products under several current VOC test

Generation risk assessment in volatile conditions with wind, hydro, and natural gas units

International Nuclear Information System (INIS)

Sahin, Cem; Shahidehpour, Mohammad; Erkmen, Ismet

2012-01-01

Highlights: ► Stochastic price-based unit commitment (PBUC) for a generation company (GENCO). ► Water inflow, wind, and NG interruption uncertainties are considered. ► Diversification of assets and bilateral contracts enhance payoff and decrease financial risk. ► The utilization of NG in the risk-neutral GENCO case increases as the wind uncertainty increases. ► NG utilization is lowered by the algorithm to decrease in risk-considered case. -- Abstract: This paper studies a generating company (GENCO)’s midterm (a few months to a year) scheduling payoffs and risks in volatile operating conditions. The proposed algorithm considers the integration of intermittent wind units into a GENCO’s generation assets and coordinates the GENCO’s hourly wind generation schedule with that of natural gas (NG) units (with volatile gas prices) and hydro units (with water inflow forecast) for maximizing the GENCO’s payoff. The proposed midterm GENCO model applies market price forecasts to the risk-constrained stochastic price-based unit commitment (PBUC) for calculating the GENCO’s risk in energy and ancillary services markets. The proposed PBUC minimizes the cost of (a) NG contracts, storage, startup and shutdown, (b) startup and shutdown of cascaded hydro units, and (c) penalty for defaulting on the scheduled power delivery. Simulation results show that the diversification of generating assets including bilateral contracts (BCs) could enhance the GENCO’s midterm planning by increasing the expected payoff and decreasing the financial risk.

'Marginal Employment' and the Demand for Heterogenous Labour: Empirical Evidence from a Multi-factor Labour Demand Model for Germany

OpenAIRE

Ronny Freier; Viktor Steiner

2007-01-01

We develop a structural multi-factor labour demand model which distinguishes between eight labour categories including non-standard types of employment such as marginal employment. The model is estimated for both the number of workers and total working hours using a new panel data set. For unskilled and skilled workers in full-time employment, we find labour demand elasticities similar to previous estimates for the west German economy. Our new estimates of own-wage elasticities for marginal e...

Modeling the return and volatility of the Greek electricity marginal system price

International Nuclear Information System (INIS)

Theodorou, Petros; Karyampas, Dimitrios

2008-01-01

Traditional cost based optimization models (WASP) for expansion planning do not allow for mark-to-market valuation and cannot satisfy arbitrage free requirements. This work will fill this gap by developing and estimating models for mark-to-market valuation. Furthermore the present paper examines the return and volatility of the newly born Greek's electricity market's marginal system price. A detailed description of the market mechanism and regulation is used to describe how prices are determined in order to proceed with return and volatility modeling. Continuous time mean reverting and time varying mean reverting stochastic processes have been solved in discrete time processes and estimated econometrically along with ARMAX and GARCH models. It was found that GARCH model gave much better estimation and forecasting ability. Strong persistence in mean has been found giving suspicions of market inefficiency and strong incentives for arbitrage opportunities. Finally, the change in the regulatory framework has been controlled and found to have significant impact. (author)

Noncausal stochastic calculus

CERN Document Server

Ogawa, Shigeyoshi

2017-01-01

This book presents an elementary introduction to the theory of noncausal stochastic calculus that arises as a natural alternative to the standard theory of stochastic calculus founded in 1944 by Professor Kiyoshi Itô. As is generally known, Itô Calculus is essentially based on the "hypothesis of causality", asking random functions to be adapted to a natural filtration generated by Brownian motion or more generally by square integrable martingale. The intention in this book is to establish a stochastic calculus that is free from this "hypothesis of causality". To be more precise, a noncausal theory of stochastic calculus is developed in this book, based on the noncausal integral introduced by the author in 1979. After studying basic properties of the noncausal stochastic integral, various concrete problems of noncausal nature are considered, mostly concerning stochastic functional equations such as SDE, SIE, SPDE, and others, to show not only the necessity of such theory of noncausal stochastic calculus but ...

Pricing Volatility of Stock Returns with Volatile and Persistent Components

DEFF Research Database (Denmark)

Zhu, Jie

In this paper a two-component volatility model based on the component's first moment is introduced to describe the dynamic of speculative return volatility. The two components capture the volatile and persistent part of volatility respectively. Then the model is applied to 10 Asia-Pacific stock m......, a positive or risk-premium effect exists between return and the volatile component, yet the persistent component is not significantly priced for return dynamic process....... markets. Their in-mean effects on return are also tested. The empirical results show that the persistent component accounts much more for volatility dynamic process than the volatile component. However the volatile component is found to be a significant pricing factor of asset returns for most markets...

Endogenous Lunar Volatiles

Science.gov (United States)

McCubbin, F. M.; Liu, Y.; Barnes, J. J.; Boyce, J. W.; Day, J. M. D.; Elardo, S. M.; Hui, H.; Magna, T.; Ni, P.; Tartese, R.;

The influence of surface roughness on volatile transport on the Moon

Science.gov (United States)

Prem, P.; Goldstein, D. B.; Varghese, P. L.; Trafton, L. M.

2018-01-01

The Moon and other virtually airless bodies provide distinctive environments for the transport and sequestration of water and other volatiles delivered to their surfaces by various sources. In this work, we conduct Monte Carlo simulations of water vapor transport on the Moon to investigate the role of small-scale roughness (unresolved by orbital measurements) in the migration and cold-trapping of volatiles. Observations indicate that surface roughness, combined with the insulating nature of lunar regolith and the absence of significant exospheric heat flow, can cause large variations in temperature over very small scales. Surface temperature has a strong influence on the residence time of migrating water molecules on the lunar surface, which in turn affects the rate and magnitude of volatile transport to permanently shadowed craters (cold traps) near the lunar poles, as well as exospheric structure and the susceptibility of migrating molecules to photodestruction. Here, we develop a stochastic rough surface temperature model suitable for simulations of volatile transport on a global scale, and compare the results of Monte Carlo simulations of volatile transport with and without the surface roughness model. We find that including small-scale temperature variations and shadowing leads to a slight increase in cold-trapping at the lunar poles, accompanied by a slight decrease in photodestruction. Exospheric structure is altered only slightly, primarily at the dawn terminator. We also examine the sensitivity of our results to the temperature of small-scale shadows, and the energetics of water molecule desorption from the lunar regolith - two factors that remain to be definitively constrained by other methods - and find that both these factors affect the rate at which cold trap capture and photodissociation occur, as well as exospheric density and longevity.

Pricing Volatility of Stock Returns with Volatile and Persistent Components

DEFF Research Database (Denmark)

Zhu, Jie

2009-01-01

This paper introduces a two-component volatility model based on first moments of both components to describe the dynamics of speculative return volatility. The two components capture the volatile and the persistent part of volatility, respectively. The model is applied to 10 Asia-Pacific stock ma...... markets. A positive or risk-premium effect exists between the return and the volatile component, yet the persistent component is not significantly priced for the return dynamic process....... markets. Their in-mean effects on returns are tested. The empirical results show that the persistent component is much more important for the volatility dynamic process than is the volatile component. However, the volatile component is found to be a significant pricing factor of asset returns for most...

Mining nutrigenetics patterns related to obesity: use of parallel multifactor dimensionality reduction.

Science.gov (United States)

Karayianni, Katerina N; Grimaldi, Keith A; Nikita, Konstantina S; Valavanis, Ioannis K

2015-01-01

This paper aims to enlighten the complex etiology beneath obesity by analysing data from a large nutrigenetics study, in which nutritional and genetic factors associated with obesity were recorded for around two thousand individuals. In our previous work, these data have been analysed using artificial neural network methods, which identified optimised subsets of factors to predict one's obesity status. These methods did not reveal though how the selected factors interact with each other in the obtained predictive models. For that reason, parallel Multifactor Dimensionality Reduction (pMDR) was used here to further analyse the pre-selected subsets of nutrigenetic factors. Within pMDR, predictive models using up to eight factors were constructed, further reducing the input dimensionality, while rules describing the interactive effects of the selected factors were derived. In this way, it was possible to identify specific genetic variations and their interactive effects with particular nutritional factors, which are now under further study.

ALGORITHM FOR GENERALIZED GARMAN EQUATION IN OPTION PRICING OF A FINANCIAL DERIVATIVES WITH STOCHASTIC VOLATILITY MODELS

Directory of Open Access Journals (Sweden)

Maxim Ioan

2009-05-01

Full Text Available In our paper we build a reccurence from generalized Garman equation and discretization of 3-dimensional domain. From reccurence we build an algorithm for computing values of an option based on time, momentan volatility of support and value of support on a

Equilibrium Investment Strategy for DC Pension Plan with Inflation and Stochastic Income under Heston’s SV Model

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Jingyun Sun

2016-01-01

Full Text Available We consider a portfolio selection problem for a defined contribution (DC pension plan under the mean-variance criteria. We take into account the inflation risk and assume that the salary income process of the pension plan member is stochastic. Furthermore, the financial market consists of a risk-free asset, an inflation-linked bond, and a risky asset with Heston’s stochastic volatility (SV. Under the framework of game theory, we derive two extended Hamilton-Jacobi-Bellman (HJB equations systems and give the corresponding verification theorems in both the periods of accumulation and distribution of the DC pension plan. The explicit expressions of the equilibrium investment strategies, corresponding equilibrium value functions, and the efficient frontiers are also obtained. Finally, some numerical simulations and sensitivity analysis are presented to verify our theoretical results.

Brownian motion model with stochastic parameters for asset prices

Science.gov (United States)

Ching, Soo Huei; Hin, Pooi Ah

2013-09-01

The Brownian motion model may not be a completely realistic model for asset prices because in real asset prices the drift μ and volatility σ may change over time. Presently we consider a model in which the parameter x = (μ,σ) is such that its value x (t + Δt) at a short time Δt ahead of the present time t depends on the value of the asset price at time t + Δt as well as the present parameter value x(t) and m-1 other parameter values before time t via a conditional distribution. The Malaysian stock prices are used to compare the performance of the Brownian motion model with fixed parameter with that of the model with stochastic parameter.

On a Corporate Bond Pricing Model with Credit Rating Migration Risksand Stochastic Interest Rate

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Jin Liang

2017-10-01

Full Text Available In this paper we study a corporate bond-pricing model with credit rating migration and astochastic interest rate. The volatility of bond price in the model strongly depends on potential creditrating migration and stochastic change of the interest rate. This new model improves the previousexisting models in which the interest rate is considered to be a constant. The existence, uniquenessand regularity of the solution for the model are established. Moreover, some properties includingthe smoothness of the free boundary are obtained. Furthermore, some numerical computations arepresented to illustrate the theoretical results.

STOCHASTIC FLOWS OF MAPPINGS

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

In this paper, the stochastic flow of mappings generated by a Feller convolution semigroup on a compact metric space is studied. This kind of flow is the generalization of superprocesses of stochastic flows and stochastic diffeomorphism induced by the strong solutions of stochastic differential equations.

Level Shifts in Volatility and the Implied-Realized Volatility Relation

DEFF Research Database (Denmark)

Christensen, Bent Jesper; de Magistris, Paolo Santucci

We propose a simple model in which realized stock market return volatility and implied volatility backed out of option prices are subject to common level shifts corresponding to movements between bull and bear markets. The model is estimated using the Kalman filter in a generalization to the mult......We propose a simple model in which realized stock market return volatility and implied volatility backed out of option prices are subject to common level shifts corresponding to movements between bull and bear markets. The model is estimated using the Kalman filter in a generalization...... to the multivariate case of the univariate level shift technique by Lu and Perron (2008). An application to the S&P500 index and a simulation experiment show that the recently documented empirical properties of strong persistence in volatility and forecastability of future realized volatility from current implied...... volatility, which have been interpreted as long memory (or fractional integration) in volatility and fractional cointegration between implied and realized volatility, are accounted for by occasional common level shifts....

Nonzero-Sum Stochastic Differential Portfolio Games under a Markovian Regime Switching Model

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Chaoqun Ma

2015-01-01

Full Text Available We consider a nonzero-sum stochastic differential portfolio game problem in a continuous-time Markov regime switching environment when the price dynamics of the risky assets are governed by a Markov-modulated geometric Brownian motion (GBM. The market parameters, including the bank interest rate and the appreciation and volatility rates of the risky assets, switch over time according to a continuous-time Markov chain. We formulate the nonzero-sum stochastic differential portfolio game problem as two utility maximization problems of the sum process between two investors’ terminal wealth. We derive a pair of regime switching Hamilton-Jacobi-Bellman (HJB equations and two systems of coupled HJB equations at different regimes. We obtain explicit optimal portfolio strategies and Feynman-Kac representations of the two value functions. Furthermore, we solve the system of coupled HJB equations explicitly in a special case where there are only two states in the Markov chain. Finally we provide comparative statics and numerical simulation analysis of optimal portfolio strategies and investigate the impact of regime switching on optimal portfolio strategies.

Stochastic processes

CERN Document Server

Parzen, Emanuel

1962-01-01

Well-written and accessible, this classic introduction to stochastic processes and related mathematics is appropriate for advanced undergraduate students of mathematics with a knowledge of calculus and continuous probability theory. The treatment offers examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models, and it develops the methods of probability model-building.Chapter 1 presents precise definitions of the notions of a random variable and a stochastic process and introduces the Wiener and Poisson processes. Subsequent chapters examine

FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.

Directory of Open Access Journals (Sweden)

Tom Cattaert

Full Text Available We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR with Model-Based MDR (MB-MDR. We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR, which is a generalization of Multifactor Dimensionality Reduction (MDR to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC, an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS. This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.

In vitro mineral nutrition of Curcuma longa L. affects production of volatile compounds in rhizomes after transfer to the greenhouse.

Science.gov (United States)

El-Hawaz, Rabia F; Grace, Mary H; Janbey, Alan; Lila, Mary Ann; Adelberg, Jeffrey W

2018-06-18

Turmeric is a rich source of bioactive compounds useful in both medicine and cuisine. Mineral concentrations effects (PO 4 3- , Ca 2+ , Mg 2+ , and KNO 3 ) were tested during in vitro rhizome development on the ex vitro content of volatile constituents in rhizomes after 6 months in the greenhouse. A response surface method (D-optimal criteria) was repeated in both high and low-input fertilizer treatments. Control plants were grown on Murashige and Skoog (MS) medium, acclimatized in the greenhouse and grown in the field. The volatile constituents were investigated by GC-MS. The total content of volatiles was affected by fertilizer treatments, and in vitro treatment with Ca 2+ and KNO 3 ; but PO 4 3- and Mg 2+ had no significant effect. The content was higher in the high-input fertilizer treatments (49.7 ± 9 mg/g DM) with 4 mM Ca 2+ , 60 mM KNO 3 and 5 mM NH 4 + , than the low-input fertilizer (26.6 ± 9 mg/g DM), and the MS control (15.28 ± 2.7 mg/g DM; 3 mM Ca 2+ , 20 mM K + , 39 mM NO 3 - , 20 mM NH 4 + , 1.25 mM PO 4 3- , and 1.5 mM Mg 2+ ). The interaction of Ca 2+ with KNO 3 affected curcumenol isomer I and II, germacrone, isocurcumenol, and β-elemenone content. Increasing in vitro phosphate concentration to 6.25 mM increased ex vitro neocurdione and methenolone contents. These results show that minerals in the in vitro bioreactor medium during rhizome development affected biosynthesis of turmeric volatile components after transfer to the greenhouse six months later. The multi-factor design identified 1) nutrient regulation of specific components within unique phytochemical profile for Curcuma longa L. clone 35-1 and 2) the varied phytochemical profiles were maintained with integrity during the greenhouse growth in high fertility conditions.

The multi-factor energy input–output model

International Nuclear Information System (INIS)

Guevara, Zeus; Domingos, Tiago

2017-01-01

Energy input–output analysis (EIO analysis) is a noteworthy tool for the analysis of the role of energy in the economy. However, it has relied on models that provide a limited description of energy flows in the economic system and do not allow an adequate analysis of energy efficiency. This paper introduces a novel energy input–output model, the multi-factor energy input–output model (MF-EIO model), which is obtained from a partitioning of a hybrid-unit input–output system of the economy. This model improves on current models by describing the energy flows according to the processes of energy conversion and the levels of energy use in the economy. It characterizes the vector of total energy output as a function of seven factors: two energy efficiency indicators; two characteristics of end-use energy consumption; and three economic features of the rest of the economy. Moreover, it is consistent with the standard model for EIO analysis, i.e., the hybrid-unit model. This paper also introduces an approximate version of the MF-EIO model, which is equivalent to the former under equal energy prices for industries and final consumers, but requires less data processing. The latter is composed by two linked models: a model of the energy sector in physical units, and a model of the rest of the economy in monetary units. In conclusion, the proposed modelling framework improves EIO analysis and extends EIO applications to the accounting for energy efficiency of the economy. - Highlights: • A novel energy input–output model is introduced. • It allows a more adequate analysis of energy flows than current models. • It describes energy flows according to processes of energy conversion and use. • It can be used for other environmental applications (material use and emissions). • An approximate version of the model is introduced, simpler and less data intensive.

Modelling electricity futures prices using seasonal path-dependent volatility

International Nuclear Information System (INIS)

Fanelli, Viviana; Maddalena, Lucia; Musti, Silvana

2016-01-01

Highlights: • A no-arbitrage term structure model is applied to the electricity market. • Volatility parameters of the HJM model are estimated by using German data. • The model captures the seasonal price behaviour. • Electricity futures prices are forecasted. • Call options are evaluated according to different strike prices. - Abstract: The liberalization of electricity markets gave rise to new patterns of futures prices and the need of models that could efficiently describe price dynamics grew exponentially, in order to improve decision making for all of the agents involved in energy issues. Although there are papers focused on modelling electricity as a flow commodity by using Heath et al. (1992) approach in order to price futures contracts, the literature is scarce on attempts to consider a seasonal volatility as input to models. In this paper, we propose a futures price model that allows looking into observed stylized facts in the electricity market, in particular stochastic price variability, and periodic behavior. We consider a seasonal path-dependent volatility for futures returns that are modelled in Heath et al. (1992) framework and we obtain the dynamics of futures prices. We use these series to price the underlying asset of a call option in a risk management perspective. We test the model on the German electricity market, and we find that it is accurate in futures and option value estimates. In addition, the obtained results and the proposed methodology can be useful as a starting point for risk management or portfolio optimization under uncertainty in the current context of energy markets.

On the realized volatility of the ECX CO2 emissions 2008 futures contract: distribution, dynamics and forecasting

International Nuclear Information System (INIS)

Chevallier, Julien; Sevi, Benoit

2009-01-01

The recent implementation of the EU Emissions Trading Scheme (EU ETS) in January 2005 created new financial risks for emitting firms. To deal with these risks, options are traded since October 2006. Because the EU ETS is a new market, the relevant underlying model for option pricing is still a controversial issue. This article improves our understanding of this issue by characterizing the conditional and unconditional distributions of the realized volatility for the 2008 futures contract in the European Climate Exchange (ECX), which is valid during Phase II (2008-2012) of the EU ETS. The realized volatility measures from naive, kernel-based and sub-sampling estimators are used to obtain inferences about the distributional and dynamic properties of the ECX emissions futures volatility. The distribution of the daily realized volatility in logarithmic form is shown to be close to normal. The mixture-of-distributions hypothesis is strongly rejected, as the returns standardized using daily measures of volatility clearly departs from normality. A simplified HAR-RV model (Corsi, 2009) with only a weekly component, which reproduces long memory properties of the series, is then used to model the volatility dynamics. Finally, the predictive accuracy of the HAR-RV model is tested against GARCH specifications using one-step-ahead forecasts, which confirms the HAR-RV superior ability. Our conclusions indicate that (i) the standard Brownian motion is not an adequate tool for option pricing in the EU ETS, and (ii) a jump component should be included in the stochastic process to price options, thus providing more efficient tools for risk-management activities. (authors)

Multifactor Assessment of Metabolic Syndrome Risk in Uzbek Children and Adolescents with Obesity

Directory of Open Access Journals (Sweden)

Gulnara N. Rakhimova

2016-03-01

Full Text Available Metabolic syndrome (MetS contributes to early atherosclerotic changes of blood vessels and type 2 diabetes mellitusnot only among adults, but among children and adolescents, causing onset and progression of severe diseases resulting in early disablement and death. Multifactor analysis of MetS risk in Uzbek children and adolescents with exogenous-constitutional obesity (ECO was the purpose of the study. The study included 100 Uzbek children and adolescents with ECO aged from 6 to 16 (mean age 11.7±0.25 years—54(54.0% boys and 46(46.0% girls. Prognostic matrix was made up by means of a modification of Bayesian probability by E. Shigan (1986. Mathematical analysis confirmed a high degree of risk for MetS onset and progression in obese patients with disorders of lipid profile and hemodynamics. MetS risk is 8.2 times higher with levels of HDL-C 3.0, HbA1c >6.7%, and obesity onset before 5 years of age.

Stochastic arbitrage return and its implication for option pricing

Science.gov (United States)

Fedotov, Sergei; Panayides, Stephanos

2005-01-01

The purpose of this work is to explore the role that random arbitrage opportunities play in pricing financial derivatives. We use a non-equilibrium model to set up a stochastic portfolio, and for the random arbitrage return, we choose a stationary ergodic random process rapidly varying in time. We exploit the fact that option price and random arbitrage returns change on different time scales which allows us to develop an asymptotic pricing theory involving the central limit theorem for random processes. We restrict ourselves to finding pricing bands for options rather than exact prices. The resulting pricing bands are shown to be independent of the detailed statistical characteristics of the arbitrage return. We find that the volatility “smile” can also be explained in terms of random arbitrage opportunities.

The interpolation method of stochastic functions and the stochastic variational principle

International Nuclear Information System (INIS)

Liu Xianbin; Chen Qiu

1993-01-01

Uncertainties have been attaching more importance to increasingly in modern engineering structural design. Viewed on an appropriate scale, the inherent physical attributes (material properties) of many structural systems always exhibit some patterns of random variation in space and time, generally the random variation shows a small parameter fluctuation. For a linear mechanical system, the random variation is modeled as a random one of a linear partial differential operator and, in stochastic finite element method, a random variation of a stiffness matrix. Besides the stochasticity of the structural physical properties, the influences of random loads which always represent themselves as the random boundary conditions bring about much more complexities in structural analysis. Now the stochastic finite element method or the probabilistic finite element method is used to study the structural systems with random physical parameters, whether or not the loads are random. Differing from the general finite element theory, the main difficulty which the stochastic finite element method faces is the inverse operation of stochastic operators and stochastic matrices, since the inverse operators and the inverse matrices are statistically correlated to the random parameters and random loads. So far, many efforts have been made to obtain the reasonably approximate expressions of the inverse operators and inverse matrices, such as Perturbation Method, Neumann Expansion Method, Galerkin Method (in appropriate Hilbert Spaces defined for random functions), Orthogonal Expansion Method. Among these methods, Perturbation Method appear to be the most available. The advantage of these methods is that the fairly accurate response statistics can be obtained under the condition of the finite information of the input. However, the second-order statistics obtained by use of Perturbation Method and Neumann Expansion Method are not always the appropriate ones, because the relevant second

Stochastic thermodynamics

Science.gov (United States)

Eichhorn, Ralf; Aurell, Erik

2014-04-01

'Stochastic thermodynamics as a conceptual framework combines the stochastic energetics approach introduced a decade ago by Sekimoto [1] with the idea that entropy can consistently be assigned to a single fluctuating trajectory [2]'. This quote, taken from Udo Seifert's [3] 2008 review, nicely summarizes the basic ideas behind stochastic thermodynamics: for small systems, driven by external forces and in contact with a heat bath at a well-defined temperature, stochastic energetics [4] defines the exchanged work and heat along a single fluctuating trajectory and connects them to changes in the internal (system) energy by an energy balance analogous to the first law of thermodynamics. Additionally, providing a consistent definition of trajectory-wise entropy production gives rise to second-law-like relations and forms the basis for a 'stochastic thermodynamics' along individual fluctuating trajectories. In order to construct meaningful concepts of work, heat and entropy production for single trajectories, their definitions are based on the stochastic equations of motion modeling the physical system of interest. Because of this, they are valid even for systems that are prevented from equilibrating with the thermal environment by external driving forces (or other sources of non-equilibrium). In that way, the central notions of equilibrium thermodynamics, such as heat, work and entropy, are consistently extended to the non-equilibrium realm. In the (non-equilibrium) ensemble, the trajectory-wise quantities acquire distributions. General statements derived within stochastic thermodynamics typically refer to properties of these distributions, and are valid in the non-equilibrium regime even beyond the linear response. The extension of statistical mechanics and of exact thermodynamic statements to the non-equilibrium realm has been discussed from the early days of statistical mechanics more than 100 years ago. This debate culminated in the development of linear response

Augmenting collider searches and enhancing discovery potentials through stochastic jet grooming

Science.gov (United States)

Roy, Tuhin S.; Thalapillil, Arun M.

2017-04-01

The jet trimming procedure has been demonstrated to greatly improve event reconstruction in hadron collisions by mitigating contamination due initial state radiation, multiple interactions, and event pileup. Meanwhile, Qjets—a nondeterministic approach to tree-based jet substructure—has been shown to be a powerful technique in decreasing random statistical fluctuations, yielding significant effective luminosity improvements. This manifests through an improvement in the significance S /δ B , relative to conventional methods. Qjets also provides novel observables in many cases, like mass-volatility, that could be used to further discriminate between signal and background events. The statistical robustness and volatility observables, for tagging, are obtained simultaneously. We explore here a combination of the two techniques, and demonstrate that significant enhancements in discovery potentials may be obtained in nontrivial ways. We will illustrate this by considering a diboson resonance analysis as a case study, enabling us to interpolate between scenarios where the gains are purely due to statistical robustness and scenarios where the gains are also reinforced by volatility variable discriminants. The former, for instance, is applicable to digluon/diquark resonances, while the latter will be of relevance to di -W±/di -Z0 resonances, where the boosted vector bosons are decaying hadronically and have an intrinsic mass scale attached to them. We argue that one can enhance signal significance and discovery potentials markedly through stochastic grooming, and help augment studies at the Large Hadron Collider and future hadron colliders.

Volatile and non-volatile/semi-volatile compounds and in vitro bioactive properties of Chilean Ulmo (Eucryphia cordifolia Cav.) honey.

Science.gov (United States)

Acevedo, Francisca; Torres, Paulina; Oomah, B Dave; de Alencar, Severino Matias; Massarioli, Adna Prado; Martín-Venegas, Raquel; Albarral-Ávila, Vicenta; Burgos-Díaz, César; Ferrer, Ruth; Rubilar, Mónica

2017-04-01

Ulmo honey originating from Eucryphia cordifolia tree, known locally in the Araucania region as the Ulmo tree is a natural product with valuable nutritional and medicinal qualities. It has been used in the Mapuche culture to treat infections. This study aimed to identify the volatile and non-volatile/semi-volatile compounds of Ulmo honey and elucidate its in vitro biological properties by evaluating its antioxidant, antibacterial, antiproliferative and hemolytic properties and cytotoxicity in Caco-2 cells. Headspace volatiles of Ulmo honey were isolated by solid-phase microextraction (SPME); non-volatiles/semi-volatiles were obtained by removing all saccharides with acidified water and the compounds were identified by GC/MS analysis. Ulmo honey volatiles consisted of 50 compounds predominated by 20 flavor components. Two of the volatile compounds, lyrame and anethol have never been reported before as honey compounds. The non-volatile/semi-volatile components of Ulmo honey comprised 27 compounds including 13 benzene derivatives accounting 75% of the total peak area. Ulmo honey exhibited weak antioxidant activity but strong antibacterial activity particularly against gram-negative bacteria and methicillin-resistant Staphylococcus aureus (MRSA), the main strain involved in wounds and skin infections. At concentrations >0.5%, Ulmo honey reduced Caco-2 cell viability, released lactate dehydrogenase (LDH) and increased reactive oxygen species (ROS) production in a dose dependent manner in the presence of foetal bovine serum (FBS). The wide array of volatile and non-volatile/semi-volatile constituents of Ulmo honey rich in benzene derivatives may partly account for its strong antibacterial and antiproliferative properties important for its therapeutic use. Our results indicate that Ulmo honey can potentially inhibit cancer growth at least partly by modulating oxidative stress. Copyright © 2017 Elsevier Ltd. All rights reserved.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas

2017-12-27

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas; Richtarik, Peter

2017-01-01

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Stochastic neuron models

CERN Document Server

Greenwood, Priscilla E

2016-01-01

This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise. This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may contribute neuroscience insight. An extensive bibliography is included. Dr. Priscilla E. Greenwood is a Professor Emerita in the Department of Mathematics at the University of British Columbia. Dr. Lawrence M. Ward is a Professor in the Department of Psychology and the Brain...

Iodine volatility

International Nuclear Information System (INIS)

Beahm, E.C.; Shockley, W.E.

1984-01-01

The ultimate aim of this program is to couple experimental aqueous iodine volatilities to a fission product release model. Iodine partition coefficients, for inorganic iodine, have been measured during hydrolysis and radiolysis. The hydrolysis experiments have illustrated the importance of reaction time on iodine volatility. However, radiolysis effects can override hydrolysis in determining iodine volatility. In addition, silver metal in radiolysis samples can react to form silver iodide accompanied by a decrease in iodine volatility. Experimental data are now being coupled to an iodine transport and release model that was developed in the Federal Republic of Germany

Effect of five enological practices and of the general phenolic composition on fermentation-related aroma compounds in Mencia young red wines.

Science.gov (United States)

Añón, Ana; López, Jorge F; Hernando, Diego; Orriols, Ignacio; Revilla, Eugenio; Losada, Manuel M

2014-04-01

The effects of five technological procedures and of the contents of total anthocyanins and condensed tannins on 19 fermentation-related aroma compounds of young red Mencia wines were studied. Multifactor ANOVA revealed that levels of those volatiles changed significantly over the length of storage in bottles and, to a lesser extent, due to other technological factors considered; total anthocyanins and condensed tannins also changed significantly as a result of the five practices assayed. Five aroma compounds possessed an odour activity value >1 in all wines, and another four in some wines. Linear correlation among volatile compounds and general phenolic composition revealed that total anthocyanins were highly related to 14 different aroma compounds. Multifactor ANOVA, considering the content of total anthocyanins as a sixth random factor, revealed that this parameter affected significantly the contents of ethyl lactate, ethyl isovalerate, 1-pentanol and ethyl octanoate. Thus, the aroma of young red Mencia wines may be affected by levels of total anthocyanins. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multifactor investigation of relative postirradiation changes in various types of behavioural reactions in rats

International Nuclear Information System (INIS)

Davydov, B.I.; Tikhonchuk, V.S.; Karpov, V.N.; Ushakov, I.B.

1989-01-01

The use of the methods of multifactor, orthogonal and composition planning in studying the behavioural disturbances in rats after γ-irradiation with doses of 0.258 to 1.29 C/kg and the application of the proposed method of discrimination of effects by empirical models permitted to establish the informative and adequate dependences of the probability of these disturbances on dose of nonuniform irradiation and the degree of strengthening of the conditioned reflex. Within the range of the studied factors both the value of the dose of whole-body irradiation and the degree of strengthening of the conditioned reflex significantly affected the probability of fulfilling the task by the animals the significance of the radiation dose being several times higher. The effects of the interaction of the two factors, that is, irradiation and the radiation affection, were insignificant in changing the behavioural reactions under study

Stochastic tools in turbulence

CERN Document Server

Lumey, John L

2012-01-01

Stochastic Tools in Turbulence discusses the available mathematical tools to describe stochastic vector fields to solve problems related to these fields. The book deals with the needs of turbulence in relation to stochastic vector fields, particularly, on three-dimensional aspects, linear problems, and stochastic model building. The text describes probability distributions and densities, including Lebesgue integration, conditional probabilities, conditional expectations, statistical independence, lack of correlation. The book also explains the significance of the moments, the properties of the

Efficacy and safety of a multifactor intervention to improve therapeutic adherence in patients with chronic obstructive pulmonary disease (COPD: protocol for the ICEPOC study

Directory of Open Access Journals (Sweden)

Prados-Torres Daniel

2011-02-01

Full Text Available Abstract Background Low therapeutic adherence to medication is very common. Clinical effectiveness is related to dose rate and route of administration and so poor therapeutic adherence can reduce the clinical benefit of treatment. The therapeutic adherence of patients with chronic obstructive pulmonary disease (COPD is extremely poor according to most studies. The research about COPD adherence has mainly focussed on quantifying its effect, and few studies have researched factors that affect non-adherence. Our study will evaluate the effectiveness of a multifactor intervention to improve the therapeutic adherence of COPD patients. Methods/Design A randomized controlled clinical trial with 140 COPD diagnosed patients selected by a non-probabilistic method of sampling. Subjects will be randomly allocated into two groups, using the block randomization technique. Every patient in each group will be visited four times during the year of the study. Intervention: Motivational aspects related to adherence (beliefs and behaviour: group and individual interviews; cognitive aspects: information about illness; skills: inhaled technique training. Reinforcement of the cognitive-emotional aspects and inhaled technique training will be carried out in all visits of the intervention group. Discussion Adherence to a prescribed treatment involves a behavioural change. Cognitive, emotional and motivational aspects influence this change and so we consider the best intervention procedure to improve adherence would be a cognitive and emotional strategy which could be applied in daily clinical practice. Our hypothesis is that the application of a multifactor intervention (COPD information, dose reminders and reinforcing audiovisual material, motivational aspects and inhalation technique training to COPD patients taking inhaled treatment will give a 25% increase in the number of patients showing therapeutic adherence in this group compared to the control group. We will

Stochastic processes in cell biology

CERN Document Server

Bressloff, Paul C

2014-01-01

This book develops the theory of continuous and discrete stochastic processes within the context of cell biology.  A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods.   This text is primarily...

Asymmetric Realized Volatility Risk

Directory of Open Access Journals (Sweden)

David E. Allen

2014-06-01

Full Text Available In this paper, we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are nearly Gaussian, this unpredictability brings considerably more uncertainty to the empirically relevant ex ante distribution of returns. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized volatility model, which incorporates the fact that realized volatility series are systematically more volatile in high volatility periods. Returns in this framework display time varying volatility, skewness and kurtosis. We provide a detailed account of the empirical advantages of the model using data on the S&P 500 index and eight other indexes and stocks.

Stochastic pump effect and geometric phases in dissipative and stochastic systems

Energy Technology Data Exchange (ETDEWEB)

Sinitsyn, Nikolai [Los Alamos National Laboratory

2008-01-01

The success of Berry phases in quantum mechanics stimulated the study of similar phenomena in other areas of physics, including the theory of living cell locomotion and motion of patterns in nonlinear media. More recently, geometric phases have been applied to systems operating in a strongly stochastic environment, such as molecular motors. We discuss such geometric effects in purely classical dissipative stochastic systems and their role in the theory of the stochastic pump effect (SPE).

DOES ENERGY CONSUMPTION VOLATILITY AFFECT REAL GDP VOLATILITY? AN EMPIRICAL ANALYSIS FOR THE UK

Directory of Open Access Journals (Sweden)

Abdul Rashid

2013-10-01

Full Text Available This paper empirically examines the relation between energy consumption volatility and unpredictable variations in real gross domestic product (GDP in the UK. Estimating the Markov switching ARCH model we find a significant regime switching in the behavior of both energy consumption and GDP volatility. The results from the Markov regime-switching model show that the variability of energy consumption has a significant role to play in determining the behavior of GDP volatilities. Moreover, the results suggest that the impacts of unpredictable variations in energy consumption on GDP volatility are asymmetric, depending on the intensity of volatility. In particular, we find that while there is no significant contemporaneous relationship between energy consumption volatility and GDP volatility in the first (low-volatility regime, GDP volatility is significantly positively related to the volatility of energy utilization in the second (high-volatility regime.

Multi-factor challenge/response approach for remote biometric authentication

Science.gov (United States)

Al-Assam, Hisham; Jassim, Sabah A.

2011-06-01

Although biometric authentication is perceived to be more reliable than traditional authentication schemes, it becomes vulnerable to many attacks when it comes to remote authentication over open networks and raises serious privacy concerns. This paper proposes a biometric-based challenge-response approach to be used for remote authentication between two parties A and B over open networks. In the proposed approach, a remote authenticator system B (e.g. a bank) challenges its client A who wants to authenticate his/her self to the system by sending a one-time public random challenge. The client A responds by employing the random challenge along with secret information obtained from a password and a token to produce a one-time cancellable representation of his freshly captured biometric sample. The one-time biometric representation, which is based on multi-factor, is then sent back to B for matching. Here, we argue that eavesdropping of the one-time random challenge and/or the resulting one-time biometric representation does not compromise the security of the system, and no information about the original biometric data is leaked. In addition to securing biometric templates, the proposed protocol offers a practical solution for the replay attack on biometric systems. Moreover, we propose a new scheme for generating a password-based pseudo random numbers/permutation to be used as a building block in the proposed approach. The proposed scheme is also designed to provide protection against repudiation. We illustrate the viability and effectiveness of the proposed approach by experimental results based on two biometric modalities: fingerprint and face biometrics.

Sequential stochastic optimization

CERN Document Server

Cairoli, Renzo

1996-01-01

Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-paramet

Realized Volatility Risk

NARCIS (Netherlands)

D.E. Allen (David); M.J. McAleer (Michael); M. Scharth (Marcel)

2013-01-01

textabstractIn this paper we document that realized variation measures constructed from highfrequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive.

Stochastic Optimization of Wind Turbine Power Factor Using Stochastic Model of Wind Power

DEFF Research Database (Denmark)

Chen, Peiyuan; Siano, Pierluigi; Bak-Jensen, Birgitte

2010-01-01

This paper proposes a stochastic optimization algorithm that aims to minimize the expectation of the system power losses by controlling wind turbine (WT) power factors. This objective of the optimization is subject to the probability constraints of bus voltage and line current requirements....... The optimization algorithm utilizes the stochastic models of wind power generation (WPG) and load demand to take into account their stochastic variation. The stochastic model of WPG is developed on the basis of a limited autoregressive integrated moving average (LARIMA) model by introducing a crosscorrelation...... structure to the LARIMA model. The proposed stochastic optimization is carried out on a 69-bus distribution system. Simulation results confirm that, under various combinations of WPG and load demand, the system power losses are considerably reduced with the optimal setting of WT power factor as compared...

Singular stochastic differential equations

CERN Document Server

Cherny, Alexander S

2005-01-01

The authors introduce, in this research monograph on stochastic differential equations, a class of points termed isolated singular points. Stochastic differential equations possessing such points (called singular stochastic differential equations here) arise often in theory and in applications. However, known conditions for the existence and uniqueness of a solution typically fail for such equations. The book concentrates on the study of the existence, the uniqueness, and, what is most important, on the qualitative behaviour of solutions of singular stochastic differential equations. This is done by providing a qualitative classification of isolated singular points, into 48 possible types.

The Multi-factor Predictive Seis &Gis Model of Ecological, Genetical, Population Health Risk and Bio-geodynamic Processes In Geopathogenic Zones

Science.gov (United States)

Bondarenko, Y.

I. Goal and Scope. Human birth rate decrease, death-rate growth and increase of mu- tagenic deviations risk take place in geopathogenic and anthropogenic hazard zones. Such zones create unfavourable conditions for reproductive process of future genera- tions. These negative trends should be considered as a protective answer of the com- plex biosocial system to the appearance of natural and anthropogenic risk factors that are unfavourable for human health. The major goals of scientific evaluation and de- crease of risk of appearance of hazardous processes on the territory of Dnipropetrovsk, along with creation of the multi-factor predictive Spirit-Energy-Information Space "SEIS" & GIS Model of ecological, genetical and population health risk in connection with dangerous bio-geodynamic processes, were: multi-factor modeling and correla- tion of natural and anthropogenic environmental changes and those of human health; determination of indicators that show the risk of destruction structures appearance on different levels of organization and functioning of the city ecosystem (geophys- ical and geochemical fields, soil, hydrosphere, atmosphere, biosphere); analysis of regularities of natural, anthropogenic, and biological rhythms' interactions. II. Meth- ods. The long spatio-temporal researches (Y. Bondarenko, 1996, 2000) have proved that the ecological, genetic and epidemiological processes are in connection with de- velopment of dangerous bio-geophysical and bio-geodynamic processes. Mathemat- ical processing of space photos, lithogeochemical and geophysical maps with use of JEIS o and ERDAS o computer systems was executed at the first stage of forma- tion of multi-layer geoinformation model "Dnipropetrovsk ARC View GIS o. The multi-factor nonlinear correlation between solar activity and cosmic ray variations, geophysical, geodynamic, geochemical, atmospheric, technological, biological, socio- economical processes and oncologic case rate frequency, general and primary

Realized volatility and absolute return volatility: a comparison indicating market risk.

Science.gov (United States)

Zheng, Zeyu; Qiao, Zhi; Takaishi, Tetsuya; Stanley, H Eugene; Li, Baowen

2014-01-01

Measuring volatility in financial markets is a primary challenge in the theory and practice of risk management and is essential when developing investment strategies. Although the vast literature on the topic describes many different models, two nonparametric measurements have emerged and received wide use over the past decade: realized volatility and absolute return volatility. The former is strongly favored in the financial sector and the latter by econophysicists. We examine the memory and clustering features of these two methods and find that both enable strong predictions. We compare the two in detail and find that although realized volatility has a better short-term effect that allows predictions of near-future market behavior, absolute return volatility is easier to calculate and, as a risk indicator, has approximately the same sensitivity as realized volatility. Our detailed empirical analysis yields valuable guidelines for both researchers and market participants because it provides a significantly clearer comparison of the strengths and weaknesses of the two methods.

Realized volatility and absolute return volatility: a comparison indicating market risk.

Directory of Open Access Journals (Sweden)

Zeyu Zheng

Full Text Available Measuring volatility in financial markets is a primary challenge in the theory and practice of risk management and is essential when developing investment strategies. Although the vast literature on the topic describes many different models, two nonparametric measurements have emerged and received wide use over the past decade: realized volatility and absolute return volatility. The former is strongly favored in the financial sector and the latter by econophysicists. We examine the memory and clustering features of these two methods and find that both enable strong predictions. We compare the two in detail and find that although realized volatility has a better short-term effect that allows predictions of near-future market behavior, absolute return volatility is easier to calculate and, as a risk indicator, has approximately the same sensitivity as realized volatility. Our detailed empirical analysis yields valuable guidelines for both researchers and market participants because it provides a significantly clearer comparison of the strengths and weaknesses of the two methods.

Unstable volatility

DEFF Research Database (Denmark)

Casas, Isabel; Gijbels, Irène

2012-01-01

The objective of this paper is to introduce the break-preserving local linear (BPLL) estimator for the estimation of unstable volatility functions for independent and asymptotically independent processes. Breaks in the structure of the conditional mean and/or the volatility functions are common...... in Finance. Nonparametric estimators are well suited for these events due to the flexibility of their functional form and their good asymptotic properties. However, the local polynomial kernel estimators are not consistent at points where the volatility function has a break. The estimator presented...

Functional Abstraction of Stochastic Hybrid Systems

NARCIS (Netherlands)

Bujorianu, L.M.; Blom, Henk A.P.; Hermanns, H.

2006-01-01

The verification problem for stochastic hybrid systems is quite difficult. One method to verify these systems is stochastic reachability analysis. Concepts of abstractions for stochastic hybrid systems are needed to ease the stochastic reachability analysis. In this paper, we set up different ways

Stochastic quantisation: theme and variation

International Nuclear Information System (INIS)

Klauder, J.R.; Kyoto Univ.

1987-01-01

The paper on stochastic quantisation is a contribution to the book commemorating the sixtieth birthday of E.S. Fradkin. Stochastic quantisation reformulates Euclidean quantum field theory in the language of Langevin equations. The generalised free field is discussed from the viewpoint of stochastic quantisation. An artificial family of highly singular model theories wherein the space-time derivatives are dropped altogether is also examined. Finally a modified form of stochastic quantisation is considered. (U.K.)

STOCHASTIC ASSESSMENT OF NIGERIAN STOCHASTIC ...

African Journals Online (AJOL)

eobe

STOCHASTIC ASSESSMENT OF NIGERIAN WOOD FOR BRIDGE DECKS ... abandoned bridges with defects only in their decks in both rural and urban locations can be effectively .... which can be seen as the detection of rare physical.

Pluto's Volatile Transport

Science.gov (United States)

Young, Leslie

2012-10-01

Pluto's varying subsolar latitude and heliocentric distance leads to large variations in the surface volatile distribution and surface pressure. I present results of new volatile transport models (Young 2012a, b). The models include insolation, thermal emission, subsurface conduction, heating of a volatile slab, internal heat flux, latent heat of sublimation, and strict global mass balance. Numeric advances include initial conditions that allow for rapid convergence, efficient computation with matrix arithmetic, and stable Crank-Nicholson timesteps for both bare and volatile-covered areas. Runs of the model show six distinct seasons on Pluto. (1) As Pluto approaches perihelion, the volatiles on the old winter pole (the Rotational North Pole, RNP) becomes more directly illuminated , and the pressure and albedo rise rapidly. (2) When a new ice cap forms on the Rotational South Pole, RSP, volatiles are exchanged between poles. The pressure and albedo change more slowly. (3) When all volatiles have sublimed from the RNP, the albedo and pressure drop rapidly. (4-6) A similar pattern is repeated near aphelion with a reversal of the roles and the poles. I will compare results with earlier Pluto models of Hansen and Paige (1996), show the dependence on parameters such as substrate inertia, and make predictions for the New Horizons flyby of Pluto in 2015. This work was supported, in part, by funding from NASA Planetary Atmospheres Grant NNG06GF32G and the Spitzer project (JPL research support Agreement 1368573). Hansen, C. J. and D. A. Paige 1996. Seasonal Nitrogen Cycles on Pluto. Icarus 120, 247-265. Young, L. A. 2012a. Volatile transport on inhomogeneous surfaces: I - Analytic expressions, with application to Pluto’s day. Icarus, in press Young, L. A. 2012b. Volatile transport on inhomogeneous surfaces: II. Numerical calculations, with application to Pluto's season. In preparation.

Stochastic quantization and gravity

International Nuclear Information System (INIS)

Rumpf, H.

1984-01-01

We give a preliminary account of the application of stochastic quantization to the gravitational field. We start in Section I from Nelson's formulation of quantum mechanics as Newtonian stochastic mechanics and only then introduce the Parisi-Wu stochastic quantization scheme on which all the later discussion will be based. In Section II we present a generalization of the scheme that is applicable to fields in physical (i.e. Lorentzian) space-time and treat the free linearized gravitational field in this manner. The most remarkable result of this is the noncausal propagation of conformal gravitons. Moreover the concept of stochastic gauge-fixing is introduced and a complete discussion of all the covariant gauges is given. A special symmetry relating two classes of covariant gauges is exhibited. Finally Section III contains some preliminary remarks on full nonlinear gravity. In particular we argue that in contrast to gauge fields the stochastic gravitational field cannot be transformed to a Gaussian process. (Author)

Probabilistic Forecasts of Wind Power Generation by Stochastic Differential Equation Models

DEFF Research Database (Denmark)

Møller, Jan Kloppenborg; Zugno, Marco; Madsen, Henrik

2016-01-01

The increasing penetration of wind power has resulted in larger shares of volatile sources of supply in power systems worldwide. In order to operate such systems efficiently, methods for reliable probabilistic forecasts of future wind power production are essential. It is well known...... that the conditional density of wind power production is highly dependent on the level of predicted wind power and prediction horizon. This paper describes a new approach for wind power forecasting based on logistic-type stochastic differential equations (SDEs). The SDE formulation allows us to calculate both state......-dependent conditional uncertainties as well as correlation structures. Model estimation is performed by maximizing the likelihood of a multidimensional random vector while accounting for the correlation structure defined by the SDE formulation. We use non-parametric modelling to explore conditional correlation...

Stochastic climate theory

NARCIS (Netherlands)

Gottwald, G.A.; Crommelin, D.T.; Franzke, C.L.E.; Franzke, C.L.E.; O'Kane, T.J.

2017-01-01

In this chapter we review stochastic modelling methods in climate science. First we provide a conceptual framework for stochastic modelling of deterministic dynamical systems based on the Mori-Zwanzig formalism. The Mori-Zwanzig equations contain a Markov term, a memory term and a term suggestive of

2–stage stochastic Runge–Kutta for stochastic delay differential equations

Energy Technology Data Exchange (ETDEWEB)

Rosli, Norhayati; Jusoh Awang, Rahimah [Faculty of Industrial Science and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Pahang (Malaysia); Bahar, Arifah; Yeak, S. H. [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia)

2015-05-15

This paper proposes a newly developed one-step derivative-free method, that is 2-stage stochastic Runge-Kutta (SRK2) to approximate the solution of stochastic delay differential equations (SDDEs) with a constant time lag, r > 0. General formulation of stochastic Runge-Kutta for SDDEs is introduced and Stratonovich Taylor series expansion for numerical solution of SRK2 is presented. Local truncation error of SRK2 is measured by comparing the Stratonovich Taylor expansion of the exact solution with the computed solution. Numerical experiment is performed to assure the validity of the method in simulating the strong solution of SDDEs.

Space-time-modulated stochastic processes

Science.gov (United States)

Giona, Massimiliano

2017-10-01

Starting from the physical problem associated with the Lorentzian transformation of a Poisson-Kac process in inertial frames, the concept of space-time-modulated stochastic processes is introduced for processes possessing finite propagation velocity. This class of stochastic processes provides a two-way coupling between the stochastic perturbation acting on a physical observable and the evolution of the physical observable itself, which in turn influences the statistical properties of the stochastic perturbation during its evolution. The definition of space-time-modulated processes requires the introduction of two functions: a nonlinear amplitude modulation, controlling the intensity of the stochastic perturbation, and a time-horizon function, which modulates its statistical properties, providing irreducible feedback between the stochastic perturbation and the physical observable influenced by it. The latter property is the peculiar fingerprint of this class of models that makes them suitable for extension to generic curved-space times. Considering Poisson-Kac processes as prototypical examples of stochastic processes possessing finite propagation velocity, the balance equations for the probability density functions associated with their space-time modulations are derived. Several examples highlighting the peculiarities of space-time-modulated processes are thoroughly analyzed.

RES: Regularized Stochastic BFGS Algorithm

Science.gov (United States)

Mokhtari, Aryan; Ribeiro, Alejandro

2014-12-01

RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second order methods, on the other hand, is impracticable because computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both, the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian egeinvalues of the sample functions are sufficient to guarantee convergence to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.

Elitism and Stochastic Dominance

OpenAIRE

Bazen, Stephen; Moyes, Patrick

2011-01-01

Stochastic dominance has typically been used with a special emphasis on risk and inequality reduction something captured by the concavity of the utility function in the expected utility model. We claim that the applicability of the stochastic dominance approach goes far beyond risk and inequality measurement provided suitable adpations be made. We apply in the paper the stochastic dominance approach to the measurment of elitism which may be considered the opposite of egalitarianism. While the...

COVAR: Computer Program for Multifactor Relative Risks and Tests of Hypotheses Using a Variance-Covariance Matrix from Linear and Log-Linear Regression

Directory of Open Access Journals (Sweden)

Leif E. Peterson

1997-11-01

Full Text Available A computer program for multifactor relative risks, confidence limits, and tests of hypotheses using regression coefficients and a variance-covariance matrix obtained from a previous additive or multiplicative regression analysis is described in detail. Data used by the program can be stored and input from an external disk-file or entered via the keyboard. The output contains a list of the input data, point estimates of single or joint effects, confidence intervals and tests of hypotheses based on a minimum modified chi-square statistic. Availability of the program is also discussed.

Stochastic analytic regularization

International Nuclear Information System (INIS)

Alfaro, J.

1984-07-01

Stochastic regularization is reexamined, pointing out a restriction on its use due to a new type of divergence which is not present in the unregulated theory. Furthermore, we introduce a new form of stochastic regularization which permits the use of a minimal subtraction scheme to define the renormalized Green functions. (author)

On Stochastic Dependence

Science.gov (United States)

Meyer, Joerg M.

2018-01-01

The contrary of stochastic independence splits up into two cases: pairs of events being favourable or being unfavourable. Examples show that both notions have quite unexpected properties, some of them being opposite to intuition. For example, transitivity does not hold. Stochastic dependence is also useful to explain cases of Simpson's paradox.

Stochastic massless fields I: Integer spin

International Nuclear Information System (INIS)

Lim, S.C.

1981-04-01

Nelson's stochastic quantization scheme is applied to classical massless tensor potential in ''Coulomb'' gauge. The relationship between stochastic potential field in various gauges is discussed using the case of vector potential as an illustration. It is possible to identify the Euclidean tensor potential with the corresponding stochastic field in physical Minkowski space-time. Stochastic quantization of massless fields can also be carried out in terms of field strength tensors. An example of linearized stochastic gravitational field in vacuum is given. (author)

Normalization for Implied Volatility

OpenAIRE

Fukasawa, Masaaki

2010-01-01

We study specific nonlinear transformations of the Black-Scholes implied volatility to show remarkable properties of the volatility surface. Model-free bounds on the implied volatility skew are given. Pricing formulas for the European options which are written in terms of the implied volatility are given. In particular, we prove elegant formulas for the fair strikes of the variance swap and the gamma swap.

Money growth volatility and the demand for money in Germany: Friedman's volatility hypothesis revisited

OpenAIRE

Brüggemann, Imke; Nautz, Dieter

1997-01-01

Recently, the Bundesbank claimed that monetary targeting has become considerably more diffcult by the increased volatility of short-term money growth. The present paper investigates the impact of German money growth volatility on income velocity and money demand in view of Friedman's money growth volatility hypothesis. Granger-causality tests provide some evidence for a velocity-volatility linkage. However the estimation of volatility-augmented money demand functions reveals that - in contras...

Stochastic processes inference theory

CERN Document Server

Rao, Malempati M

2014-01-01

This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.

Path to Stochastic Stability: Comparative Analysis of Stochastic Learning Dynamics in Games

KAUST Repository

Jaleel, Hassan

2018-04-08

Stochastic stability is a popular solution concept for stochastic learning dynamics in games. However, a critical limitation of this solution concept is its inability to distinguish between different learning rules that lead to the same steady-state behavior. We address this limitation for the first time and develop a framework for the comparative analysis of stochastic learning dynamics with different update rules but same steady-state behavior. We present the framework in the context of two learning dynamics: Log-Linear Learning (LLL) and Metropolis Learning (ML). Although both of these dynamics have the same stochastically stable states, LLL and ML correspond to different behavioral models for decision making. Moreover, we demonstrate through an example setup of sensor coverage game that for each of these dynamics, the paths to stochastically stable states exhibit distinctive behaviors. Therefore, we propose multiple criteria to analyze and quantify the differences in the short and medium run behavior of stochastic learning dynamics. We derive and compare upper bounds on the expected hitting time to the set of Nash equilibria for both LLL and ML. For the medium to long-run behavior, we identify a set of tools from the theory of perturbed Markov chains that result in a hierarchical decomposition of the state space into collections of states called cycles. We compare LLL and ML based on the proposed criteria and develop invaluable insights into the comparative behavior of the two dynamics.

Quantum stochastics

CERN Document Server

Chang, Mou-Hsiung

2015-01-01

The classical probability theory initiated by Kolmogorov and its quantum counterpart, pioneered by von Neumann, were created at about the same time in the 1930s, but development of the quantum theory has trailed far behind. Although highly appealing, the quantum theory has a steep learning curve, requiring tools from both probability and analysis and a facility for combining the two viewpoints. This book is a systematic, self-contained account of the core of quantum probability and quantum stochastic processes for graduate students and researchers. The only assumed background is knowledge of the basic theory of Hilbert spaces, bounded linear operators, and classical Markov processes. From there, the book introduces additional tools from analysis, and then builds the quantum probability framework needed to support applications to quantum control and quantum information and communication. These include quantum noise, quantum stochastic calculus, stochastic quantum differential equations, quantum Markov semigrou...

Stochastic cooling

International Nuclear Information System (INIS)

Bisognano, J.; Leemann, C.

1982-03-01

Stochastic cooling is the damping of betatron oscillations and momentum spread of a particle beam by a feedback system. In its simplest form, a pickup electrode detects the transverse positions or momenta of particles in a storage ring, and the signal produced is amplified and applied downstream to a kicker. The time delay of the cable and electronics is designed to match the transit time of particles along the arc of the storage ring between the pickup and kicker so that an individual particle receives the amplified version of the signal it produced at the pick-up. If there were only a single particle in the ring, it is obvious that betatron oscillations and momentum offset could be damped. However, in addition to its own signal, a particle receives signals from other beam particles. In the limit of an infinite number of particles, no damping could be achieved; we have Liouville's theorem with constant density of the phase space fluid. For a finite, albeit large number of particles, there remains a residue of the single particle damping which is of practical use in accumulating low phase space density beams of particles such as antiprotons. It was the realization of this fact that led to the invention of stochastic cooling by S. van der Meer in 1968. Since its conception, stochastic cooling has been the subject of much theoretical and experimental work. The earliest experiments were performed at the ISR in 1974, with the subsequent ICE studies firmly establishing the stochastic cooling technique. This work directly led to the design and construction of the Antiproton Accumulator at CERN and the beginnings of p anti p colliding beam physics at the SPS. Experiments in stochastic cooling have been performed at Fermilab in collaboration with LBL, and a design is currently under development for a anti p accumulator for the Tevatron

Stochastic optimal control, forward-backward stochastic differential equations and the Schroedinger equation

Energy Technology Data Exchange (ETDEWEB)

Paul, Wolfgang; Koeppe, Jeanette [Institut fuer Physik, Martin Luther Universitaet, 06099 Halle (Germany); Grecksch, Wilfried [Institut fuer Mathematik, Martin Luther Universitaet, 06099 Halle (Germany)

2016-07-01

The standard approach to solve a non-relativistic quantum problem is through analytical or numerical solution of the Schroedinger equation. We show a way to go around it. This way is based on the derivation of the Schroedinger equation from conservative diffusion processes and the establishment of (several) stochastic variational principles leading to the Schroedinger equation under the assumption of a kinematics described by Nelson's diffusion processes. Mathematically, the variational principle can be considered as a stochastic optimal control problem linked to the forward-backward stochastic differential equations of Nelson's stochastic mechanics. The Hamilton-Jacobi-Bellmann equation of this control problem is the Schroedinger equation. We present the mathematical background and how to turn it into a numerical scheme for analyzing a quantum system without using the Schroedinger equation and exemplify the approach for a simple 1d problem.

Chasing volatility

DEFF Research Database (Denmark)

Caporin, Massimiliano; Rossi, Eduardo; Santucci de Magistris, Paolo

The realized volatility of financial returns is characterized by persistence and occurrence of unpreditable large increments. To capture those features, we introduce the Multiplicative Error Model with jumps (MEM-J). When a jump component is included in the multiplicative specification, the condi......The realized volatility of financial returns is characterized by persistence and occurrence of unpreditable large increments. To capture those features, we introduce the Multiplicative Error Model with jumps (MEM-J). When a jump component is included in the multiplicative specification...... estimate alternative specifications of the model using a set of daily bipower measures for 7 stock indexes and 16 individual NYSE stocks. The estimates of the jump component confirm that the probability of jumps dramatically increases during the financial crisis. Compared to other realized volatility...... models, the introduction of the jump component provides a sensible improvement in the fit, as well as for in-sample and out-of-sample volatility tail forecasts....

Stochastic Analysis : A Series of Lectures

CERN Document Server

Dozzi, Marco; Flandoli, Franco; Russo, Francesco

2015-01-01

This book presents in thirteen refereed survey articles an overview of modern activity in stochastic analysis, written by leading international experts. The topics addressed include stochastic fluid dynamics and regularization by noise of deterministic dynamical systems; stochastic partial differential equations driven by Gaussian or Lévy noise, including the relationship between parabolic equations and particle systems, and wave equations in a geometric framework; Malliavin calculus and applications to stochastic numerics; stochastic integration in Banach spaces; porous media-type equations; stochastic deformations of classical mechanics and Feynman integrals and stochastic differential equations with reflection. The articles are based on short courses given at the Centre Interfacultaire Bernoulli of the Ecole Polytechnique Fédérale de Lausanne, Switzerland, from January to June 2012. They offer a valuable resource not only for specialists, but also for other researchers and Ph.D. students in the fields o...

Stochastic Analysis with Financial Applications

CERN Document Server

Kohatsu-Higa, Arturo; Sheu, Shuenn-Jyi

2011-01-01

Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. This book also covers the areas of backward stochastic differential equations via the (non-li

Stochastic Reachability Analysis of Hybrid Systems

CERN Document Server

Bujorianu, Luminita Manuela

2012-01-01

Stochastic reachability analysis (SRA) is a method of analyzing the behavior of control systems which mix discrete and continuous dynamics. For probabilistic discrete systems it has been shown to be a practical verification method but for stochastic hybrid systems it can be rather more. As a verification technique SRA can assess the safety and performance of, for example, autonomous systems, robot and aircraft path planning and multi-agent coordination but it can also be used for the adaptive control of such systems. Stochastic Reachability Analysis of Hybrid Systems is a self-contained and accessible introduction to this novel topic in the analysis and development of stochastic hybrid systems. Beginning with the relevant aspects of Markov models and introducing stochastic hybrid systems, the book then moves on to coverage of reachability analysis for stochastic hybrid systems. Following this build up, the core of the text first formally defines the concept of reachability in the stochastic framework and then...

Estimating the influence of U.S. ethanol policy on plant investment decisions: A real options analysis with two stochastic variables

International Nuclear Information System (INIS)

Schmit, T.M.; Luo, J.; Conrad, J.M.

2011-01-01

U.S. ethanol policies have contributed to changes in the levels and the volatilities of revenues and costs facing ethanol firms. The implications of these policies for optimal investment behavior are investigated through an extension of the real options framework that allows for the consideration of volatility in both revenue and cost components, as well as the correlation between them. The effects of policy affecting plant revenues dominate the effects of those policies affecting production costs. In the absence of these policies, much of the recent expansionary periods would have not existed and market conditions in the late-1990s would have led to some plant closures. We also show that, regardless of plant size, U.S. ethanol policy has narrowed the distance between the optimal entry and exit curves, implying a more narrow range of inactivity and indicative of a more volatile evolution for the industry than would have existed otherwise. - Highlights: ► An extended real options framework with two stochastic variables is developed. ► Ethanol expansion largely induced by the revenue-enhancing effects of policy. ► Removing effects of policy changes optimal entry/exit environment considerably. ► To expand US ethanol industry, size of policy contributions needs to grow. ► US ethanol policy has fostered more volatile industry development.

Homogenization of the stochastic Navier–Stokes equation with a stochastic slip boundary condition

KAUST Repository

Bessaih, Hakima

2015-11-02

The two-dimensional Navier–Stokes equation in a perforated domain with a dynamical slip boundary condition is considered. We assume that the dynamic is driven by a stochastic perturbation on the interior of the domain and another stochastic perturbation on the boundaries of the holes. We consider a scaling (ᵋ for the viscosity and 1 for the density) that will lead to a time-dependent limit problem. However, the noncritical scaling (ᵋ, β > 1) is considered in front of the nonlinear term. The homogenized system in the limit is obtained as a Darcy’s law with memory with two permeabilities and an extra term that is due to the stochastic perturbation on the boundary of the holes. The nonhomogeneity on the boundary contains a stochastic part that yields in the limit an additional term in the Darcy’s law. We use the two-scale convergence method after extending the solution with 0 inside the holes to pass to the limit. By Itô stochastic calculus, we get uniform estimates on the solution in appropriate spaces. Due to the stochastic integral, the pressure that appears in the variational formulation does not have enough regularity in time. This fact made us rely only on the variational formulation for the passage to the limit on the solution. We obtain a variational formulation for the limit that is solution of a Stokes system with two pressures. This two-scale limit gives rise to three cell problems, two of them give the permeabilities while the third one gives an extra term in the Darcy’s law due to the stochastic perturbation on the boundary of the holes.

Stochastic Estimation via Polynomial Chaos

Science.gov (United States)

2015-10-01

AFRL-RW-EG-TR-2015-108 Stochastic Estimation via Polynomial Chaos Douglas V. Nance Air Force Research...COVERED (From - To) 20-04-2015 – 07-08-2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Stochastic Estimation via Polynomial Chaos ...This expository report discusses fundamental aspects of the polynomial chaos method for representing the properties of second order stochastic

Remarks on stochastic acceleration

International Nuclear Information System (INIS)

Graeff, P.

1982-12-01

Stochastic acceleration and turbulent diffusion are strong turbulence problems since no expansion parameter exists. Hence the problem of finding rigorous results is of major interest both for checking approximations and for reference models. Since we have found a way of constructing such models in the turbulent diffusion case the question of the extension to stochastic acceleration now arises. The paper offers some possibilities illustrated by the case of 'stochastic free fall' which may be particularly interesting in the context of linear response theory. (orig.)

Volatility in Equilibrium

DEFF Research Database (Denmark)

Bollerslev, Tim; Sizova, Natalia; Tauchen, George

Stock market volatility clusters in time, carries a risk premium, is fractionally inte- grated, and exhibits asymmetric leverage effects relative to returns. This paper develops a first internally consistent equilibrium based explanation for these longstanding empirical facts. The model is cast i......, and the dynamic cross-correlations of the volatility measures with the returns calculated from actual high-frequency intra-day data on the S&P 500 aggregate market and VIX volatility indexes....

Stochastic modeling of stock price process induced from the conjugate heat equation

Science.gov (United States)

Paeng, Seong-Hun

2015-02-01

Currency can be considered as a ruler for values of commodities. Then the price is the measured value by the ruler. We can suppose that inflation and variation of exchange rate are caused by variation of the scale of the ruler. In geometry, variation of the scale means that the metric is time-dependent. The conjugate heat equation is the modified heat equation which satisfies the heat conservation law for the time-dependent metric space. We propose a new model of stock prices by using the stochastic process whose transition probability is determined by the kernel of the conjugate heat equation. Our model of stock prices shows how the volatility term is affected by inflation and exchange rate. This model modifies the Black-Scholes equation in light of inflation and exchange rate.

Stochastic parameterizing manifolds and non-Markovian reduced equations stochastic manifolds for nonlinear SPDEs II

CERN Document Server

Chekroun, Mickaël D; Wang, Shouhong

2015-01-01

In this second volume, a general approach is developed to provide approximate parameterizations of the "small" scales by the "large" ones for a broad class of stochastic partial differential equations (SPDEs). This is accomplished via the concept of parameterizing manifolds (PMs), which are stochastic manifolds that improve, for a given realization of the noise, in mean square error the partial knowledge of the full SPDE solution when compared to its projection onto some resolved modes. Backward-forward systems are designed to give access to such PMs in practice. The key idea consists of representing the modes with high wave numbers as a pullback limit depending on the time-history of the modes with low wave numbers. Non-Markovian stochastic reduced systems are then derived based on such a PM approach. The reduced systems take the form of stochastic differential equations involving random coefficients that convey memory effects. The theory is illustrated on a stochastic Burgers-type equation.

Stochastic spin-one massive field

International Nuclear Information System (INIS)

Lim, S.C.

1984-01-01

Stochastic quantization schemes of Nelson and Parisi and Wu are applied to a spin-one massive field. Unlike the scalar case Nelson's stochastic spin-one massive field cannot be identified with the corresponding euclidean field even if the fourth component of the euclidean coordinate is taken as equal to the real physical time. In the Parisi-Wu quantization scheme the stochastic Proca vector field has a similar property as the scalar field; which has an asymptotically stationary part and a transient part. The large equal-time limit of the expectation values of the stochastic Proca field are equal to the expectation values of the corresponding euclidean field. In the Stueckelberg formalism the Parisi-Wu scheme gives rise to a stochastic vector field which differs from the massless gauge field in that the gauge cannot be fixed by the choice of boundary condition. (orig.)

A Stochastic Maximum Principle for a Stochastic Differential Game of a Mean-Field Type

Energy Technology Data Exchange (ETDEWEB)

Hosking, John Joseph Absalom, E-mail: j.j.a.hosking@cma.uio.no [University of Oslo, Centre of Mathematics for Applications (CMA) (Norway)

2012-12-15

We construct a stochastic maximum principle (SMP) which provides necessary conditions for the existence of Nash equilibria in a certain form of N-agent stochastic differential game (SDG) of a mean-field type. The information structure considered for the SDG is of a possible asymmetric and partial type. To prove our SMP we take an approach based on spike-variations and adjoint representation techniques, analogous to that of S. Peng (SIAM J. Control Optim. 28(4):966-979, 1990) in the optimal stochastic control context. In our proof we apply adjoint representation procedures at three points. The first-order adjoint processes are defined as solutions to certain mean-field backward stochastic differential equations, and second-order adjoint processes of a first type are defined as solutions to certain backward stochastic differential equations. Second-order adjoint processes of a second type are defined as solutions of certain backward stochastic equations of a type that we introduce in this paper, and which we term conditional mean-field backward stochastic differential equations. From the resulting representations, we show that the terms relating to these second-order adjoint processes of the second type are of an order such that they do not appear in our final SMP equations. A comparable situation exists in an article by R. Buckdahn, B. Djehiche, and J. Li (Appl. Math. Optim. 64(2):197-216, 2011) that constructs a SMP for a mean-field type optimal stochastic control problem; however, the approach we take of using these second-order adjoint processes of a second type to deal with the type of terms that we refer to as the second form of quadratic-type terms represents an alternative to a development, to our setting, of the approach used in their article for their analogous type of term.

A Stochastic Maximum Principle for a Stochastic Differential Game of a Mean-Field Type

International Nuclear Information System (INIS)

Hosking, John Joseph Absalom

2012-01-01

We construct a stochastic maximum principle (SMP) which provides necessary conditions for the existence of Nash equilibria in a certain form of N-agent stochastic differential game (SDG) of a mean-field type. The information structure considered for the SDG is of a possible asymmetric and partial type. To prove our SMP we take an approach based on spike-variations and adjoint representation techniques, analogous to that of S. Peng (SIAM J. Control Optim. 28(4):966–979, 1990) in the optimal stochastic control context. In our proof we apply adjoint representation procedures at three points. The first-order adjoint processes are defined as solutions to certain mean-field backward stochastic differential equations, and second-order adjoint processes of a first type are defined as solutions to certain backward stochastic differential equations. Second-order adjoint processes of a second type are defined as solutions of certain backward stochastic equations of a type that we introduce in this paper, and which we term conditional mean-field backward stochastic differential equations. From the resulting representations, we show that the terms relating to these second-order adjoint processes of the second type are of an order such that they do not appear in our final SMP equations. A comparable situation exists in an article by R. Buckdahn, B. Djehiche, and J. Li (Appl. Math. Optim. 64(2):197–216, 2011) that constructs a SMP for a mean-field type optimal stochastic control problem; however, the approach we take of using these second-order adjoint processes of a second type to deal with the type of terms that we refer to as the second form of quadratic-type terms represents an alternative to a development, to our setting, of the approach used in their article for their analogous type of term.

Stochastic TDHF and the Boltzman-Langevin equation

International Nuclear Information System (INIS)

Suraud, E.; Reinhard, P.G.

1991-01-01

Outgoing from a time-dependent theory of correlations, we present a stochastic differential equation for the propagation of ensembles of Slater determinants, called Stochastic Time-Dependent Hartree-Fock (Stochastic TDHF). These ensembles are allowed to develop large fluctuations in the Hartree-Fock mean fields. An alternative stochastic differential equation, the Boltzmann-Langevin equation, can be derived from Stochastic TDHF by averaging over subensembles with small fluctuations

Stochastic resonance in a stochastic bistable system with additive noises and square–wave signal

International Nuclear Information System (INIS)

Feng, Guo; Xiang-Dong, Luo; Shao-Fu, Li; Yu-Rong, Zhou

2010-01-01

This paper considers the stochastic resonance in a stochastic bistable system driven by a periodic square-wave signal and a static force as well as by additive white noise and dichotomous noise from the viewpoint of signal-to-noise ratio. It finds that the signal-to-noise ratio appears as stochastic resonance behaviour when it is plotted as a function of the noise strength of the white noise and dichotomous noise, as a function of the system parameters, or as a function of the static force. Moreover, the influence of the strength of the stochastic potential force and the correlation rate of the dichotomous noise on the signal-to-noise ratio is investigated. (general)

Proboscis extension reflex platform for volatiles and semi-volatiles detection

Energy Technology Data Exchange (ETDEWEB)

Wingo, Robert M. (Los Alamos, NM); McCabe, Kirsten J. (Los Alamos, NM); Haarmann, Timothy K. (Jemez Pueblo, NM)

2010-11-30

The present invention provides an apparatus for the detection of volatile and semi-volatile chemicals using the olfactory abilities of honey bees that are trained to respond to the presence of a specific chemical in a sample of gas with the proboscis extension reflex (PER). In particular, the geometry and arrangement of the parts of the apparatus are such that the amount of surface area in contact with the sample of gas prior to its introduction to the bees is minimized to improve the detection of particular volatile and semi-volatile that have a tendency to "stick" to contacting surfaces, especially certain chemicals associated with explosives and narcotics. According to another aspect of the present invention, a pre-concentrating means is incorporated with the device to effectively increase the concentration of "sticky" chemicals presented to the insects.

Stochastic quantization of Proca field

International Nuclear Information System (INIS)

Lim, S.C.

1981-03-01

We discuss the complications that arise in the application of Nelson's stochastic quantization scheme to classical Proca field. One consistent way to obtain spin-one massive stochastic field is given. It is found that the result of Guerra et al on the connection between ground state stochastic field and the corresponding Euclidean-Markov field extends to the spin-one case. (author)

Stochastic optimization methods

CERN Document Server

Marti, Kurt

2005-01-01

Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.

Generalized Fractional Processes with Long Memory and Time Dependent Volatility Revisited

Directory of Open Access Journals (Sweden)

M. Shelton Peiris

2016-09-01

Full Text Available In recent years, fractionally-differenced processes have received a great deal of attention due to their flexibility in financial applications with long-memory. This paper revisits the class of generalized fractionally-differenced processes generated by Gegenbauer polynomials and the ARMA structure (GARMA with both the long-memory and time-dependent innovation variance. We establish the existence and uniqueness of second-order solutions. We also extend this family with innovations to follow GARCH and stochastic volatility (SV. Under certain regularity conditions, we give asymptotic results for the approximate maximum likelihood estimator for the GARMA-GARCH model. We discuss a Monte Carlo likelihood method for the GARMA-SV model and investigate finite sample properties via Monte Carlo experiments. Finally, we illustrate the usefulness of this approach using monthly inflation rates for France, Japan and the United States.

Phenomenology of stochastic exponential growth

Science.gov (United States)

Pirjol, Dan; Jafarpour, Farshid; Iyer-Biswas, Srividya

2017-06-01

Stochastic exponential growth is observed in a variety of contexts, including molecular autocatalysis, nuclear fission, population growth, inflation of the universe, viral social media posts, and financial markets. Yet literature on modeling the phenomenology of these stochastic dynamics has predominantly focused on one model, geometric Brownian motion (GBM), which can be described as the solution of a Langevin equation with linear drift and linear multiplicative noise. Using recent experimental results on stochastic exponential growth of individual bacterial cell sizes, we motivate the need for a more general class of phenomenological models of stochastic exponential growth, which are consistent with the observation that the mean-rescaled distributions are approximately stationary at long times. We show that this behavior is not consistent with GBM, instead it is consistent with power-law multiplicative noise with positive fractional powers. Therefore, we consider this general class of phenomenological models for stochastic exponential growth, provide analytical solutions, and identify the important dimensionless combination of model parameters, which determines the shape of the mean-rescaled distribution. We also provide a prescription for robustly inferring model parameters from experimentally observed stochastic growth trajectories.

Optimal Control for Stochastic Delay Evolution Equations

Energy Technology Data Exchange (ETDEWEB)

Meng, Qingxin, E-mail: mqx@hutc.zj.cn [Huzhou University, Department of Mathematical Sciences (China); Shen, Yang, E-mail: skyshen87@gmail.com [York University, Department of Mathematics and Statistics (Canada)

2016-08-15

In this paper, we investigate a class of infinite-dimensional optimal control problems, where the state equation is given by a stochastic delay evolution equation with random coefficients, and the corresponding adjoint equation is given by an anticipated backward stochastic evolution equation. We first prove the continuous dependence theorems for stochastic delay evolution equations and anticipated backward stochastic evolution equations, and show the existence and uniqueness of solutions to anticipated backward stochastic evolution equations. Then we establish necessary and sufficient conditions for optimality of the control problem in the form of Pontryagin’s maximum principles. To illustrate the theoretical results, we apply stochastic maximum principles to study two examples, an infinite-dimensional linear-quadratic control problem with delay and an optimal control of a Dirichlet problem for a stochastic partial differential equation with delay. Further applications of the two examples to a Cauchy problem for a controlled linear stochastic partial differential equation and an optimal harvesting problem are also considered.

Introduction to stochastic calculus

CERN Document Server

Karandikar, Rajeeva L

2018-01-01

This book sheds new light on stochastic calculus, the branch of mathematics that is most widely applied in financial engineering and mathematical finance. The first book to introduce pathwise formulae for the stochastic integral, it provides a simple but rigorous treatment of the subject, including a range of advanced topics. The book discusses in-depth topics such as quadratic variation, Ito formula, and Emery topology. The authors briefly address continuous semi-martingales to obtain growth estimates and study solution of a stochastic differential equation (SDE) by using the technique of random time change. Later, by using Metivier–Pellumail inequality, the solutions to SDEs driven by general semi-martingales are discussed. The connection of the theory with mathematical finance is briefly discussed and the book has extensive treatment on the representation of martingales as stochastic integrals and a second fundamental theorem of asset pricing. Intended for undergraduate- and beginning graduate-level stud...

Brownian motion, martingales, and stochastic calculus

CERN Document Server

Le Gall, Jean-François

2016-01-01

This book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales. The main tools of stochastic calculus, including Itô’s formula, the optional stopping theorem and Girsanov’s theorem, are treated in detail alongside many illustrative examples. The book also contains an introduction to Markov processes, with applications to solutions of stochastic differential equations and to connections between Brownian motion and partial differential equations. The theory of local times of semimartingales is discussed in the last chapter. Since its invention by Itô, stochastic calculus has proven to be one of the most important techniques of modern probability theory, and has been used in the most recent theoretical advances as well as in applications to other fields such as mathematical finance. Brownian Motion, Martingales, and Stochastic Calculus provides a strong theoretical background to the reader interested i...

Stochastic line motion and stochastic flux conservation for nonideal hydromagnetic models

International Nuclear Information System (INIS)

Eyink, Gregory L.

2009-01-01

We prove that smooth solutions of nonideal (viscous and resistive) incompressible magnetohydrodynamic (MHD) equations satisfy a stochastic law of flux conservation. This property implies that the magnetic flux through a surface is equal to the average of the magnetic fluxes through an ensemble of surfaces advected backward in time by the plasma velocity perturbed with a random white noise. Our result is an analog of the well-known Alfven theorem of ideal MHD and is valid for any value of the magnetic Prandtl number. A second stochastic conservation law is shown to hold at unit Prandtl number, a random version of the generalized Kelvin theorem derived by Bekenstein and Oron for ideal MHD. These stochastic conservation laws are not only shown to be consequences of the nonideal MHD equations but are proved in fact to be equivalent to those equations. We derive similar results for two more refined hydromagnetic models, Hall MHD and the two-fluid plasma model, still assuming incompressible velocities and isotropic transport coefficients. Finally, we use these results to discuss briefly the infinite-Reynolds-number limit of hydromagnetic turbulence and to support the conjecture that flux conservation remains stochastic in that limit.

Volatility and variance swaps : A comparison of quantitative models to calculate the fair volatility and variance strike

OpenAIRE

Röring, Johan

2017-01-01

Volatility is a common risk measure in the field of finance that describes the magnitude of an asset’s up and down movement. From only being a risk measure, volatility has become an asset class of its own and volatility derivatives enable traders to get an isolated exposure to an asset’s volatility. Two kinds of volatility derivatives are volatility swaps and variance swaps. The problem with volatility swaps and variance swaps is that they require estimations of the future variance and volati...

The Clean-Development Mechanism, stochastic permit prices and energy investments

International Nuclear Information System (INIS)

Hieronymi, Philipp; Schüller, David

2015-01-01

We analyze the impact on energy investments stemming from different emission permit classes, by considering permits that are allocated inside the European Emission Trading Scheme and secondary Certified Emission Reduction (sCER) permits originating from the Clean Development Mechanism. One price taking firm which is subject to emission regulation has the choice to invest in gas or wind power plant. The firm faces uncertainty regarding stochastically evolving permit prices, while it receives a premium on the electricity price for wind energy. As a first step, we determine the value of the option to invest into a gas power plant over time. Then, we calculate the investment probability of a gas power investment in a range of policy scenarios. We find that allowing the usage of sCER permits in the present policy framework has a positive impact on gas power investment. Decoupling the price processes has a similar effect. If the quota of sCER permits is doubled, the decrease in the investment probability for wind power is large. We carry out sensitivity tests for different parameter values, and find that investment behavior changes significantly with differing interest rates, the wind energy premium and volatility. - Highlights: • We model the impact of two CO 2 permit classes on energy investments. • We present a real-options framework accounting for uncertainty. • Clean Development Mechanism permits have a negative influence on investment into renewable energy. • Interest rate and volatility values have a strong impact on the results

Brownian motion and stochastic calculus

CERN Document Server

Karatzas, Ioannis

1998-01-01

This book is designed as a text for graduate courses in stochastic processes. It is written for readers familiar with measure-theoretic probability and discrete-time processes who wish to explore stochastic processes in continuous time. The vehicle chosen for this exposition is Brownian motion, which is presented as the canonical example of both a martingale and a Markov process with continuous paths. In this context, the theory of stochastic integration and stochastic calculus is developed. The power of this calculus is illustrated by results concerning representations of martingales and change of measure on Wiener space, and these in turn permit a presentation of recent advances in financial economics (option pricing and consumption/investment optimization). This book contains a detailed discussion of weak and strong solutions of stochastic differential equations and a study of local time for semimartingales, with special emphasis on the theory of Brownian local time. The text is complemented by a large num...

Variance decomposition in stochastic simulators.

Science.gov (United States)

Le Maître, O P; Knio, O M; Moraes, A

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Science.gov (United States)

Le Maître, O. P.; Knio, O. M.; Moraes, A.

2015-06-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Energy Technology Data Exchange (ETDEWEB)

Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

KAUST Repository

Le Maî tre, O. P.; Knio, O. M.; Moraes, Alvaro

2015-01-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Stochastic synaptic plasticity with memristor crossbar arrays

KAUST Repository

Naous, Rawan

2016-11-01

Memristive devices have been shown to exhibit slow and stochastic resistive switching behavior under low-voltage, low-current operating conditions. Here we explore such mechanisms to emulate stochastic plasticity in memristor crossbar synapse arrays. Interfaced with integrate-and-fire spiking neurons, the memristive synapse arrays are capable of implementing stochastic forms of spike-timing dependent plasticity which parallel mean-rate models of stochastic learning with binary synapses. We present theory and experiments with spike-based stochastic learning in memristor crossbar arrays, including simplified modeling as well as detailed physical simulation of memristor stochastic resistive switching characteristics due to voltage and current induced filament formation and collapse. © 2016 IEEE.

Stochastic synaptic plasticity with memristor crossbar arrays

KAUST Repository

Naous, Rawan; Al-Shedivat, Maruan; Neftci, Emre; Cauwenberghs, Gert; Salama, Khaled N.

2016-01-01

Memristive devices have been shown to exhibit slow and stochastic resistive switching behavior under low-voltage, low-current operating conditions. Here we explore such mechanisms to emulate stochastic plasticity in memristor crossbar synapse arrays. Interfaced with integrate-and-fire spiking neurons, the memristive synapse arrays are capable of implementing stochastic forms of spike-timing dependent plasticity which parallel mean-rate models of stochastic learning with binary synapses. We present theory and experiments with spike-based stochastic learning in memristor crossbar arrays, including simplified modeling as well as detailed physical simulation of memristor stochastic resistive switching characteristics due to voltage and current induced filament formation and collapse. © 2016 IEEE.

Endogenous Lunar Volatiles

Science.gov (United States)

McCubbin, F. M.; Liu, Y.; Barnes, J. J.; Anand, M.; Boyce, J. W.; Burney, D.; Day, J. M. D.; Elardo, S. M.; Hui, H.; Klima, R. L.; Magna, T.; Ni, P.; Steenstra, E.; Tartèse, R.; Vander Kaaden, K. E.

2018-04-01

This abstract discusses numerous outstanding questions on the topic of endogenous lunar volatiles that will need to be addressed in the coming years. Although substantial insights into endogenous lunar volatiles have been gained, more work remains.

Emerging non-volatile memories

CERN Document Server

Hong, Seungbum; Wouters, Dirk

2014-01-01

This book is an introduction to the fundamentals of emerging non-volatile memories and provides an overview of future trends in the field. Readers will find coverage of seven important memory technologies, including Ferroelectric Random Access Memory (FeRAM), Ferromagnetic RAM (FMRAM), Multiferroic RAM (MFRAM), Phase-Change Memories (PCM), Oxide-based Resistive RAM (RRAM), Probe Storage, and Polymer Memories. Chapters are structured to reflect diffusions and clashes between different topics. Emerging Non-Volatile Memories is an ideal book for graduate students, faculty, and professionals working in the area of non-volatile memory. This book also: Covers key memory technologies, including Ferroelectric Random Access Memory (FeRAM), Ferromagnetic RAM (FMRAM), and Multiferroic RAM (MFRAM), among others. Provides an overview of non-volatile memory fundamentals. Broadens readers' understanding of future trends in non-volatile memories.

Volatility Exposure for Strategic Asset Allocation

OpenAIRE

Briere, Marie; Burgues, Alexandre; Signori, Ombretta

2008-01-01

This paper examines the advantages of incorporating strategic exposure to equity volatility into the investment-opportunity set of a long-term equity investor. We consider two standard volatility investments: implied volatility and volatility risk premium strategies. To calibrate and assess the risk/return profile of the portfolio, we present an analytical framework offering pragmatic solutions for long-term investors seeking exposure to volatility. The benefit of volatility exposure for a co...

Economic policy optimization based on both one stochastic model and the parametric control theory

Science.gov (United States)

Ashimov, Abdykappar; Borovskiy, Yuriy; Onalbekov, Mukhit

2016-06-01

A nonlinear dynamic stochastic general equilibrium model with financial frictions is developed to describe two interacting national economies in the environment of the rest of the world. Parameters of nonlinear model are estimated based on its log-linearization by the Bayesian approach. The nonlinear model is verified by retroprognosis, estimation of stability indicators of mappings specified by the model, and estimation the degree of coincidence for results of internal and external shocks' effects on macroeconomic indicators on the basis of the estimated nonlinear model and its log-linearization. On the base of the nonlinear model, the parametric control problems of economic growth and volatility of macroeconomic indicators of Kazakhstan are formulated and solved for two exchange rate regimes (free floating and managed floating exchange rates)

An introduction to probability and stochastic processes

CERN Document Server

Melsa, James L

2013-01-01

Geared toward college seniors and first-year graduate students, this text is designed for a one-semester course in probability and stochastic processes. Topics covered in detail include probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.

Research on nonlinear stochastic dynamical price model

International Nuclear Information System (INIS)

Li Jiaorui; Xu Wei; Xie Wenxian; Ren Zhengzheng

2008-01-01

In consideration of many uncertain factors existing in economic system, nonlinear stochastic dynamical price model which is subjected to Gaussian white noise excitation is proposed based on deterministic model. One-dimensional averaged Ito stochastic differential equation for the model is derived by using the stochastic averaging method, and applied to investigate the stability of the trivial solution and the first-passage failure of the stochastic price model. The stochastic price model and the methods presented in this paper are verified by numerical studies

Origin of Volatiles in Earth: Indigenous Versus Exogenous Sources Based on Highly Siderophile, Volatile Siderophile, and Light Volatile Elements

Science.gov (United States)

Righter, K.; Danielson, L.; Pando, K. M.; Marin, N.; Nickodem, K.

2015-01-01

Origin of Earth's volatiles has traditionally been ascribed to late accretion of material after major differentiation events - chondrites, comets, ice or other exogenous sources. A competing theory is that the Earth accreted its volatiles as it was built, thus water and other building blocks were present early and during differentiation and core formation (indigenous). Here we discuss geochemical evidence from three groups of elements that suggests Earth's volatiles were acquired during accretion and did not require additional sources after differentiation.

Role of management strategies and environmental factors in determining the emissions of biogenic volatile organic compounds from urban greenspaces.

Science.gov (United States)

Ren, Yuan; Ge, Ying; Gu, Baojing; Min, Yong; Tani, Akira; Chang, Jie

2014-06-03

Biogenic volatile organic compound (BVOC) emissions from urban greenspace have recently become a global concern. To identify key factors affecting the dynamics of urban BVOC emissions, we built an estimation model and utilized the city of Hangzhou in southeastern China as an example. A series of single-factor scenarios were first developed, and then nine multifactor scenarios using a combination of different single-factor scenarios were built to quantify the effects of environmental changes and urban management strategies on urban BVOC emissions. Results of our model simulations showed that (1) annual total BVOC emissions from the metropolitan area of Hangzhou were 4.7×10(8) g of C in 2010 and were predicted to be 1.2-3.2 Gg of C (1 Gg=10(9) g) in our various scenarios in 2050, (2) urban management played a more important role in determining future urban BVOC emissions than environmental changes, and (3) a high ecosystem service value (e.g., lowest BVOC/leaf mass ratio) could be achieved through positive coping in confronting environmental changes and adopting proactive urban management strategies on a local scale, that is, to moderately increase tree density while restricting excessive greenspace expansion and optimizing the species composition of existing and newly planted trees.

Stochastic Systems Uncertainty Quantification and Propagation

CERN Document Server

Grigoriu, Mircea

2012-01-01

Uncertainty is an inherent feature of both properties of physical systems and the inputs to these systems that needs to be quantified for cost effective and reliable designs. The states of these systems satisfy equations with random entries, referred to as stochastic equations, so that they are random functions of time and/or space. The solution of stochastic equations poses notable technical difficulties that are frequently circumvented by heuristic assumptions at the expense of accuracy and rigor. The main objective of Stochastic Systems is to promoting the development of accurate and efficient methods for solving stochastic equations and to foster interactions between engineers, scientists, and mathematicians. To achieve these objectives Stochastic Systems presents: ·         A clear and brief review of essential concepts on probability theory, random functions, stochastic calculus, Monte Carlo simulation, and functional analysis   ·          Probabilistic models for random variables an...

Stochastic-field cavitation model

International Nuclear Information System (INIS)

Dumond, J.; Magagnato, F.; Class, A.

2013-01-01

Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian “particles” or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations

Stochastic-field cavitation model

Science.gov (United States)

Dumond, J.; Magagnato, F.; Class, A.

2013-07-01

Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian "particles" or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations.

Stochastic modeling of the energy supply system with uncertain fuel price – A case of emerging technologies for distributed power generation

International Nuclear Information System (INIS)

Mirkhani, Sh.; Saboohi, Y.

2012-01-01

Highlights: ► An existing bottom-up deterministic energy system model (ESM) has limited capability in handling the uncertainties. ► Uncertainty has been modeled based on GBM. Probabilistic scenarios are generated based on Cox–Ross method. ► A multistage stochastic model has been developed where scenarios are integrated in the energy system model. ► A distributed generation system has been introduced as a case study where fuel price is considered as an uncertain parameter. - Abstract: A deterministic energy supply model with bottom-up structure has limited capability in handling the uncertainties. To enhance the applicability of such a model in an uncertain environment two main issues have been investigated in the present paper. First, a binomial lattice is generated based on the stochastic nature of the source of uncertainty. Second, an energy system model (ESM) has been reformulated as a multistage stochastic problem. The result of the application of the modified energy model encompasses all uncertain outcomes together and enables optimal timing of capacity expansion. The performance of the model has been demonstrated with the help of a case study. The case study has been formulated on the assumption that a gas fired engine competes with renewable energy technologies in an uncertain environment where the price of natural gas is volatile. The result of stochastic model has then been compared with those of a deterministic model by studying the expected value of perfect information (EVPI) and the value of stochastic solution (VSS). Finally the results of the sensitivity analysis have been discussed where the characteristics of uncertainty of the price of fuel are varied.

Volatility transmission and volatility impulse response functions in European electricity forward markets

International Nuclear Information System (INIS)

Le Pen, Yannick; Sevi, Benoit

2008-01-01

Using daily data from March 2001 to June 2005, we estimate a VAR-BEKK model and find evidence of return and volatility spillovers between the German, the Dutch and the British forward electricity markets. We apply Hafner and Herwartz [2006, Journal of International Money and Finance 25, 719-740] Volatility Impulse Response Function(VIRF) to quantify the impact of shock on expected conditional volatility. We observe that a shock has a high positive impact only if its size is large compared to the current level of volatility. The impact of shocks are usually not persistent, which may be an indication of market efficiency. Finally, we estimate the density of the VIRF at different forecast horizon. These fitted distributions are asymmetric and show that extreme events are possible even if their probability is low. These results have interesting implications for market participants whose risk management policy is based on option prices which themselves depend on the volatility level. (authors)

The volatility of HOL

International Nuclear Information System (INIS)

Wren, D.J.; Sanipelli, G.

1985-01-01

The volatility of HOI has been measured using a mass spectrometer to analyze the gas phase above an aqueous solution. The HOI in solution was generated continuously in a flow reactor that combined I/sup -/ and OCl/sup -/ solutions. The analysis has resulted in a lower limit of 6X10/sup 3/ mol . dm/sup -3/ . atm/sup -1/ for the equilibrium constant for the reaction HOI(g)/equilibrium/HOI(aq). This value is a factor 30 greater than the best previous estimate. This new limit for HOI volatility results in higher total iodine partition coefficients, particularly for solutions with pH>8. The upper limit for the equilibrium constant is consistent with essentially zero volatility for HOI. The effect of HOI volatility on total iodine volatility is briefly discussed as a function of solution chemistry and kinetics

Stochastic Pi-calculus Revisited

DEFF Research Database (Denmark)

Cardelli, Luca; Mardare, Radu Iulian

2013-01-01

We develop a version of stochastic Pi-calculus with a semantics based on measure theory. We dene the behaviour of a process in a rate environment using measures over the measurable space of processes induced by structural congruence. We extend the stochastic bisimulation to include the concept of...

Volatility behavior of visibility graph EMD financial time series from Ising interacting system

Science.gov (United States)

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.

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.

Electricity price forecast using Combinatorial Neural Network trained by a new stochastic search method

International Nuclear Information System (INIS)

Abedinia, O.; Amjady, N.; Shafie-khah, M.; Catalão, J.P.S.

2015-01-01

Highlights: • Presenting a Combinatorial Neural Network. • Suggesting a new stochastic search method. • Adapting the suggested method as a training mechanism. • Proposing a new forecast strategy. • Testing the proposed strategy on real-world electricity markets. - Abstract: Electricity price forecast is key information for successful operation of electricity market participants. However, the time series of electricity price has nonlinear, non-stationary and volatile behaviour and so its forecast method should have high learning capability to extract the complex input/output mapping function of electricity price. In this paper, a Combinatorial Neural Network (CNN) based forecasting engine is proposed to predict the future values of price data. The CNN-based forecasting engine is equipped with a new training mechanism for optimizing the weights of the CNN. This training mechanism is based on an efficient stochastic search method, which is a modified version of chemical reaction optimization algorithm, giving high learning ability to the CNN. The proposed price forecast strategy is tested on the real-world electricity markets of Pennsylvania–New Jersey–Maryland (PJM) and mainland Spain and its obtained results are extensively compared with the results obtained from several other forecast methods. These comparisons illustrate effectiveness of the proposed strategy.

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

Quantum stochastic calculus associated with quadratic quantum noises

International Nuclear Information System (INIS)

Ji, Un Cig; Sinha, Kalyan B.

2016-01-01

We first study a class of fundamental quantum stochastic processes induced by the generators of a six dimensional non-solvable Lie †-algebra consisting of all linear combinations of the generalized Gross Laplacian and its adjoint, annihilation operator, creation operator, conservation, and time, and then we study the quantum stochastic integrals associated with the class of fundamental quantum stochastic processes, and the quantum Itô formula is revisited. The existence and uniqueness of solution of a quantum stochastic differential equation is proved. The unitarity conditions of solutions of quantum stochastic differential equations associated with the fundamental processes are examined. The quantum stochastic calculus extends the Hudson-Parthasarathy quantum stochastic calculus

Quantum stochastic calculus associated with quadratic quantum noises

Energy Technology Data Exchange (ETDEWEB)

Ji, Un Cig, E-mail: uncigji@chungbuk.ac.kr [Department of Mathematics, Research Institute of Mathematical Finance, Chungbuk National University, Cheongju, Chungbuk 28644 (Korea, Republic of); Sinha, Kalyan B., E-mail: kbs-jaya@yahoo.co.in [Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur, Bangalore-64, India and Department of Mathematics, Indian Institute of Science, Bangalore-12 (India)

2016-02-15

We first study a class of fundamental quantum stochastic processes induced by the generators of a six dimensional non-solvable Lie †-algebra consisting of all linear combinations of the generalized Gross Laplacian and its adjoint, annihilation operator, creation operator, conservation, and time, and then we study the quantum stochastic integrals associated with the class of fundamental quantum stochastic processes, and the quantum Itô formula is revisited. The existence and uniqueness of solution of a quantum stochastic differential equation is proved. The unitarity conditions of solutions of quantum stochastic differential equations associated with the fundamental processes are examined. The quantum stochastic calculus extends the Hudson-Parthasarathy quantum stochastic calculus.

Set-Valued Stochastic Lebesque Integral and Representation Theorems

Directory of Open Access Journals (Sweden)

Jungang Li

2008-06-01

Full Text Available In this paper, we shall firstly illustrate why we should introduce set-valued stochastic integrals, and then we shall discuss some properties of set-valued stochastic processes and the relation between a set-valued stochastic process and its selection set. After recalling the Aumann type definition of stochastic integral, we shall introduce a new definition of Lebesgue integral of a set-valued stochastic process with respect to the time t . Finally we shall prove the presentation theorem of set-valued stochastic integral and dis- cuss further properties that will be useful to study set-valued stochastic differential equations with their applications.

Instantaneous stochastic perturbation theory

International Nuclear Information System (INIS)

Lüscher, Martin

2015-01-01

A form of stochastic perturbation theory is described, where the representative stochastic fields are generated instantaneously rather than through a Markov process. The correctness of the procedure is established to all orders of the expansion and for a wide class of field theories that includes all common formulations of lattice QCD.

Cost Linkages Transmit Volatility Across Markets

DEFF Research Database (Denmark)

Nguyen, Daniel Xuyen; Schaur, Georg

We present and test a model relating a firm's idiosyncratic cost, its exporting status, and the volatilities of its domestic and export sales. In prior models of trade, supply costs for domestic and exports were linear and thus additively separable. We introduce a nonlinear cost function in order...... to link the domestic and export supply costs. This theoretical contribution has two new implications for the exporting firm. First, the demand volatility in the foreign market now directly affects the firm's domestic sales volatility. Second, firms hedge domestic demand volatility with exports. The model...... has several testable predictions. First, larger firms have lower total and domestic sales volatilities. Second, foreign market volatility increases domestic sales volatilities for exporters. Third, exporters allocate output across both markets in order to reduce total sales volatility. We find...

Time-Varying Periodicity in Intraday Volatility

DEFF Research Database (Denmark)

Andersen, Torben Gustav; Thyrsgaard, Martin; Todorov, Viktor

We develop a nonparametric test for deciding whether return volatility exhibits time-varying intraday periodicity using a long time-series of high-frequency data. Our null hypothesis, commonly adopted in work on volatility modeling, is that volatility follows a stationary process combined...... with a constant time-of-day periodic component. We first construct time-of-day volatility estimates and studentize the high-frequency returns with these periodic components. If the intraday volatility periodicity is invariant over time, then the distribution of the studentized returns should be identical across...... with estimating volatility moments through their sample counterparts. Critical values are computed via easy-to-implement simulation. In an empirical application to S&P 500 index returns, we find strong evidence for variation in the intraday volatility pattern driven in part by the current level of volatility...

A retrodictive stochastic simulation algorithm

International Nuclear Information System (INIS)

Vaughan, T.G.; Drummond, P.D.; Drummond, A.J.

2010-01-01

In this paper we describe a simple method for inferring the initial states of systems evolving stochastically according to master equations, given knowledge of the final states. This is achieved through the use of a retrodictive stochastic simulation algorithm which complements the usual predictive stochastic simulation approach. We demonstrate the utility of this new algorithm by applying it to example problems, including the derivation of likely ancestral states of a gene sequence given a Markovian model of genetic mutation.

Stochastic processes and quantum theory

International Nuclear Information System (INIS)

Klauder, J.R.

1975-01-01

The author analyses a variety of stochastic processes, namely real time diffusion phenomena, which are analogues of imaginary time quantum theory and convariant imaginary time quantum field theory. He elaborates some standard properties involving probability measures and stochastic variables and considers a simple class of examples. Finally he develops the fact that certain stochastic theories actually exhibit divergences that simulate those of covariant quantum field theory and presents examples of both renormaizable and unrenormalizable behavior. (V.J.C.)

Stochastic Still Water Response Model

DEFF Research Database (Denmark)

Friis-Hansen, Peter; Ditlevsen, Ove Dalager

2002-01-01

In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model is...... out that an important parameter of the stochastic cargo field model is the mean number of containers delivered by each customer.......In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model...... is to establish the stochastic load field conditional on a given draft and trim of the vessel. The model contributes to a realistic modelling of the stochastic load processes to be used in a reliability evaluation of the ship hull. Emphasis is given to container vessels. The formulation of the model for obtaining...

Stochastic quantization and topological theories

International Nuclear Information System (INIS)

Fainberg, V.Y.; Subbotin, A.V.; Kuznetsov, A.N.

1992-01-01

In the last two years topological quantum field theories (TQFT) have attached much attention. This paper reports that from the very beginning it was realized that due to a peculiar BRST-like symmetry these models admitted so-called Nicolai mapping: the Nicolai variables, in terms of which actions of the theories become gaussian, are nothing but (anti-) selfduality conditions or their generalizations. This fact became a starting point in the quest of possible stochastic interpretation to topological field theories. The reasons behind were quite simple and included, in particular, the well-known relations between stochastic processes and supersymmetry. The main goal would have been achieved, if it were possible to construct stochastic processes governed by Langevin or Fokker-Planck equations in a real Euclidean time leading to TQFT's path integrals (equivalently: to reformulate TQFTs as non-equilibrium phase dynamics of stochastic processes). Further on, if it would appear that these processes correspond to the stochastic quantization of theories of some definite kind, one could expect (d + 1)-dimensional TQFTs to share some common properties with d-dimensional ones

Stochastic quantization of Einstein gravity

International Nuclear Information System (INIS)

Rumpf, H.

1986-01-01

We determine a one-parameter family of covariant Langevin equations for the metric tensor of general relativity corresponding to DeWitt's one-parameter family of supermetrics. The stochastic source term in these equations can be expressed in terms of a Gaussian white noise upon the introduction of a stochastic tetrad field. The only physically acceptable resolution of a mathematical ambiguity in the ansatz for the source term is the adoption of Ito's calculus. By taking the formal equilibrium limit of the stochastic metric a one-parameter family of covariant path-integral measures for general relativity is obtained. There is a unique parameter value, distinguished by any one of the following three properties: (i) the metric is harmonic with respect to the supermetric, (ii) the path-integral measure is that of DeWitt, (iii) the supermetric governs the linearized Einstein dynamics. Moreover the Feynman propagator corresponding to this parameter is causal. Finally we show that a consistent stochastic perturbation theory gives rise to a new type of diagram containing ''stochastic vertices.''

Momentum Maps and Stochastic Clebsch Action Principles

Science.gov (United States)

Cruzeiro, Ana Bela; Holm, Darryl D.; Ratiu, Tudor S.

2018-01-01

We derive stochastic differential equations whose solutions follow the flow of a stochastic nonlinear Lie algebra operation on a configuration manifold. For this purpose, we develop a stochastic Clebsch action principle, in which the noise couples to the phase space variables through a momentum map. This special coupling simplifies the structure of the resulting stochastic Hamilton equations for the momentum map. In particular, these stochastic Hamilton equations collectivize for Hamiltonians that depend only on the momentum map variable. The Stratonovich equations are derived from the Clebsch variational principle and then converted into Itô form. In comparing the Stratonovich and Itô forms of the stochastic dynamical equations governing the components of the momentum map, we find that the Itô contraction term turns out to be a double Poisson bracket. Finally, we present the stochastic Hamiltonian formulation of the collectivized momentum map dynamics and derive the corresponding Kolmogorov forward and backward equations.

The determinants of exchange rates and the movements of EUR/RON exchange rate via non-linear stochastic processes

Directory of Open Access Journals (Sweden)

Petrică Andreea-Cristina

2017-07-01

Full Text Available Modeling exchange rate volatility became an important topic for research debate starting with 1973, when many countries switched to floating exchange rate system. In this paper, we focus on the EUR/RON exchange rate both as an economic measure and present the implied economic links, and also as a financial investment and analyze its movements and fluctuations through two volatility stochastic processes: the Standard Generalized Autoregressive Conditionally Heteroscedastic Model (GARCH and the Exponential Generalized Autoregressive Conditionally Heteroscedastic Model (EGARCH. The objective of the conditional variance processes is to capture dependency in the return series of the EUR/RON exchange rate. On this account, analyzing exchange rates could be seen as the input for economic decisions regarding Romanian macroeconomics - the exchange rates being influenced by many factors such as: interest rates, inflation, trading relationships with other countries (imports and exports, or investments - portfolio optimization, risk management, asset pricing. Therefore, we talk about political stability and economic performance of a country that represents a link between the two types of inputs mentioned above and influences both the macroeconomics and the investments. Based on time-varying volatility, we examine implied volatility of daily returns of EUR/RON exchange rate using the standard GARCH model and the asymmetric EGARCH model, whose parameters are estimated through the maximum likelihood method and the error terms follow two distributions (Normal and Student’s t. The empirical results show EGARCH(2,1 with Asymmetric order 2 and Student’s t error terms distribution performs better than all the estimated standard GARCH models (GARCH(1,1, GARCH(1,2, GARCH(2,1 and GARCH(2,2. This conclusion is supported by the major advantage of the EGARCH model compared to the GARCH model which consists in allowing good and bad news having different impact on the

Stochastic biomathematical models with applications to neuronal modeling

CERN Document Server

Batzel, Jerry; Ditlevsen, Susanne

2013-01-01

Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and its application in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.

Forecasting volatility of crude oil markets

International Nuclear Information System (INIS)

Kang, Sang Hoon; Kang, Sang-Mok; Yoon, Seong-Min

2009-01-01

This article investigates the efficacy of a volatility model for three crude oil markets - Brent, Dubai, and West Texas Intermediate (WTI) - with regard to its ability to forecast and identify volatility stylized facts, in particular volatility persistence or long memory. In this context, we assess persistence in the volatility of the three crude oil prices using conditional volatility models. The CGARCH and FIGARCH models are better equipped to capture persistence than are the GARCH and IGARCH models. The CGARCH and FIGARCH models also provide superior performance in out-of-sample volatility forecasts. We conclude that the CGARCH and FIGARCH models are useful for modeling and forecasting persistence in the volatility of crude oil prices. (author)

Forecasting volatility of crude oil markets

Energy Technology Data Exchange (ETDEWEB)

Kang, Sang Hoon [Department of Business Administration, Gyeongsang National University, Jinju, 660-701 (Korea); Kang, Sang-Mok; Yoon, Seong-Min [Department of Economics, Pusan National University, Busan, 609-735 (Korea)

2009-01-15

This article investigates the efficacy of a volatility model for three crude oil markets - Brent, Dubai, and West Texas Intermediate (WTI) - with regard to its ability to forecast and identify volatility stylized facts, in particular volatility persistence or long memory. In this context, we assess persistence in the volatility of the three crude oil prices using conditional volatility models. The CGARCH and FIGARCH models are better equipped to capture persistence than are the GARCH and IGARCH models. The CGARCH and FIGARCH models also provide superior performance in out-of-sample volatility forecasts. We conclude that the CGARCH and FIGARCH models are useful for modeling and forecasting persistence in the volatility of crude oil prices. (author)

Dynamically Hedging Oil and Currency Futures Using Receding Horizontal Control and Stochastic Programming

Science.gov (United States)

Cottrell, Paul Edward

There is a lack of research in the area of hedging future contracts, especially in illiquid or very volatile market conditions. It is important to understand the volatility of the oil and currency markets because reduced fluctuations in these markets could lead to better hedging performance. This study compared different hedging methods by using a hedging error metric, supplementing the Receding Horizontal Control and Stochastic Programming (RHCSP) method by utilizing the London Interbank Offered Rate with the Levy process. The RHCSP hedging method was investigated to determine if improved hedging error was accomplished compared to the Black-Scholes, Leland, and Whalley and Wilmott methods when applied on simulated, oil, and currency futures markets. A modified RHCSP method was also investigated to determine if this method could significantly reduce hedging error under extreme market illiquidity conditions when applied on simulated, oil, and currency futures markets. This quantitative study used chaos theory and emergence for its theoretical foundation. An experimental research method was utilized for this study with a sample size of 506 hedging errors pertaining to historical and simulation data. The historical data were from January 1, 2005 through December 31, 2012. The modified RHCSP method was found to significantly reduce hedging error for the oil and currency market futures by the use of a 2-way ANOVA with a t test and post hoc Tukey test. This study promotes positive social change by identifying better risk controls for investment portfolios and illustrating how to benefit from high volatility in markets. Economists, professional investment managers, and independent investors could benefit from the findings of this study.

Introduction to stochastic dynamic programming

CERN Document Server

Ross, Sheldon M; Lukacs, E

1983-01-01

Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist-providing counterexamples where appropriate-and the

Stochastic Finite Elements in Reliability-Based Structural Optimization

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Engelund, S.

Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect to optimi......Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect...

BRST stochastic quantization

International Nuclear Information System (INIS)

Hueffel, H.

1990-01-01

After a brief review of the BRST formalism and of the Parisi-Wu stochastic quantization method we introduce the BRST stochastic quantization scheme. It allows the second quantization of constrained Hamiltonian systems in a manifestly gauge symmetry preserving way. The examples of the relativistic particle, the spinning particle and the bosonic string are worked out in detail. The paper is closed by a discussion on the interacting field theory associated to the relativistic point particle system. 58 refs. (Author)

Stochastic quantum gravity

International Nuclear Information System (INIS)

Rumpf, H.

1987-01-01

We begin with a naive application of the Parisi-Wu scheme to linearized gravity. This will lead into trouble as one peculiarity of the full theory, the indefiniteness of the Euclidean action, shows up already at this level. After discussing some proposals to overcome this problem, Minkowski space stochastic quantization will be introduced. This will still not result in an acceptable quantum theory of linearized gravity, as the Feynman propagator turns out to be non-causal. This defect will be remedied only after a careful analysis of general covariance in stochastic quantization has been performed. The analysis requires the notion of a metric on the manifold of metrics, and a natural candidate for this is singled out. With this a consistent stochastic quantization of Einstein gravity becomes possible. It is even possible, at least perturbatively, to return to the Euclidean regime. 25 refs. (Author)

Stochastic models, estimation, and control

CERN Document Server

Maybeck, Peter S

1982-01-01

This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.

Stochastic theories of quantum mechanics

International Nuclear Information System (INIS)

De la Pena, L.; Cetto, A.M.

1991-01-01

The material of this article is organized into five sections. In Sect. I the basic characteristics of quantum systems are briefly discussed, with emphasis on their stochastic properties. In Sect. II a version of stochastic quantum mechanics is presented, to conclude that the quantum formalism admits an interpretation in terms of stochastic processes. In Sect. III the elements of stochastic electrodynamics are described, and its possibilities and limitations as a fundamental theory of quantum systems are discussed. Section IV contains a recent reformulation that overcomes the limitations of the theory discussed in the foregoing section. Finally, in Sect. V the theorems of EPR, Von Neumann and Bell are discussed briefly. The material is pedagogically presented and includes an ample list of references, but the details of the derivations are generally omitted. (Author)

A heterogeneous stochastic FEM framework for elliptic PDEs

International Nuclear Information System (INIS)

Hou, Thomas Y.; Liu, Pengfei

2015-01-01

We introduce a new concept of sparsity for the stochastic elliptic operator −div(a(x,ω)∇(⋅)), which reflects the compactness of its inverse operator in the stochastic direction and allows for spatially heterogeneous stochastic structure. This new concept of sparsity motivates a heterogeneous stochastic finite element method (HSFEM) framework for linear elliptic equations, which discretizes the equations using the heterogeneous coupling of spatial basis with local stochastic basis to exploit the local stochastic structure of the solution space. We also provide a sampling method to construct the local stochastic basis for this framework using the randomized range finding techniques. The resulting HSFEM involves two stages and suits the multi-query setting: in the offline stage, the local stochastic structure of the solution space is identified; in the online stage, the equation can be efficiently solved for multiple forcing functions. An online error estimation and correction procedure through Monte Carlo sampling is given. Numerical results for several problems with high dimensional stochastic input are presented to demonstrate the efficiency of the HSFEM in the online stage

Separable quadratic stochastic operators

International Nuclear Information System (INIS)

Rozikov, U.A.; Nazir, S.

2009-04-01

We consider quadratic stochastic operators, which are separable as a product of two linear operators. Depending on properties of these linear operators we classify the set of the separable quadratic stochastic operators: first class of constant operators, second class of linear and third class of nonlinear (separable) quadratic stochastic operators. Since the properties of operators from the first and second classes are well known, we mainly study the properties of the operators of the third class. We describe some Lyapunov functions of the operators and apply them to study ω-limit sets of the trajectories generated by the operators. We also compare our results with known results of the theory of quadratic operators and give some open problems. (author)

Trajectory averaging for stochastic approximation MCMC algorithms

KAUST Repository

Liang, Faming

2010-01-01

to the stochastic approximation Monte Carlo algorithm [Liang, Liu and Carroll J. Amer. Statist. Assoc. 102 (2007) 305-320]. The application of the trajectory averaging estimator to other stochastic approximationMCMC algorithms, for example, a stochastic

Dynamical and hamiltonian dilations of stochastic processes

International Nuclear Information System (INIS)

Baumgartner, B.; Gruemm, H.-R.

1982-01-01

This is a study of the problem, which stochastic processes could arise from dynamical systems by loss of information. The notions of ''dilation'' and ''approximate dilation'' of a stochastic process are introduced to give exact definitions of this particular relationship. It is shown that every generalized stochastic process is approximately dilatable by a sequence of dynamical systems, but for stochastic processes in full generality one needs nets. (Author)

Transport in Stochastic Media

International Nuclear Information System (INIS)

Haran, O.; Shvarts, D.; Thieberger, R.

1998-01-01

Classical transport of neutral particles in a binary, scattering, stochastic media is discussed. It is assumed that the cross-sections of the constituent materials and their volume fractions are known. The inner structure of the media is stochastic, but there exist a statistical knowledge about the lump sizes, shapes and arrangement. The transmission through the composite media depends on the specific heterogeneous realization of the media. The current research focuses on the averaged transmission through an ensemble of realizations, frm which an effective cross-section for the media can be derived. The problem of one dimensional transport in stochastic media has been studied extensively [1]. In the one dimensional description of the problem, particles are transported along a line populated with alternating material segments of random lengths. The current work discusses transport in two-dimensional stochastic media. The phenomenon that is unique to the multi-dimensional description of the problem is obstacle bypassing. Obstacle bypassing tends to reduce the opacity of the media, thereby reducing its effective cross-section. The importance of this phenomenon depends on the manner in which the obstacles are arranged in the media. Results of transport simulations in multi-dimensional stochastic media are presented. Effective cross-sections derived from the simulations are compared against those obtained for the one-dimensional problem, and against those obtained from effective multi-dimensional models, which are partially based on a Markovian assumption

Stochastic Stability of Endogenous Growth: Theory and Applications

OpenAIRE

Boucekkine, Raouf; Pintus, Patrick; Zou, Benteng

2015-01-01

We examine the issue of stability of stochastic endogenous growth. First, stochastic stability concepts are introduced and applied to stochastic linear homogenous differen- tial equations to which several stochastic endogenous growth models reduce. Second, we apply the mathematical theory to two models, starting with the stochastic AK model. It’s shown that in this case exponential balanced paths, which characterize optimal trajectories in the absence of uncertainty, are not robust to uncerta...

Stochastic models: theory and simulation.

Energy Technology Data Exchange (ETDEWEB)

Field, Richard V., Jr.

2008-03-01

Many problems in applied science and engineering involve physical phenomena that behave randomly in time and/or space. Examples are diverse and include turbulent flow over an aircraft wing, Earth climatology, material microstructure, and the financial markets. Mathematical models for these random phenomena are referred to as stochastic processes and/or random fields, and Monte Carlo simulation is the only general-purpose tool for solving problems of this type. The use of Monte Carlo simulation requires methods and algorithms to generate samples of the appropriate stochastic model; these samples then become inputs and/or boundary conditions to established deterministic simulation codes. While numerous algorithms and tools currently exist to generate samples of simple random variables and vectors, no cohesive simulation tool yet exists for generating samples of stochastic processes and/or random fields. There are two objectives of this report. First, we provide some theoretical background on stochastic processes and random fields that can be used to model phenomena that are random in space and/or time. Second, we provide simple algorithms that can be used to generate independent samples of general stochastic models. The theory and simulation of random variables and vectors is also reviewed for completeness.

The Multifactor Measure of Performance: Its Development, Norming, and Validation.

Science.gov (United States)

Bar-On, Reuven

2018-01-01

This article describes the development as well as the initial norming and validation of the Multifactor Measure of Performance™ (MMP™), which is a psychometric instrument that is designed to study, assess and enhance key predictors of human performance to help individuals perform at a higher level. It was created by the author, for the purpose of going beyond existing conceptual and psychometric models that often focus on relatively few factors that are purported to assess performance at school, in the workplace and elsewhere. The relative sparsity of multifactorial pre-employment assessment instruments exemplifies, for the author, one of the important reasons for developing the MMP™, which attempts to comprehensively evaluate a wider array of factors that are thought to contribute to performance. In that this situation creates a need in the area of test-construction that should be addressed, the author sought to develop a multifactorial assessment and development instrument that could concomitantly evaluate a combination of physical, cognitive, intra-personal, inter-personal, and motivational factors that significantly contribute to performance. The specific aim of this article is to show why, how and if this could be done as well as to present and discuss the potential importance of the results obtained to date. The findings presented here will hopefully add to what is known about human performance and thus contribute to the professional literature, in addition to contribute to the continued development of the MMP™. The impetus for developing the MMP™ is first explained below, followed by a detailed description of the process involved and the findings obtained; and their potential application is then discussed as well as the possible limitations of the present research and the need for future studies to address them.

Stochastic diffusion models for substitutable technological innovations

NARCIS (Netherlands)

Wang, L.; Hu, B.; Yu, X.

2004-01-01

Based on the analysis of firms' stochastic adoption behaviour, this paper first points out the necessity to build more practical stochastic models. And then, stochastic evolutionary models are built for substitutable innovation diffusion system. Finally, through the computer simulation of the

Stochasticity in the Josephson map

International Nuclear Information System (INIS)

Nomura, Y.; Ichikawa, Y.H.; Filippov, A.T.

1996-04-01

The Josephson map describes nonlinear dynamics of systems characterized by standard map with the uniform external bias superposed. The intricate structures of the phase space portrait of the Josephson map are examined on the basis of the tangent map associated with the Josephson map. Numerical observation of the stochastic diffusion in the Josephson map is examined in comparison with the renormalized diffusion coefficient calculated by the method of characteristic function. The global stochasticity of the Josephson map occurs at the values of far smaller stochastic parameter than the case of the standard map. (author)

Stochastic Finite Elements in Reliability-Based Structural Optimization

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Engelund, S.

1995-01-01

Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect to optimi......Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect...... to optimization variables can be performed. A computer implementation is described and an illustrative example is given....

Impact of microorganism on polonium volatilization

International Nuclear Information System (INIS)

Momoshima, N.; Ishida, A.; Fukuda, A.; Yoshinaga, C.

2007-01-01

Volatilization of polonium by microorganisms, Chromobacterium violaceum, Escherichia coli and Bacillus subtilis was examined for pure cultures in LB medium at 30 deg C, showing relative Po emission intensity 100, 10 and 1, respectively. Chromobacterium violaceum pre-cultured in LB medium without Po and suspended in water with Po showed high Po volatilization in spite of poor nutriment condition. Antibiotics inhibit volatilization of Po and cultivation at low temperature greatly reduced volatilization. The results strongly support the biological effects on Po volatilization. (author)

Stochastic nonlinear time series forecasting using time-delay reservoir computers: performance and universality.

Science.gov (United States)

Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

2014-07-01

Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a time-delay differential equation and show their good performance in the forecasting of the conditional covariances associated to multivariate discrete-time nonlinear stochastic processes of VEC-GARCH type as well as in the prediction of factual daily market realized volatilities computed with intraday quotes, using as training input daily log-return series of moderate size. We tackle some problems associated to the lack of task-universality for individually operating reservoirs and propose a solution based on the use of parallel arrays of time-delay reservoirs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Environmental vs Demographic Stochasticity in Population Growth

OpenAIRE

Braumann, C. A.

2010-01-01

Compares the effect on population growth of envinonmental stochasticity (random environmental variations described by stochastic differential equations) with demographic stochasticity (random variations in births and deaths described by branching processes and birth-and-death processes), in the density-independent and the density-dependent cases.

Multi-factor analysis on events related to hematological toxicity in 153Sm-EDTMP palliative therapy for skeletal metastases

International Nuclear Information System (INIS)

Zhan Hongwei; Yu Xiaoling; Ye Xiaojuan; Bao Chengkan; Sun Da; He Gangqiang

2006-01-01

Objective: To investigate the clinical factors related to hematological toxicity induced by intravenous samarium-153 ethylenediaminetetramethylene phosphonic acid ( 153 Sm-EDTMP) treatment. Methods A total of 206 patients with bony metastases treated with 153 Sm-EDTMP were retrospectively analyzed. Logistic regression (SPSS 10.0 for Windows) and correlation analysis were used to evaluate the factors concerned. Results: Age of the patient, number of bone metastatic lesion, chemotherapy before 153 Sm-EDTMP therapy, concurrent radiotherapy and repeat-times of 153 Sm-EDTMP treatments were found the individual factors related to hematological toxicity. Chemotherapy before 153 Sm-EDTMP, concurrent radiotherapy, medication for normal blood counting and repeat-times of 153 Sm-EDTMP treatments were the hematological toxicity factors in multi-factor analysis. Conclusion: In 153 Sm-EDTMP therapy, several factors were found related to hematological toxicity suggesting more attention be paid to the change of blood cell counting after the palliative therapy. (authors)

Transport stochastic multi-dimensional media

International Nuclear Information System (INIS)

Haran, O.; Shvarts, D.

1996-01-01

Many physical phenomena evolve according to known deterministic rules, but in a stochastic media in which the composition changes in space and time. Examples to such phenomena are heat transfer in turbulent atmosphere with non uniform diffraction coefficients, neutron transfer in boiling coolant of a nuclear reactor and radiation transfer through concrete shields. The results of measurements conducted upon such a media are stochastic by nature, and depend on the specific realization of the media. In the last decade there has been a considerable efforts to describe linear particle transport in one dimensional stochastic media composed of several immiscible materials. However, transport in two or three dimensional stochastic media has been rarely addressed. The important effect in multi-dimensional transport that does not appear in one dimension is the ability to bypass obstacles. The current work is an attempt to quantify this effect. (authors)

Transport stochastic multi-dimensional media

Energy Technology Data Exchange (ETDEWEB)

Haran, O; Shvarts, D [Israel Atomic Energy Commission, Beersheba (Israel). Nuclear Research Center-Negev; Thiberger, R [Ben-Gurion Univ. of the Negev, Beersheba (Israel)

1996-12-01

Many physical phenomena evolve according to known deterministic rules, but in a stochastic media in which the composition changes in space and time. Examples to such phenomena are heat transfer in turbulent atmosphere with non uniform diffraction coefficients, neutron transfer in boiling coolant of a nuclear reactor and radiation transfer through concrete shields. The results of measurements conducted upon such a media are stochastic by nature, and depend on the specific realization of the media. In the last decade there has been a considerable efforts to describe linear particle transport in one dimensional stochastic media composed of several immiscible materials. However, transport in two or three dimensional stochastic media has been rarely addressed. The important effect in multi-dimensional transport that does not appear in one dimension is the ability to bypass obstacles. The current work is an attempt to quantify this effect. (authors).

Modelling and application of stochastic processes

CERN Document Server

1986-01-01

The subject of modelling and application of stochastic processes is too vast to be exhausted in a single volume. In this book, attention is focused on a small subset of this vast subject. The primary emphasis is on realization and approximation of stochastic systems. Recently there has been considerable interest in the stochastic realization problem, and hence, an attempt has been made here to collect in one place some of the more recent approaches and algorithms for solving the stochastic realiza­ tion problem. Various different approaches for realizing linear minimum-phase systems, linear nonminimum-phase systems, and bilinear systems are presented. These approaches range from time-domain methods to spectral-domain methods. An overview of the chapter contents briefly describes these approaches. Also, in most of these chapters special attention is given to the problem of developing numerically ef­ ficient algorithms for obtaining reduced-order (approximate) stochastic realizations. On the application side,...

Turbulent response in a stochastic regime

International Nuclear Information System (INIS)

Molvig, K.; Freidberg, J.P.; Potok, R.; Hirshman, S.P.; Whitson, J.C.; Tajima, T.

1981-06-01

The theory for the non-linear, turbulent response in a system with intrinsic stochasticity is considered. It is argued that perturbative Eulerian theories, such as the Direct Interaction Approximation (DIA), are inherently unsuited to describe such a system. The exponentiation property that characterizes stochasticity appears in the Lagrangian picture and cannot even be defined in the Eulerian representation. An approximation for stochastic systems - the Normal Stochastic Approximation - is developed and states that the perturbed orbit functions (Lagrangian fluctuations) behave as normally distributed random variables. This is independent of the Eulerian statistics and, in fact, we treat the Eulerian fluctuations as fixed. A simple model problem (appropriate for the electron response in the drift wave) is subjected to a series of computer experiments. To within numerical noise the results are in agreement with the Normal Stochastic Approximation. The predictions of the DIA for this mode show substantial qualitative and quantitative departures from the observations

Stochastic modeling and analysis of telecoms networks

CERN Document Server

Decreusefond, Laurent

2012-01-01

This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an

Trajectory averaging for stochastic approximation MCMC algorithms

KAUST Repository

Liang, Faming

2010-10-01

The subject of stochastic approximation was founded by Robbins and Monro [Ann. Math. Statist. 22 (1951) 400-407]. After five decades of continual development, it has developed into an important area in systems control and optimization, and it has also served as a prototype for the development of adaptive algorithms for on-line estimation and control of stochastic systems. Recently, it has been used in statistics with Markov chain Monte Carlo for solving maximum likelihood estimation problems and for general simulation and optimizations. In this paper, we first show that the trajectory averaging estimator is asymptotically efficient for the stochastic approximation MCMC (SAMCMC) algorithm under mild conditions, and then apply this result to the stochastic approximation Monte Carlo algorithm [Liang, Liu and Carroll J. Amer. Statist. Assoc. 102 (2007) 305-320]. The application of the trajectory averaging estimator to other stochastic approximationMCMC algorithms, for example, a stochastic approximation MLE algorithm for missing data problems, is also considered in the paper. © Institute of Mathematical Statistics, 2010.

Stochastic resonance during a polymer translocation process

International Nuclear Information System (INIS)

Mondal, Debasish; Muthukumar, M.

2016-01-01

We have studied the occurrence of stochastic resonance when a flexible polymer chain undergoes a single-file translocation through a nano-pore separating two spherical cavities, under a time-periodic external driving force. The translocation of the chain is controlled by a free energy barrier determined by chain length, pore length, pore-polymer interaction, and confinement inside the donor and receiver cavities. The external driving force is characterized by a frequency and amplitude. By combining the Fokker-Planck formalism for polymer translocation and a two-state model for stochastic resonance, we have derived analytical formulas for criteria for emergence of stochastic resonance during polymer translocation. We show that no stochastic resonance is possible if the free energy barrier for polymer translocation is purely entropic in nature. The polymer chain exhibits stochastic resonance only in the presence of an energy threshold in terms of polymer-pore interactions. Once stochastic resonance is feasible, the chain entropy controls the optimal synchronization conditions significantly.

Is human failure a stochastic process?

International Nuclear Information System (INIS)

Dougherty, Ed M.

1997-01-01

Human performance results in failure events that occur with a risk-significant frequency. System analysts have taken for granted the random (stochastic) nature of these events in engineering assessments such as risk assessment. However, cognitive scientists and error technologists, at least those who have interest in human reliability, have, over the recent years, claimed that human error does not need this stochastic framework. Yet they still use the language appropriate to stochastic processes. This paper examines the potential for the stochastic nature of human failure production as the basis for human reliability analysis. It distinguishes and leaves to others, however, the epistemic uncertainties over the possible probability models for the real variability of human performance

Stochastic Switching Dynamics

DEFF Research Database (Denmark)

Simonsen, Maria

This thesis treats stochastic systems with switching dynamics. Models with these characteristics are studied from several perspectives. Initially in a simple framework given in the form of stochastic differential equations and, later, in an extended form which fits into the framework of sliding...... mode control. It is investigated how to understand and interpret solutions to models of switched systems, which are exposed to discontinuous dynamics and uncertainties (primarily) in the form of white noise. The goal is to gain knowledge about the performance of the system by interpreting the solution...

Stochastic singular optics

CSIR Research Space (South Africa)

Roux, FS

2013-09-01

Full Text Available Roux Presented at the International Conference on Correlation Optics 2013 Chernivtsi, Ukraine 18-20 September 2013 CSIR National Laser Centre, Pretoria, South Africa – p. 1/24 Contents ⊲ Defining Stochastic Singular Optics (SSO) ⊲ Tools of Stochastic... of vortices: topological charge ±1 (higher order are unstable). Positive and negative vortex densities np(x, y, z) and nn(x, y, z) ⊲ Vortex density: V = np + nn ⊲ Topological charge density: T = np − nn – p. 4/24 Subfields of SSO ⊲ Homogeneous, normally...

Dynamics of non-holonomic systems with stochastic transport

Science.gov (United States)

Holm, D. D.; Putkaradze, V.

2018-01-01

This paper formulates a variational approach for treating observational uncertainty and/or computational model errors as stochastic transport in dynamical systems governed by action principles under non-holonomic constraints. For this purpose, we derive, analyse and numerically study the example of an unbalanced spherical ball rolling under gravity along a stochastic path. Our approach uses the Hamilton-Pontryagin variational principle, constrained by a stochastic rolling condition, which we show is equivalent to the corresponding stochastic Lagrange-d'Alembert principle. In the example of the rolling ball, the stochasticity represents uncertainty in the observation and/or error in the computational simulation of the angular velocity of rolling. The influence of the stochasticity on the deterministically conserved quantities is investigated both analytically and numerically. Our approach applies to a wide variety of stochastic, non-holonomically constrained systems, because it preserves the mathematical properties inherited from the variational principle.

The price of fixed income market volatility

CERN Document Server

Mele, Antonio

2015-01-01

Fixed income volatility and equity volatility evolve heterogeneously over time, co-moving disproportionately during periods of global imbalances and each reacting to events of different nature. While the methodology for options-based "model-free" pricing of equity volatility has been known for some time, little is known about analogous methodologies for pricing various fixed income volatilities. This book fills this gap and provides a unified evaluation framework of fixed income volatility while dealing with disparate markets such as interest-rate swaps, government bonds, time-deposits and credit. It develops model-free, forward looking indexes of fixed-income volatility that match different quoting conventions across various markets, and uncovers subtle yet important pitfalls arising from naïve superimpositions of the standard equity volatility methodology when pricing various fixed income volatilities. The ultimate goal of the authors´ efforts is to make interest rate volatility standardization a valuable...

Stochastic cooling at Fermilab

International Nuclear Information System (INIS)

Marriner, J.

1986-08-01

The topics discussed are the stochastic cooling systems in use at Fermilab and some of the techniques that have been employed to meet the particular requirements of the anti-proton source. Stochastic cooling at Fermilab became of paramount importance about 5 years ago when the anti-proton source group at Fermilab abandoned the electron cooling ring in favor of a high flux anti-proton source which relied solely on stochastic cooling to achieve the phase space densities necessary for colliding proton and anti-proton beams. The Fermilab systems have constituted a substantial advance in the techniques of cooling including: large pickup arrays operating at microwave frequencies, extensive use of cryogenic techniques to reduce thermal noise, super-conducting notch filters, and the development of tools for controlling and for accurately phasing the system

Stochastic inflation in phase space: is slow roll a stochastic attractor?

Energy Technology Data Exchange (ETDEWEB)

Grain, Julien [Institut d' Astrophysique Spatiale, UMR8617, CNRS, Univ. Paris Sud, Université Paris-Saclay, Bt. 121, Orsay, F-91405 (France); Vennin, Vincent, E-mail: julien.grain@ias.u-psud.fr, E-mail: vincent.vennin@port.ac.uk [Institute of Cosmology and Gravitation, University of Portsmouth, Dennis Sciama Building, Burnaby Road, Portsmouth, PO13FX (United Kingdom)

2017-05-01

An appealing feature of inflationary cosmology is the presence of a phase-space attractor, ''slow roll'', which washes out the dependence on initial field velocities. We investigate the robustness of this property under backreaction from quantum fluctuations using the stochastic inflation formalism in the phase-space approach. A Hamiltonian formulation of stochastic inflation is presented, where it is shown that the coarse-graining procedure—where wavelengths smaller than the Hubble radius are integrated out—preserves the canonical structure of free fields. This means that different sets of canonical variables give rise to the same probability distribution which clarifies the literature with respect to this issue. The role played by the quantum-to-classical transition is also analysed and is shown to constrain the coarse-graining scale. In the case of free fields, we find that quantum diffusion is aligned in phase space with the slow-roll direction. This implies that the classical slow-roll attractor is immune to stochastic effects and thus generalises to a stochastic attractor regardless of initial conditions, with a relaxation time at least as short as in the classical system. For non-test fields or for test fields with non-linear self interactions however, quantum diffusion and the classical slow-roll flow are misaligned. We derive a condition on the coarse-graining scale so that observational corrections from this misalignment are negligible at leading order in slow roll.

Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

KAUST Repository

Richtarik, Peter; Taká č, Martin

2017-01-01

We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

KAUST Repository

Richtarik, Peter

2017-06-04

We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

Quantization of dynamical systems and stochastic control theory

International Nuclear Information System (INIS)

Guerra, F.; Morato, L.M.

1982-09-01

In the general framework of stochastic control theory we introduce a suitable form of stochastic action associated to the controlled process. Then a variational principle gives all main features of Nelson's stochastic mechanics. In particular we derive the expression of the current velocity field as the gradient of the phase action. Moreover the stochastic corrections to the Hamilton-Jacobi equation are in agreement with the quantum mechanical form of the Madelung fluid (equivalent to the Schroedinger equation). Therefore stochastic control theory can provide a very simple model simulating quantum mechanical behavior

Multifactor leadership styles and new exposure to workplace bullying: a six-month prospective study

Science.gov (United States)

TSUNO, Kanami; KAWAKAMI, Norito

2014-01-01

This study investigated the prospective association between supervisor leadership styles and workplace bullying. Altogether 404 civil servants from a local government in Japan completed baseline and follow-up surveys. The leadership variables and exposure to bullying were measured by Multifactor Leadership Questionnaire and Negative Acts Questionnaire-Revised, respectively. The prevalence of workplace bullying was 14.8% at baseline and 15.1% at follow-up. Among respondents who did not experience bullying at baseline (n=216), those who worked under the supervisors as higher in passive laissez-faire leadership had a 4.3 times higher risk of new exposure to bullying. On the other hand, respondents whose supervisors with highly considerate of the individual had a 70% lower risk of new exposure to bullying. In the entire sample (n=317), passive laissez-faire leadership was significantly and positively associated, while charisma/inspiration, individual consideration, and contingent reward were negatively associated both after adjusting for demographic and occupational characteristics at baseline, life events during follow-up, and exposure to workplace bullying at baseline. Results indicated that passive laissez-faire and low individual consideration leadership style at baseline were strong predictors of new exposure to bullying and high individual consideration leadership of supervisors/managers could be a preventive factor against bullying. PMID:25382384

Multifactor leadership styles and new exposure to workplace bullying: a six-month prospective study.

Science.gov (United States)

Tsuno, Kanami; Kawakami, Norito

2015-01-01

This study investigated the prospective association between supervisor leadership styles and workplace bullying. Altogether 404 civil servants from a local government in Japan completed baseline and follow-up surveys. The leadership variables and exposure to bullying were measured by Multifactor Leadership Questionnaire and Negative Acts Questionnaire-Revised, respectively. The prevalence of workplace bullying was 14.8% at baseline and 15.1% at follow-up. Among respondents who did not experience bullying at baseline (n=216), those who worked under the supervisors as higher in passive laissez-faire leadership had a 4.3 times higher risk of new exposure to bullying. On the other hand, respondents whose supervisors with highly considerate of the individual had a 70% lower risk of new exposure to bullying. In the entire sample (n=317), passive laissez-faire leadership was significantly and positively associated, while charisma/inspiration, individual consideration, and contingent reward were negatively associated both after adjusting for demographic and occupational characteristics at baseline, life events during follow-up, and exposure to workplace bullying at baseline. Results indicated that passive laissez-faire and low individual consideration leadership style at baseline were strong predictors of new exposure to bullying and high individual consideration leadership of supervisors/managers could be a preventive factor against bullying.

Volatile accretion history of the Earth.

Science.gov (United States)

Wood, B J; Halliday, A N; Rehkämper, M

2010-10-28

It has long been thought that the Earth had a protracted and complex history of volatile accretion and loss. Albarède paints a different picture, proposing that the Earth first formed as a dry planet which, like the Moon, was devoid of volatile constituents. He suggests that the Earth's complement of volatile elements was only established later, by the addition of a small veneer of volatile-rich material at ∼100 Myr (here and elsewhere, ages are relative to the origin of the Solar System). Here we argue that the Earth's mass balance of moderately volatile elements is inconsistent with Albarède's hypothesis but is well explained by the standard model of accretion from partially volatile-depleted material, accompanied by core formation.

On Lipschitzian quantum stochastic differential inclusions

International Nuclear Information System (INIS)

Ekhaguere, G.O.S.

1990-12-01

Quantum stochastic differential inclusions are introduced and studied within the framework of the Hudson-Parthasarathy formulation of quantum stochastic calculus. Results concerning the existence of solutions of a Lipschitzian quantum stochastic differential inclusion and the relationship between the solutions of such an inclusion and those of its convexification are presented. These generalize the Filippov existence theorem and the Filippov-Wazewski Relaxation Theorem for classical differential inclusions to the present noncommutative setting. (author). 9 refs

Stochastic temperature and the Nicolai map

International Nuclear Information System (INIS)

Hueffel, H.

1989-01-01

Just as standard temperature can be related to the time coordinate of Euclidean space, a new concept of 'stochastic temperature' may be introduced by associating it to the Parisi-Wu time of stochastic quantization. The perturbative equilibrium limit for a self-interacting scalar field is studied, and a 'thermal' mass shift to one loop is shown. In addition one may interpret the underlying stochastic process as a Nicolai map at nonzero 'temperature'. 22 refs. (Author)

Stochastic Linear Quadratic Optimal Control Problems

International Nuclear Information System (INIS)

Chen, S.; Yong, J.

2001-01-01

This paper is concerned with the stochastic linear quadratic optimal control problem (LQ problem, for short) for which the coefficients are allowed to be random and the cost functional is allowed to have a negative weight on the square of the control variable. Some intrinsic relations among the LQ problem, the stochastic maximum principle, and the (linear) forward-backward stochastic differential equations are established. Some results involving Riccati equation are discussed as well

Stochastic programming with integer recourse

NARCIS (Netherlands)

van der Vlerk, Maarten Hendrikus

1995-01-01

In this thesis we consider two-stage stochastic linear programming models with integer recourse. Such models are at the intersection of two different branches of mathematical programming. On the one hand some of the model parameters are random, which places the problem in the field of stochastic

Demonstration of Novel Sampling Techniques for Measurement of Turbine Engine Volatile and Non-Volatile Particulate Matter (PM) Emissions

Science.gov (United States)

2017-03-06

WP-201317) Demonstration of Novel Sampling Techniques for Measurement of Turbine Engine Volatile and Non-volatile Particulate Matter (PM... Engine Volatile and Non-Volatile Particulate Matter (PM) Emissions 6. AUTHOR(S) E. Corporan, M. DeWitt, C. Klingshirn, M.D. Cheng, R. Miake-Lye, J. Peck...the performance and viability of two devices to condition aircraft turbine engine exhaust to allow the accurate measurement of total (volatile and non

Stochastic quantization of gravity and string fields

International Nuclear Information System (INIS)

Rumpf, H.

1986-01-01

The stochastic quantization method of Parisi and Wu is generalized so as to make it applicable to Einstein's theory of gravitation. The generalization is based on the existence of a preferred metric in field configuration space, involves Ito's calculus, and introduces a complex stochastic process adapted to Lorentzian spacetime. It implies formally the path integral measure of DeWitt, a causual Feynman propagator, and a consistent stochastic perturbation theory. The lineraized version of the theory is also obtained from the stochastic quantization of the free string field theory of Siegel and Zwiebach. (Author)

Financial market volatility and contagion effect: A copula-multifractal volatility approach

Science.gov (United States)

Chen, Wang; Wei, Yu; Lang, Qiaoqi; Lin, Yu; Liu, Maojuan

2014-03-01

In this paper, we propose a new approach based on the multifractal volatility method (MFV) to study the contagion effect between the U.S. and Chinese stock markets. From recent studies, which reveal that multifractal characteristics exist in both developed and emerging financial markets, according to the econophysics literature we could draw conclusions as follows: Firstly, we estimate volatility using the multifractal volatility method, and find out that the MFV method performs best among other volatility models, such as GARCH-type and realized volatility models. Secondly, we analyze the tail dependence structure between the U.S. and Chinese stock market. The estimated static copula results for the entire period show that the SJC copula performs best, indicating asymmetric characteristics of the tail dependence structure. The estimated dynamic copula results show that the time-varying t copula achieves the best performance, which means the symmetry dynamic t copula is also a good choice, for it is easy to estimate and is able to depict both the upper and lower tail dependence structure. Finally, with the results of the previous two steps, we analyze the contagion effect between the U.S. and Chinese stock markets during the subprime mortgage crisis. The empirical results show that the subprime mortgage crisis started in the U.S. and that its stock market has had an obvious contagion effect on the Chinese stock market. Our empirical results should/might be useful for investors allocating their portfolios.

The Dynamic Programming Method of Stochastic Differential Game for Functional Forward-Backward Stochastic System

Directory of Open Access Journals (Sweden)

Shaolin Ji

2013-01-01

Full Text Available This paper is devoted to a stochastic differential game (SDG of decoupled functional forward-backward stochastic differential equation (FBSDE. For our SDG, the associated upper and lower value functions of the SDG are defined through the solution of controlled functional backward stochastic differential equations (BSDEs. Applying the Girsanov transformation method introduced by Buckdahn and Li (2008, the upper and the lower value functions are shown to be deterministic. We also generalize the Hamilton-Jacobi-Bellman-Isaacs (HJBI equations to the path-dependent ones. By establishing the dynamic programming principal (DPP, we derive that the upper and the lower value functions are the viscosity solutions of the corresponding upper and the lower path-dependent HJBI equations, respectively.

Thermal mixtures in stochastic mechanics

Energy Technology Data Exchange (ETDEWEB)

Guerra, F [Rome Univ. (Italy). Ist. di Matematica; Loffredo, M I [Salerno Univ. (Italy). Ist. di Fisica

1981-01-17

Stochastic mechanics is extended to systems in thermal equilibrium. The resulting stochastic processes are mixtures of Nelson processes. Their Markov property is investigated in some simple cases. It is found that in order to inforce Markov property the algebra of observable associated to the present must be suitably enlarged.

Parallel Prediction of Stock Volatility

Directory of Open Access Journals (Sweden)

Priscilla Jenq

2017-10-01

Full Text Available Volatility is a measurement of the risk of financial products. A stock will hit new highs and lows over time and if these highs and lows fluctuate wildly, then it is considered a high volatile stock. Such a stock is considered riskier than a stock whose volatility is low. Although highly volatile stocks are riskier, the returns that they generate for investors can be quite high. Of course, with a riskier stock also comes the chance of losing money and yielding negative returns. In this project, we will use historic stock data to help us forecast volatility. Since the financial industry usually uses S&P 500 as the indicator of the market, we will use S&P 500 as a benchmark to compute the risk. We will also use artificial neural networks as a tool to predict volatilities for a specific time frame that will be set when we configure this neural network. There have been reports that neural networks with different numbers of layers and different numbers of hidden nodes may generate varying results. In fact, we may be able to find the best configuration of a neural network to compute volatilities. We will implement this system using the parallel approach. The system can be used as a tool for investors to allocating and hedging assets.

The Robustness of Stochastic Switching Networks

OpenAIRE

Loh, Po-Ling; Zhou, Hongchao; Bruck, Jehoshua

2009-01-01

Many natural systems, including chemical and biological systems, can be modeled using stochastic switching circuits. These circuits consist of stochastic switches, called pswitches, which operate with a fixed probability of being open or closed. We study the effect caused by introducing an error of size ∈ to each pswitch in a stochastic circuit. We analyze two constructions – simple series-parallel and general series-parallel circuits – and prove that simple series-parallel circuits are robus...

Volatile communication in plant-aphid interactions.

Science.gov (United States)

de Vos, Martin; Jander, Georg

2010-08-01

Volatile communication plays an important role in mediating the interactions between plants, aphids, and other organisms in the environment. In response to aphid infestation, many plants initiate indirect defenses through the release of volatiles that attract ladybugs, parasitoid wasps, and other aphid-consuming predators. Aphid-induced volatile release in the model plant Arabidopsis thaliana requires the jasmonate signaling pathway. Volatile release is also induced by infection with aphid-transmitted viruses. Consistent with mathematical models of optimal transmission, viruses that are acquired rapidly by aphids induce volatile release to attract migratory aphids, but discourage long-term aphid feeding. Although the ecology of these interactions is well-studied, further research is needed to identify the molecular basis of aphid-induced and virus-induced changes in plant volatile release. Copyright 2010 Elsevier Ltd. All rights reserved.

The exploitation of volatile oil

Institute of Scientific and Technical Information of China (English)

MENG Teng; ZHANG Da; TENG Xiangjin; LINing; HAO Zaibin

2007-01-01

Rose is a kind of favorite ornamental plant. This article briefly introduced the cultivation and the use of rose around the world both in ancient time and nowadays. Today, volatile oil becomes the mainstream of the rose industry. People pay attention to the effect of volatile oil; meanwhile, they speed up their research on extracting volatile oil and the ingredients.

The intrinsic stochasticity of near-integrable Hamiltonian systems

Energy Technology Data Exchange (ETDEWEB)

Krlin, L [Ceskoslovenska Akademie Ved, Prague (Czechoslovakia). Ustav Fyziky Plazmatu

1989-09-01

Under certain conditions, the dynamics of near-integrable Hamiltonian systems appears to be stochastic. This stochasticity (intrinsic stochasticity, or deterministic chaos) is closely related to the Kolmogorov-Arnold-Moser (KAM) theorem of the stability of near-integrable multiperiodic Hamiltonian systems. The effect of the intrinsic stochasticity attracts still growing attention both in theory and in various applications in contemporary physics. The paper discusses the relation of the intrinsic stochasticity to the modern ergodic theory and to the KAM theorem, and describes some numerical experiments on related astrophysical and high-temperature plasma problems. Some open questions are mentioned in conclusion. (author).

Linear stochastic neutron transport theory

International Nuclear Information System (INIS)

Lewins, J.

1978-01-01

A new and direct derivation of the Bell-Pal fundamental equation for (low power) neutron stochastic behaviour in the Boltzmann continuum model is given. The development includes correlation of particle emission direction in induced and spontaneous fission. This leads to generalizations of the backward and forward equations for the mean and variance of neutron behaviour. The stochastic importance for neutron transport theory is introduced and related to the conventional deterministic importance. Defining equations and moment equations are derived and shown to be related to the backward fundamental equation with the detector distribution of the operational definition of stochastic importance playing the role of an adjoint source. (author)

Entropy Production in Stochastics

Directory of Open Access Journals (Sweden)

Demetris Koutsoyiannis

2017-10-01

Full Text Available While the modern definition of entropy is genuinely probabilistic, in entropy production the classical thermodynamic definition, as in heat transfer, is typically used. Here we explore the concept of entropy production within stochastics and, particularly, two forms of entropy production in logarithmic time, unconditionally (EPLT or conditionally on the past and present having been observed (CEPLT. We study the theoretical properties of both forms, in general and in application to a broad set of stochastic processes. A main question investigated, related to model identification and fitting from data, is how to estimate the entropy production from a time series. It turns out that there is a link of the EPLT with the climacogram, and of the CEPLT with two additional tools introduced here, namely the differenced climacogram and the climacospectrum. In particular, EPLT and CEPLT are related to slopes of log-log plots of these tools, with the asymptotic slopes at the tails being most important as they justify the emergence of scaling laws of second-order characteristics of stochastic processes. As a real-world application, we use an extraordinary long time series of turbulent velocity and show how a parsimonious stochastic model can be identified and fitted using the tools developed.

Understanding Financial Market Volatility

NARCIS (Netherlands)

A. Opschoor (Anne)

2014-01-01

markdownabstract__Abstract__ Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. Loosely speaking, volatility is defined as the average magnitude of fluctuations observed in some phenomenon over

Oil Volatility Risk and Expected Stock Returns

DEFF Research Database (Denmark)

Christoffersen, Peter; Pan, Xuhui (Nick)

After the financialization of commodity futures markets in 2004-05 oil volatility has become a strong predictor of returns and volatility of the overall stock market. Furthermore, stocks' exposure to oil volatility risk now drives the cross-section of expected returns. The difference in average...... return between the quintile of stocks with low exposure and high exposure to oil volatility is significant at 0.66% per month, and oil volatility risk carries a significant risk premium of -0.60% per month. In the post-financialization period, oil volatility risk is strongly related with various measures...

Core-Mantle Partitioning of Volatile Elements and the Origin of Volatile Elements in Earth and Moon

Science.gov (United States)

Righter, K.; Pando, K.; Danielson, L.; Nickodem, K.

2014-01-01

Depletions of siderophile elements in mantles have placed constraints on the conditions on core segregation and differentiation in bodies such as Earth, Earth's Moon, Mars, and asteroid 4 Vesta. Among the siderophile elements there are a sub-set that are also volatile (volatile siderophile elements or VSE; Ga, Ge, In, As, Sb, Sn, Bi, Zn, Cu, Cd), and thus can help to constrain the origin of volatile elements in these bodies, and in particular the Earth and Moon. One of the fundamental observations of the geochemistry of the Moon is the overall depletion of volatile elements relative to the Earth, but a satisfactory explanation has remained elusive. Hypotheses for Earth include addition during accretion and core formation and mobilized into the metallic core, multiple stage origin, or addition after the core formed. Any explanation for volatile elements in the Earth's mantle must also be linked to an explanation of these elements in the lunar mantle. New metal-silicate partitioning data will be applied to the origin of volatile elements in both the Earth and Moon, and will evaluate theories for exogenous versus endogenous origin of volatile elements.

Stochastic approach to microphysics

Energy Technology Data Exchange (ETDEWEB)

Aron, J.C.

1987-01-01

The presently widespread idea of ''vacuum population'', together with the quantum concept of vacuum fluctuations leads to assume a random level below that of matter. This stochastic approach starts by a reminder of the author's previous work, first on the relation of diffusion laws with the foundations of microphysics, and then on hadron spectrum. Following the latter, a random quark model is advanced; it gives to quark pairs properties similar to those of a harmonic oscillator or an elastic string, imagined as an explanation to their asymptotic freedom and their confinement. The stochastic study of such interactions as electron-nucleon, jets in e/sup +/e/sup -/ collisions, or pp -> ..pi../sup 0/ + X, gives form factors closely consistent with experiment. The conclusion is an epistemological comment (complementarity between stochastic and quantum domains, E.P.R. paradox, etc...).

Essays on Quantitative Finance

DEFF Research Database (Denmark)

Jönsson, Martin

This thesis consists of ve research papers written during the period March 2014 - April 2016. The papers can be read independently and their abstracts are: 1. European Option Pricing with Stochastic Volatility Models under Pa- rameter Uncertainty. We consider stochastic volatility models under pa...

Supercritical fluid extraction of volatile and non-volatile compounds from Schinus molle L.

Directory of Open Access Journals (Sweden)

M. S. T. Barroso

2011-06-01

Full Text Available Schinus molle L., also known as pepper tree, has been reported to have antimicrobial, antifungal, anti-inflammatory, antispasmodic, antipyretic, antitumoural and cicatrizing properties. This work studies supercritical fluid extraction (SFE to obtain volatile and non-volatile compounds from the aerial parts of Schinus molle L. and the influence of the process on the composition of the extracts. Experiments were performed in a pilot-scale extractor with a capacity of 1 L at pressures of 9, 10, 12, 15 and 20 MPa at 323.15 K. The volatile compounds were obtained by CO2 supercritical extraction with moderate pressure (9 MPa, whereas the non-volatile compounds were extracted at higher pressure (12 to 20 MPa. The analysis of the essential oil was carried out by GC-MS and the main compounds identified were sabinene, limonene, D-germacrene, bicyclogermacrene, and spathulenol. For the non-volatile extracts, the total phenolic content was determined by the Folin-Ciocalteau method. Moreover, one of the goals of this study was to compare the experimental data with the simulated yields predicted by a mathematical model based on mass transfer. The model used requires three adjustable parameters to predict the experimental extraction yield curves.

Markov stochasticity coordinates

International Nuclear Information System (INIS)

Eliazar, Iddo

2017-01-01

Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.

Markov stochasticity coordinates

Energy Technology Data Exchange (ETDEWEB)

Eliazar, Iddo, E-mail: iddo.eliazar@intel.com

2017-01-15

Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.

A Generalized Schwartz Model for Energy Spot Prices - Estimation using a Particle MCMC Method

DEFF Research Database (Denmark)

Lunde, Asger; Brix, Anne Floor; Wei, Wei

structure. Instead of using various filtering techniques for splitting the two factors, as often found in the literature, we estimate the model in one step using an adaptive MCMC method with a Rao-Blackwellized particle filter. We fit the model to UK natural gas spot prices and investigate the importance......We propose an energy spot price model featuring a two-factor price process and a two-component stochastic volatility process. The first factor in the price process captures the normal variations; the second accounts for spikes. The two-component volatility allows for a flexible autocorrelation...... of spikes and stochastic volatility. We find that the inclusion of stochastic volatility is crucial and that it strongly impacts the jump intensity in the spike process. Furthermore, our estimation method enables us to consider both continuous and purely jump-driven volatility processes, and thereby assess...

Long Memory in Stock Market Volatility and the Volatility-in-Mean Effect: The FIEGARCH-M Model

DEFF Research Database (Denmark)

Christensen, Bent Jesper; Nielsen, Morten Ørregaard; Zhu, Jie

We extend the fractionally integrated exponential GARCH (FIEGARCH) model for daily stock return data with long memory in return volatility of Bollerslev and Mikkelsen (1996) by introducing a possible volatility-in-mean effect. To avoid that the long memory property of volatility carries over to r...

Approximating Preemptive Stochastic Scheduling

OpenAIRE

Megow Nicole; Vredeveld Tjark

2009-01-01

We present constant approximative policies for preemptive stochastic scheduling. We derive policies with a guaranteed performance ratio of 2 for scheduling jobs with release dates on identical parallel machines subject to minimizing the sum of weighted completion times. Our policies as well as their analysis apply also to the recently introduced more general model of stochastic online scheduling. The performance guarantee we give matches the best result known for the corresponding determinist...

The stochastic goodwill problem

OpenAIRE

Marinelli, Carlo

2003-01-01

Stochastic control problems related to optimal advertising under uncertainty are considered. In particular, we determine the optimal strategies for the problem of maximizing the utility of goodwill at launch time and minimizing the disutility of a stream of advertising costs that extends until the launch time for some classes of stochastic perturbations of the classical Nerlove-Arrow dynamics. We also consider some generalizations such as problems with constrained budget and with discretionar...

Sequential neural models with stochastic layers

DEFF Research Database (Denmark)

Fraccaro, Marco; Sønderby, Søren Kaae; Paquet, Ulrich

2016-01-01

How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural...... generative model. The clear separation of deterministic and stochastic layers allows a structured variational inference network to track the factorization of the model's posterior distribution. By retaining both the nonlinear recursive structure of a recurrent neural network and averaging over...

Asymmetric Realized Volatility Risk

NARCIS (Netherlands)

D.E. Allen (David); M.J. McAleer (Michael); M. Scharth (Marcel)

2014-01-01

markdownabstract__Abstract__ In this paper we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized

A methodology for stochastic analysis of share prices as Markov chains with finite states.

Science.gov (United States)

Mettle, Felix Okoe; Quaye, Enoch Nii Boi; Laryea, Ravenhill Adjetey

2014-01-01

Price volatilities make stock investments risky, leaving investors in critical position when uncertain decision is made. To improve investor evaluation confidence on exchange markets, while not using time series methodology, we specify equity price change as a stochastic process assumed to possess Markov dependency with respective state transition probabilities matrices following the identified state pace (i.e. decrease, stable or increase). We established that identified states communicate, and that the chains are aperiodic and ergodic thus possessing limiting distributions. We developed a methodology for determining expected mean return time for stock price increases and also establish criteria for improving investment decision based on highest transition probabilities, lowest mean return time and highest limiting distributions. We further developed an R algorithm for running the methodology introduced. The established methodology is applied to selected equities from Ghana Stock Exchange weekly trading data.

History-dependent stochastic Petri nets

NARCIS (Netherlands)

Schonenberg, H.; Sidorova, N.; Aalst, van der W.M.P.; Hee, van K.M.; Pnueli, A.; Virbitskaite, I.; Voronkov, A.

2010-01-01

Stochastic Petri Nets are a useful and well-known tool for performance analysis. However, an implicit assumption in the different types of Stochastic Petri Nets is the Markov property. It is assumed that a choice in the Petri net only depends on the current state and not on earlier choices. For many

Stochastic ferromagnetism analysis and numerics

CERN Document Server

Brzezniak, Zdzislaw; Neklyudov, Mikhail; Prohl, Andreas

2013-01-01

This monograph examines magnetization dynamics at elevated temperatures which can be described by the stochastic Landau-Lifshitz-Gilbert equation (SLLG). Comparative computational studies with the stochastic model are included. Constructive tools such as e.g. finite element methods are used to derive the theoretical results, which are then used for computational studies.

Modelling Cow Behaviour Using Stochastic Automata

DEFF Research Database (Denmark)

Jónsson, Ragnar Ingi

This report covers an initial study on the modelling of cow behaviour using stochastic automata with the aim of detecting lameness. Lameness in cows is a serious problem that needs to be dealt with because it results in less profitable production units and in reduced quality of life...... for the affected livestock. By featuring training data consisting of measurements of cow activity, three different models are obtained, namely an autonomous stochastic automaton, a stochastic automaton with coinciding state and output and an autonomous stochastic automaton with coinciding state and output, all...... of which describe the cows' activity in the two regarded behavioural scenarios, non-lame and lame. Using the experimental measurement data the different behavioural relations for the two regarded behavioural scenarios are assessed. The three models comprise activity within last hour, activity within last...

Uncertainty of Volatility Estimates from Heston Greeks

Directory of Open Access Journals (Sweden)

Oliver Pfante

2018-01-01

Full Text Available Volatility is a widely recognized measure of market risk. As volatility is not observed it has to be estimated from market prices, i.e., as the implied volatility from option prices. The volatility index VIX making volatility a tradeable asset in its own right is computed from near- and next-term put and call options on the S&P 500 with more than 23 days and less than 37 days to expiration and non-vanishing bid. In the present paper we quantify the information content of the constituents of the VIX about the volatility of the S&P 500 in terms of the Fisher information matrix. Assuming that observed option prices are centered on the theoretical price provided by Heston's model perturbed by additive Gaussian noise we relate their Fisher information matrix to the Greeks in the Heston model. We find that the prices of options contained in the VIX basket allow for reliable estimates of the volatility of the S&P 500 with negligible uncertainty as long as volatility is large enough. Interestingly, if volatility drops below a critical value of roughly 3%, inferences from option prices become imprecise because Vega, the derivative of a European option w.r.t. volatility, and thereby the Fisher information nearly vanishes.

Exact Algorithms for Solving Stochastic Games

DEFF Research Database (Denmark)

Hansen, Kristoffer Arnsfelt; Koucky, Michal; Lauritzen, Niels

2012-01-01

Shapley's discounted stochastic games, Everett's recursive games and Gillette's undiscounted stochastic games are classical models of game theory describing two-player zero-sum games of potentially infinite duration. We describe algorithms for exactly solving these games....

Statistical Methods for Stochastic Differential Equations

CERN Document Server

Kessler, Mathieu; Sorensen, Michael

2012-01-01

The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to the topic at hand and builds gradually towards discussing recent research. The book covers Wiener-driven equations as well as stochastic differential equations with jumps, including continuous-time ARMA processes and COGARCH processes. It presents a sp

Fluctuation behaviors of financial return volatility duration

Science.gov (United States)

Niu, Hongli; Wang, Jun; Lu, Yunfan

2016-04-01

It is of significantly crucial to understand the return volatility of financial markets because it helps to quantify the investment risk, optimize the portfolio, and provide a key input of option pricing models. The characteristics of isolated high volatility events above certain threshold in price fluctuations and the distributions of return intervals between these events arouse great interest in financial research. In the present work, we introduce a new concept of daily return volatility duration, which is defined as the shortest passage time when the future volatility intensity is above or below the current volatility intensity (without predefining a threshold). The statistical properties of the daily return volatility durations for seven representative stock indices from the world financial markets are investigated. Some useful and interesting empirical results of these volatility duration series about the probability distributions, memory effects and multifractal properties are obtained. These results also show that the proposed stock volatility series analysis is a meaningful and beneficial trial.

Stochastic quantization of general relativity

International Nuclear Information System (INIS)

Rumpf, H.

1986-01-01

Following an elementary exposition of the basic mathematical concepts used in the theory of stochastic relaxation processes the stochastic quantization method of Parisi and Wu is briefly reviewed. The method is applied to Einstein's theory of gravitation using a formalism that is manifestly covariant with respect to field redefinitions. This requires the adoption of Ito's calculus and the introduction of a metric in field configuration space, for which there is a unique candidate. Due to the indefiniteness of the Euclidean Einstein-Hilbert action stochastic quantization is generalized to the pseudo-Riemannian case. It is formally shown to imply the DeWitt path integral measure. Finally a new type of perturbation theory is developed. (Author)

Stochastic estimation of electricity consumption

International Nuclear Information System (INIS)

Kapetanovic, I.; Konjic, T.; Zahirovic, Z.

1999-01-01

Electricity consumption forecasting represents a part of the stable functioning of the power system. It is very important because of rationality and increase of control process efficiency and development planning of all aspects of society. On a scientific basis, forecasting is a possible way to solve problems. Among different models that have been used in the area of forecasting, the stochastic aspect of forecasting as a part of quantitative models takes a very important place in applications. ARIMA models and Kalman filter as stochastic estimators have been treated together for electricity consumption forecasting. Therefore, the main aim of this paper is to present the stochastic forecasting aspect using short time series. (author)

Ambient Volatility of Triethyl Phosphate

Science.gov (United States)

2017-08-01

of materials is predictable using Raoult’s law. This report details the measurement of the effect of water vapor partial pressure on the volatility...empirical correlation taking into account nonideal behavior was developed to enable estimation of TEPO volatility at any combination of ambient...of the second component is expected to be one-half as much as in the absence of water vapor. Similarly, the measured volatility of the second

Stochastic dynamics and irreversibility

CERN Document Server

Tomé, Tânia

2015-01-01

This textbook presents an exposition of stochastic dynamics and irreversibility. It comprises the principles of probability theory and the stochastic dynamics in continuous spaces, described by Langevin and Fokker-Planck equations, and in discrete spaces, described by Markov chains and master equations. Special concern is given to the study of irreversibility, both in systems that evolve to equilibrium and in nonequilibrium stationary states. Attention is also given to the study of models displaying phase transitions and critical phenomema both in thermodynamic equilibrium and out of equilibrium. These models include the linear Glauber model, the Glauber-Ising model, lattice models with absorbing states such as the contact process and those used in population dynamic and spreading of epidemic, probabilistic cellular automata, reaction-diffusion processes, random sequential adsorption and dynamic percolation. A stochastic approach to chemical reaction is also presented.The textbook is intended for students of ...

Volatility persistence in crude oil markets

International Nuclear Information System (INIS)

Charles, Amélie; Darné, Olivier

2014-01-01

Financial market participants and policy-makers can benefit from a better understanding of how shocks can affect volatility over time. This study assesses the impact of structural changes and outliers on volatility persistence of three crude oil markets – Brent, West Texas Intermediate (WTI) and Organization of Petroleum Exporting Countries (OPEC) – between January 2, 1985 and June 17, 2011. We identify outliers using a new semi-parametric test based on conditional heteroscedasticity models. These large shocks can be associated with particular event patterns, such as the invasion of Kuwait by Iraq, the Operation Desert Storm, the Operation Desert Fox, and the Global Financial Crisis as well as OPEC announcements on production reduction or US announcements on crude inventories. We show that outliers can bias (i) the estimates of the parameters of the equation governing volatility dynamics; (ii) the regularity and non-negativity conditions of GARCH-type models (GARCH, IGARCH, FIGARCH and HYGARCH); and (iii) the detection of structural breaks in volatility, and thus the estimation of the persistence of the volatility. Therefore, taking into account the outliers on the volatility modelling process may improve the understanding of volatility in crude oil markets. - Highlights: • We study the impact of outliers on volatility persistence of crude oil markets. • We identify outliers and patches of outliers due to specific events. • We show that outliers can bias (i) the estimates of the parameters of GARCH models, (ii) the regularity and non-negativity conditions of GARCH-type models, (iii) the detection of structural breaks in volatility of crude oil markets

Improving Garch Volatility Forecasts

NARCIS (Netherlands)

Klaassen, F.J.G.M.

1998-01-01

Many researchers use GARCH models to generate volatility forecasts. We show, however, that such forecasts are too variable. To correct for this, we extend the GARCH model by distinguishing two regimes with different volatility levels. GARCH effects are allowed within each regime, so that our model

Automated Flight Routing Using Stochastic Dynamic Programming

Science.gov (United States)

Ng, Hok K.; Morando, Alex; Grabbe, Shon

2010-01-01

Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.

The effect of volatility on percutaneous absorption.

Science.gov (United States)

Rouse, Nicole C; Maibach, Howard I

2016-01-01

Topically applied chemicals may volatilize, or evaporate, from skin leaving behind a chemical residue with new percutaneous absorptive capabilities. Understanding volatilization of topical medications, such as sunscreens, fragrances, insect repellants, cosmetics and other commonly applied topicals may have implications for their safety and efficacy. A systematic review of English language articles from 1979 to 2014 was performed using key search terms. Articles were evaluated to assess the relationship between volatility and percutaneous absorption. A total of 12 articles were selected and reviewed. Key findings were that absorption is enhanced when coupled with a volatile substance, occlusion prevents evaporation and increases absorption, high ventilation increases volatilization and reduces absorption, and pH of skin has an affect on a chemical's volatility. The articles also brought to light that different methods may have an affect on volatility: different body regions; in vivo vs. in vitro; human vs. Data suggest that volatility is crucial for determining safety and efficacy of cutaneous exposures and therapies. Few articles have been documented reporting evaporation in the context of percutaneous absorption, and of those published, great variability exists in methods. Further investigation of volatility is needed to properly evaluate its role in percutaneous absorption.

Transport properties of stochastic Lorentz models

NARCIS (Netherlands)

Beijeren, H. van

Diffusion processes are considered for one-dimensional stochastic Lorentz models, consisting of randomly distributed fixed scatterers and one moving light particle. In waiting time Lorentz models the light particle makes instantaneous jumps between scatterers after a stochastically distributed

Stochastic gene expression in Arabidopsis thaliana.

Science.gov (United States)

Araújo, Ilka Schultheiß; Pietsch, Jessica Magdalena; Keizer, Emma Mathilde; Greese, Bettina; Balkunde, Rachappa; Fleck, Christian; Hülskamp, Martin

2017-12-14

Although plant development is highly reproducible, some stochasticity exists. This developmental stochasticity may be caused by noisy gene expression. Here we analyze the fluctuation of protein expression in Arabidopsis thaliana. Using the photoconvertible KikGR marker, we show that the protein expressions of individual cells fluctuate over time. A dual reporter system was used to study extrinsic and intrinsic noise of marker gene expression. We report that extrinsic noise is higher than intrinsic noise and that extrinsic noise in stomata is clearly lower in comparison to several other tissues/cell types. Finally, we show that cells are coupled with respect to stochastic protein expression in young leaves, hypocotyls and roots but not in mature leaves. Our data indicate that stochasticity of gene expression can vary between tissues/cell types and that it can be coupled in a non-cell-autonomous manner.

Stochastic deformation of a thermodynamic symplectic structure

OpenAIRE

Kazinski, P. O.

2008-01-01

A stochastic deformation of a thermodynamic symplectic structure is studied. The stochastic deformation procedure is analogous to the deformation of an algebra of observables like deformation quantization, but for an imaginary deformation parameter (the Planck constant). Gauge symmetries of thermodynamics and corresponding stochastic mechanics, which describes fluctuations of a thermodynamic system, are revealed and gauge fields are introduced. A physical interpretation to the gauge transform...

Stochastic differential equations and diffusion processes

CERN Document Server

Ikeda, N

1989-01-01

Being a systematic treatment of the modern theory of stochastic integrals and stochastic differential equations, the theory is developed within the martingale framework, which was developed by J.L. Doob and which plays an indispensable role in the modern theory of stochastic analysis.A considerable number of corrections and improvements have been made for the second edition of this classic work. In particular, major and substantial changes are in Chapter III and Chapter V where the sections treating excursions of Brownian Motion and the Malliavin Calculus have been expanded and refined. Sectio

Modeling and analysis of stochastic systems

CERN Document Server

Kulkarni, Vidyadhar G

2011-01-01

Based on the author's more than 25 years of teaching experience, Modeling and Analysis of Stochastic Systems, Second Edition covers the most important classes of stochastic processes used in the modeling of diverse systems, from supply chains and inventory systems to genetics and biological systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. Along with reorganizing the material, this edition revises and adds new exercises and examples. New to the second edi

Stochastic resonance: noise-enhanced order

International Nuclear Information System (INIS)

Anishchenko, Vadim S; Neiman, Arkady B; Moss, F; Shimansky-Geier, L

1999-01-01

Stochastic resonance (SR) provides a glaring example of a noise-induced transition in a nonlinear system driven by an information signal and noise simultaneously. In the regime of SR some characteristics of the information signal (amplification factor, signal-to-noise ratio, the degrees of coherence and of order, etc.) at the output of the system are significantly improved at a certain optimal noise level. SR is realized only in nonlinear systems for which a noise-intensity-controlled characteristic time becomes available. In the present review the physical mechanism and methods of theoretical description of SR are briefly discussed. SR features determined by the structure of the information signal, noise statistics and properties of particular systems with SR are studied. A nontrivial phenomenon of stochastic synchronization defined as locking of the instantaneous phase and switching frequency of a bistable system by external periodic force is analyzed in detail. Stochastic synchronization is explored in single and coupled bistable oscillators, including ensembles. The effects of SR and stochastic synchronization of ensembles of stochastic resonators are studied both with and without coupling between the elements. SR is considered in dynamical and nondynamical (threshold) systems. The SR effect is analyzed from the viewpoint of information and entropy characteristics of the signal, which determine the degree of order or self-organization in the system. Applications of the SR concept to explaining the results of a series of biological experiments are discussed. (reviews of topical problems)

Stochastic resonance: noise-enhanced order

Energy Technology Data Exchange (ETDEWEB)

Anishchenko, Vadim S; Neiman, Arkady B [N.G. Chernyshevskii Saratov State University, Saratov (Russian Federation); Moss, F [Department of Physics and Astronomy, University of Missouri at St. Louis (United States); Shimansky-Geier, L [Humboldt University at Berlin (Germany)

1999-01-31

Stochastic resonance (SR) provides a glaring example of a noise-induced transition in a nonlinear system driven by an information signal and noise simultaneously. In the regime of SR some characteristics of the information signal (amplification factor, signal-to-noise ratio, the degrees of coherence and of order, etc.) at the output of the system are significantly improved at a certain optimal noise level. SR is realized only in nonlinear systems for which a noise-intensity-controlled characteristic time becomes available. In the present review the physical mechanism and methods of theoretical description of SR are briefly discussed. SR features determined by the structure of the information signal, noise statistics and properties of particular systems with SR are studied. A nontrivial phenomenon of stochastic synchronization defined as locking of the instantaneous phase and switching frequency of a bistable system by external periodic force is analyzed in detail. Stochastic synchronization is explored in single and coupled bistable oscillators, including ensembles. The effects of SR and stochastic synchronization of ensembles of stochastic resonators are studied both with and without coupling between the elements. SR is considered in dynamical and nondynamical (threshold) systems. The SR effect is analyzed from the viewpoint of information and entropy characteristics of the signal, which determine the degree of order or self-organization in the system. Applications of the SR concept to explaining the results of a series of biological experiments are discussed. (reviews of topical problems)

An overview of a multifactor-system theory of personality and individual differences: III. Life span development and the heredity-environment issue.

Science.gov (United States)

Powell, A; Royce, J R

1981-12-01

In Part III of this three-part series on multifactor-system theory, multivariate, life-span development is approached from the standpoint of a quantitative and qualitative analysis of the ontogenesis of factors in each of the six systems. The pattern of quantitative development (described via the Gompertz equation and three developmental parameters) involves growth, stability, and decline, and qualitative development involves changes in the organization of factors (e.g., factor differentiation and convergence). Hereditary and environmental sources of variation are analyzed via the factor gene model and the concept of heredity-dominant factors, and the factor-learning model and environment-dominant factors. It is hypothesized that the sensory and motor systems are heredity dominant, that the style and value systems are environment dominant, and that the cognitive and affective systems are partially heredity dominant.

Interior Volatile Reservoirs in Mercury

Science.gov (United States)

Anzures, B. A.; Parman, S. W.; Milliken, R. E.; Head, J. W.

2018-05-01

More measurements of 1) surface volatiles, and 2) pyroclastic deposits paired with experimental volatile analyses in silicate minerals can constrain conditions of melting and subsequent eruption on Mercury.

Stochastic Community Assembly: Does It Matter in Microbial Ecology?

Science.gov (United States)

Zhou, Jizhong; Ning, Daliang

2017-12-01

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research. Copyright © 2017 American Society for Microbiology.

Non-volatile memories

CERN Document Server

Lacaze, Pierre-Camille

2014-01-01

Written for scientists, researchers, and engineers, Non-volatile Memories describes the recent research and implementations in relation to the design of a new generation of non-volatile electronic memories. The objective is to replace existing memories (DRAM, SRAM, EEPROM, Flash, etc.) with a universal memory model likely to reach better performances than the current types of memory: extremely high commutation speeds, high implantation densities and retention time of information of about ten years.

Stochastic processes

CERN Document Server

Borodin, Andrei N

2017-01-01

This book provides a rigorous yet accessible introduction to the theory of stochastic processes. A significant part of the book is devoted to the classic theory of stochastic processes. In turn, it also presents proofs of well-known results, sometimes together with new approaches. Moreover, the book explores topics not previously covered elsewhere, such as distributions of functionals of diffusions stopped at different random times, the Brownian local time, diffusions with jumps, and an invariance principle for random walks and local times. Supported by carefully selected material, the book showcases a wealth of examples that demonstrate how to solve concrete problems by applying theoretical results. It addresses a broad range of applications, focusing on concrete computational techniques rather than on abstract theory. The content presented here is largely self-contained, making it suitable for researchers and graduate students alike.

Stochastic chaos in a Duffing oscillator and its control

International Nuclear Information System (INIS)

Wu Cunli; Lei Youming; Fang Tong

2006-01-01

Stochastic chaos discussed here means a kind of chaotic responses in a Duffing oscillator with bounded random parameters under harmonic excitations. A system with random parameters is usually called a stochastic system. The modifier 'stochastic' here implies dependent on some random parameter. As the system itself is stochastic, so is the response, even under harmonic excitations alone. In this paper stochastic chaos and its control are verified by the top Lyapunov exponent of the system. A non-feedback control strategy is adopted here by adding an adjustable noisy phase to the harmonic excitation, so that the control can be realized by adjusting the noise level. It is found that by this control strategy stochastic chaos can be tamed down to the small neighborhood of a periodic trajectory or an equilibrium state. In the analysis the stochastic Duffing oscillator is first transformed into an equivalent deterministic nonlinear system by the Gegenbauer polynomial approximation, so that the problem of controlling stochastic chaos can be reduced into the problem of controlling deterministic chaos in the equivalent system. Then the top Lyapunov exponent of the equivalent system is obtained by Wolf's method to examine the chaotic behavior of the response. Numerical simulations show that the random phase control strategy is an effective way to control stochastic chaos

Volcanic fluxes of volatiles. Preliminary estimates based on rare gas and major volatile calibration

International Nuclear Information System (INIS)

Marty, B.

1992-01-01

New estimates for volatile fluxes into the atmosphere and hydrosphere through volcanism have been computed using the measured fluxes of 3 He in oceans and SO 2 in the atmosphere, and the ratios between the volatiles in Mid-Ocean Ridge basalts and in high temperature volcanic gases. These estimates have been checked using independent estimates of the volcanic fluxes. This method provides a reliable means of tracing volatile fluxes, although its precision is restricted by the limited amount of data currently available. (author). 19 refs, 1 tab

Stochastic stability and bifurcation in a macroeconomic model

International Nuclear Information System (INIS)

Li Wei; Xu Wei; Zhao Junfeng; Jin Yanfei

2007-01-01

On the basis of the work of Goodwin and Puu, a new business cycle model subject to a stochastically parametric excitation is derived in this paper. At first, we reduce the model to a one-dimensional diffusion process by applying the stochastic averaging method of quasi-nonintegrable Hamiltonian system. Secondly, we utilize the methods of Lyapunov exponent and boundary classification associated with diffusion process respectively to analyze the stochastic stability of the trivial solution of system. The numerical results obtained illustrate that the trivial solution of system must be globally stable if it is locally stable in the state space. Thirdly, we explore the stochastic Hopf bifurcation of the business cycle model according to the qualitative changes in stationary probability density of system response. It is concluded that the stochastic Hopf bifurcation occurs at two critical parametric values. Finally, some explanations are given in a simply way on the potential applications of stochastic stability and bifurcation analysis

Problems of Mathematical Finance by Stochastic Control Methods

Science.gov (United States)

Stettner, Łukasz

The purpose of this paper is to present main ideas of mathematics of finance using the stochastic control methods. There is an interplay between stochastic control and mathematics of finance. On the one hand stochastic control is a powerful tool to study financial problems. On the other hand financial applications have stimulated development in several research subareas of stochastic control in the last two decades. We start with pricing of financial derivatives and modeling of asset prices, studying the conditions for the absence of arbitrage. Then we consider pricing of defaultable contingent claims. Investments in bonds lead us to the term structure modeling problems. Special attention is devoted to historical static portfolio analysis called Markowitz theory. We also briefly sketch dynamic portfolio problems using viscosity solutions to Hamilton-Jacobi-Bellman equation, martingale-convex analysis method or stochastic maximum principle together with backward stochastic differential equation. Finally, long time portfolio analysis for both risk neutral and risk sensitive functionals is introduced.

Stochastic goal-oriented error estimation with memory

Science.gov (United States)

Ackmann, Jan; Marotzke, Jochem; Korn, Peter

2017-11-01

We propose a stochastic dual-weighted error estimator for the viscous shallow-water equation with boundaries. For this purpose, previous work on memory-less stochastic dual-weighted error estimation is extended by incorporating memory effects. The memory is introduced by describing the local truncation error as a sum of time-correlated random variables. The random variables itself represent the temporal fluctuations in local truncation errors and are estimated from high-resolution information at near-initial times. The resulting error estimator is evaluated experimentally in two classical ocean-type experiments, the Munk gyre and the flow around an island. In these experiments, the stochastic process is adapted locally to the respective dynamical flow regime. Our stochastic dual-weighted error estimator is shown to provide meaningful error bounds for a range of physically relevant goals. We prove, as well as show numerically, that our approach can be interpreted as a linearized stochastic-physics ensemble.

Stochasticity Modeling in Memristors

KAUST Repository

Naous, Rawan

2015-10-26

Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital feature for the integration of this nonlinear device into the stochastic electronics realm of study. In this paper, experimentally observed innate stochasticity is modeled in a circuit compatible format. The model proposed is generic and could be incorporated into variants of threshold-based memristor models in which apparent variations in the output hysteresis convey the switching threshold shift. Further application as a noise injection alternative paves the way for novel approaches in the fields of neuromorphic engineering circuits design. On the other hand, extra caution needs to be paid to variability intolerant digital designs based on non-deterministic memristor logic.

Stochasticity Modeling in Memristors

KAUST Repository

Naous, Rawan; Al-Shedivat, Maruan; Salama, Khaled N.

2015-01-01

Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital feature for the integration of this nonlinear device into the stochastic electronics realm of study. In this paper, experimentally observed innate stochasticity is modeled in a circuit compatible format. The model proposed is generic and could be incorporated into variants of threshold-based memristor models in which apparent variations in the output hysteresis convey the switching threshold shift. Further application as a noise injection alternative paves the way for novel approaches in the fields of neuromorphic engineering circuits design. On the other hand, extra caution needs to be paid to variability intolerant digital designs based on non-deterministic memristor logic.

Stochasticity and transport in Hamiltonian systems

International Nuclear Information System (INIS)

MacKay, R.S.; Meiss, J.D.; Percival, I.C.

1983-08-01

The theory of transport in nonlinear dynamics is developed in terms of leaky barriers which remain when invariant tori are destroyed. We describe the organization of stochastic motion by these barriers and give an explanation of long-time correlations in the stochastic regime

Stochastic quantization

International Nuclear Information System (INIS)

Klauder, J.R.

1983-01-01

The author provides an introductory survey to stochastic quantization in which he outlines this new approach for scalar fields, gauge fields, fermion fields, and condensed matter problems such as electrons in solids and the statistical mechanics of quantum spins. (Auth.)

Long-time correlations in the stochastic regime

International Nuclear Information System (INIS)

Karney, C.F.F.

1982-11-01

The phase space for Hamiltonians of two degrees of freedom is usually divided into stochastic and integrable components. Even when well into the stochastic regime, integrable orbits may surround small stable regions or islands. The effect of these islands on the correlation function for the stochastic trajectories is examined. Depending on the value of the parameter describing the rotation number for the elliptic fixed point at the center of the island, the long-time correlation function may decay as t -5 or exponentially, but more commonly it decays much more slowly (roughly as t -1 ). As a consequence these small islands may have a profound effect on the properties such as the diffusion coefficient, of the stochastic orbits

Stochastic development regression using method of moments

DEFF Research Database (Denmark)

Kühnel, Line; Sommer, Stefan Horst

2017-01-01

This paper considers the estimation problem arising when inferring parameters in the stochastic development regression model for manifold valued non-linear data. Stochastic development regression captures the relation between manifold-valued response and Euclidean covariate variables using...... the stochastic development construction. It is thereby able to incorporate several covariate variables and random effects. The model is intrinsically defined using the connection of the manifold, and the use of stochastic development avoids linearizing the geometry. We propose to infer parameters using...... the Method of Moments procedure that matches known constraints on moments of the observations conditional on the latent variables. The performance of the model is investigated in a simulation example using data on finite dimensional landmark manifolds....

Introduction to stochastic analysis integrals and differential equations

CERN Document Server

Mackevicius, Vigirdas

2013-01-01

This is an introduction to stochastic integration and stochastic differential equations written in an understandable way for a wide audience, from students of mathematics to practitioners in biology, chemistry, physics, and finances. The presentation is based on the naïve stochastic integration, rather than on abstract theories of measure and stochastic processes. The proofs are rather simple for practitioners and, at the same time, rather rigorous for mathematicians. Detailed application examples in natural sciences and finance are presented. Much attention is paid to simulation diffusion pro

Memristor-based neural networks: Synaptic versus neuronal stochasticity

KAUST Repository

Naous, Rawan

2016-11-02

In neuromorphic circuits, stochasticity in the cortex can be mapped into the synaptic or neuronal components. The hardware emulation of these stochastic neural networks are currently being extensively studied using resistive memories or memristors. The ionic process involved in the underlying switching behavior of the memristive elements is considered as the main source of stochasticity of its operation. Building on its inherent variability, the memristor is incorporated into abstract models of stochastic neurons and synapses. Two approaches of stochastic neural networks are investigated. Aside from the size and area perspective, the impact on the system performance, in terms of accuracy, recognition rates, and learning, among these two approaches and where the memristor would fall into place are the main comparison points to be considered.

[Chemical components of Vetiveria zizanioides volatiles].

Science.gov (United States)

Huang, Jinghua; Li, Huashou; Yang, Jun; Chen, Yufen; Liu, Yinghu; Li, Ning; Nie, Chengrong

2004-01-01

The chemical components of the volatiles from Vetiveria zizanioides were analyzed by SPME and GC-MS. In the roots, the main component was valencene (30.36%), while in the shoots and leaves, they were 9-octadecenamide (33.50%), 2,6,10,15,19,23-hexamethyl-2,6,10,14,18,22-tetracosahexaene (27.46%), and 1,2-benzendicarboxylic acid, diisooctyl ester(18.29%). The results showed that there were many terpenoids in the volatils. In shoot volatiles, there existed 3 monoterpenes, 2 sequiterpenes and 1 triterpene. Most of the volatiles in roots were sesquiterpenes.

Time-ordered product expansions for computational stochastic system biology

International Nuclear Information System (INIS)

Mjolsness, Eric

2013-01-01

The time-ordered product framework of quantum field theory can also be used to understand salient phenomena in stochastic biochemical networks. It is used here to derive Gillespie’s stochastic simulation algorithm (SSA) for chemical reaction networks; consequently, the SSA can be interpreted in terms of Feynman diagrams. It is also used here to derive other, more general simulation and parameter-learning algorithms including simulation algorithms for networks of stochastic reaction-like processes operating on parameterized objects, and also hybrid stochastic reaction/differential equation models in which systems of ordinary differential equations evolve the parameters of objects that can also undergo stochastic reactions. Thus, the time-ordered product expansion can be used systematically to derive simulation and parameter-fitting algorithms for stochastic systems. (paper)

Foundations of stochastic analysis

CERN Document Server

Rao, M M; Lukacs, E

1981-01-01

Foundations of Stochastic Analysis deals with the foundations of the theory of Kolmogorov and Bochner and its impact on the growth of stochastic analysis. Topics covered range from conditional expectations and probabilities to projective and direct limits, as well as martingales and likelihood ratios. Abstract martingales and their applications are also discussed. Comprised of five chapters, this volume begins with an overview of the basic Kolmogorov-Bochner theorem, followed by a discussion on conditional expectations and probabilities containing several characterizations of operators and mea

Spatial stochasticity and non-continuum effects in gas flows

Energy Technology Data Exchange (ETDEWEB)

Dadzie, S. Kokou, E-mail: k.dadzie@glyndwr.ac.uk [Mechanical and Aeronautical Engineering, Glyndwr University, Mold Road, Wrexham LL11 2AW (United Kingdom); Reese, Jason M., E-mail: jason.reese@strath.ac.uk [Department of Mechanical and Aerospace Engineering, University of Strathclyde, Glasgow G1 1XJ (United Kingdom)

2012-02-06

We investigate the relationship between spatial stochasticity and non-continuum effects in gas flows. A kinetic model for a dilute gas is developed using strictly a stochastic molecular model reasoning, without primarily referring to either the Liouville or the Boltzmann equations for dilute gases. The kinetic equation, a stochastic version of the well-known deterministic Boltzmann equation for dilute gas, is then associated with a set of macroscopic equations for the case of a monatomic gas. Tests based on a heat conduction configuration and sound wave dispersion show that spatial stochasticity can explain some non-continuum effects seen in gases. -- Highlights: ► We investigate effects of molecular spatial stochasticity in non-continuum regime. ► Present a simplify spatial stochastic kinetic equation. ► Present a spatial stochastic macroscopic flow equations. ► Show effects of the new model on sound wave dispersion prediction. ► Show effects of the new approach in density profiles in a heat conduction.

Universality in stochastic exponential growth.

Science.gov (United States)

Iyer-Biswas, Srividya; Crooks, Gavin E; Scherer, Norbert F; Dinner, Aaron R

2014-07-11

Recent imaging data for single bacterial cells reveal that their mean sizes grow exponentially in time and that their size distributions collapse to a single curve when rescaled by their means. An analogous result holds for the division-time distributions. A model is needed to delineate the minimal requirements for these scaling behaviors. We formulate a microscopic theory of stochastic exponential growth as a Master Equation that accounts for these observations, in contrast to existing quantitative models of stochastic exponential growth (e.g., the Black-Scholes equation or geometric Brownian motion). Our model, the stochastic Hinshelwood cycle (SHC), is an autocatalytic reaction cycle in which each molecular species catalyzes the production of the next. By finding exact analytical solutions to the SHC and the corresponding first passage time problem, we uncover universal signatures of fluctuations in exponential growth and division. The model makes minimal assumptions, and we describe how more complex reaction networks can reduce to such a cycle. We thus expect similar scalings to be discovered in stochastic processes resulting in exponential growth that appear in diverse contexts such as cosmology, finance, technology, and population growth.

High-speed Stochastic Fatigue Testing

DEFF Research Database (Denmark)

Brincker, Rune; Sørensen, John Dalsgaard

1990-01-01

Good stochastic fatigue tests are difficult to perform. One of the major reasons is that ordinary servohydraulic loading systems realize the prescribed load history accurately at very low testing speeds only. If the speeds used for constant amplitude testing are applied to stochastic fatigue...

STOCHASTIC GRADIENT METHODS FOR UNCONSTRAINED OPTIMIZATION

Directory of Open Access Journals (Sweden)

Nataša Krejić

2014-12-01

Full Text Available This papers presents an overview of gradient based methods for minimization of noisy functions. It is assumed that the objective functions is either given with error terms of stochastic nature or given as the mathematical expectation. Such problems arise in the context of simulation based optimization. The focus of this presentation is on the gradient based Stochastic Approximation and Sample Average Approximation methods. The concept of stochastic gradient approximation of the true gradient can be successfully extended to deterministic problems. Methods of this kind are presented for the data fitting and machine learning problems.

SATA II - Stochastic Algebraic Topology and Applications

Science.gov (United States)

2017-01-30

AFRL-AFOSR-UK-TR-2017-0018 SATA II - Stochastic Algebraic Topology and Applications 150032 Robert Adler TECHNION ISRAEL INSTITUTE OF TECHNOLOGY Final...REPORT TYPE Final 3. DATES COVERED (From - To) 15 Dec 2014 to 14 Dec 2016 4. TITLE AND SUBTITLE SATA II - Stochastic Algebraic Topology and Applications... Topology and Applications Continuation of, and associated with SATA: Stochastic Algebraic Topology and Applications FA8655-11-1-3039, 09/1/2011–08/31/2014

Stochastic growth of localized plasma waves

International Nuclear Information System (INIS)

Robinson, P.A.; Cairns, Iver H.

2001-01-01

Localized bursty plasma waves are detected by spacecraft in many space plasmas. The large spatiotemporal scales involved imply that beam and other instabilities relax to marginal stability and that mean wave energies are low. Stochastic wave growth occurs when ambient fluctuations perturb the system, causing fluctuations about marginal stability. This yields regions where growth is enhanced and others where damping is increased; bursts are associated with enhanced growth and can occur even when the mean growth rate is negative. In stochastic growth, energy loss from the source is suppressed relative to secular growth, preserving it far longer than otherwise possible. Linear stochastic growth can operate at wave levels below thresholds of nonlinear wave-clumping mechanisms such as strong-turbulence modulational instability and is not subject to their coherence and wavelength limits. These mechanisms can be distinguished by statistics of the fields, whose strengths are lognormally distributed if stochastically growing and power-law distributed in strong turbulence. Recent applications of stochastic growth theory (SGT) are described, involving bursty plasma waves and unstable particle distributions in type III solar radio sources, the Earth's foreshock, magnetosheath, and polar cap regions. It is shown that when combined with wave-wave processes, SGT also accounts for associated radio emissions