Selection Criteria in Regime Switching Conditional Volatility Models

Directory of Open Access Journals (Sweden)

Thomas Chuffart

2015-05-01

Full Text Available A large number of nonlinear conditional heteroskedastic models have been proposed in the literature. Model selection is crucial to any statistical data analysis. In this article, we investigate whether the most commonly used selection criteria lead to choice of the right specification in a regime switching framework. We focus on two types of models: the Logistic Smooth Transition GARCH and the Markov-Switching GARCH models. Simulation experiments reveal that information criteria and loss functions can lead to misspecification ; BIC sometimes indicates the wrong regime switching framework. Depending on the Data Generating Process used in the experiments, great care is needed when choosing a criterion.

Stochastic Spiking Neural Networks Enabled by Magnetic Tunnel Junctions: From Nontelegraphic to Telegraphic Switching Regimes

Science.gov (United States)

Liyanagedera, Chamika M.; Sengupta, Abhronil; Jaiswal, Akhilesh; Roy, Kaushik

2017-12-01

Stochastic spiking neural networks based on nanoelectronic spin devices can be a possible pathway to achieving "brainlike" compact and energy-efficient cognitive intelligence. The computational model attempt to exploit the intrinsic device stochasticity of nanoelectronic synaptic or neural components to perform learning or inference. However, there has been limited analysis on the scaling effect of stochastic spin devices and its impact on the operation of such stochastic networks at the system level. This work attempts to explore the design space and analyze the performance of nanomagnet-based stochastic neuromorphic computing architectures for magnets with different barrier heights. We illustrate how the underlying network architecture must be modified to account for the random telegraphic switching behavior displayed by magnets with low barrier heights as they are scaled into the superparamagnetic regime. We perform a device-to-system-level analysis on a deep neural-network architecture for a digit-recognition problem on the MNIST data set.

REGIME SWITCHING DETERMINANTS OF SOVEREIGN CDS SPREADS: EVIDENCE FROM TURKEY

Directory of Open Access Journals (Sweden)

Umurcan Polat

2017-12-01

Full Text Available In this study, it is assessed the main determinants of sovereign CDS spreads in Turkey from January 2006 to December 2015. Before delving into the nonlinear Markov regime-switching model estimation, a conventional one-state linear model is estimated answering to what extent the sovereign credit risk is affected in between global and country-specific market variables and by credit ratings announcement changes. In broad strokes, the regime-switching analysis reveals that among domestic variables, it is the foreign exchange rate that affects the sovereign credit risk more in more volatile periods and among global variables, the indicators standing for global volatility risk premiums and international liquidity primarily influence the changes in the sovereign CDS spread in turbulent regimes whereas proxies for global risk free rate are significant more in tranquil regimes.

Regime switches in the risk-return trade-off

OpenAIRE

Marcellino, Massimiliano; Ghysels, Eric; Guerin, Pierre

2014-01-01

This paper deals with the estimation of the risk-return trade-off. We use a MIDAS model for the conditional variance and allow for possible switches in the risk-return relation through a Markov-switching specification. We find strong evidence for regime changes in the risk-return relation. This finding is robust to a large range of specifications. In the first regime characterized by low ex-post returns and high volatility, the risk-return relation is reversed, whereas the intuitive positive ...

Regime switching model for financial data: Empirical risk analysis

Science.gov (United States)

Salhi, Khaled; Deaconu, Madalina; Lejay, Antoine; Champagnat, Nicolas; Navet, Nicolas

2016-11-01

This paper constructs a regime switching model for the univariate Value-at-Risk estimation. Extreme value theory (EVT) and hidden Markov models (HMM) are combined to estimate a hybrid model that takes volatility clustering into account. In the first stage, HMM is used to classify data in crisis and steady periods, while in the second stage, EVT is applied to the previously classified data to rub out the delay between regime switching and their detection. This new model is applied to prices of numerous stocks exchanged on NYSE Euronext Paris over the period 2001-2011. We focus on daily returns for which calibration has to be done on a small dataset. The relative performance of the regime switching model is benchmarked against other well-known modeling techniques, such as stable, power laws and GARCH models. The empirical results show that the regime switching model increases predictive performance of financial forecasting according to the number of violations and tail-loss tests. This suggests that the regime switching model is a robust forecasting variant of power laws model while remaining practical to implement the VaR measurement.

Alternative Asymmetric Stochastic Volatility Models

NARCIS (Netherlands)

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

2010-01-01

textabstractThe stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is

On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree

International Nuclear Information System (INIS)

Charlot, Philippe; Marimoutou, Vêlayoudom

2014-01-01

This study examines the volatility and correlation and their relationships among the euro/US dollar exchange rates, the S and P500 equity indices, and the prices of WTI crude oil and the precious metals (gold, silver, and platinum) over the period 2005 to 2012. Our model links the univariate volatilities with the correlations via a hidden stochastic decision tree. The ensuing Hidden Markov Decision Tree (HMDT) model is in fact an extension of the Hidden Markov Model (HMM) introduced by Jordan et al. (1997). The architecture of this model is the opposite that of the classical deterministic approach based on a binary decision tree and, it allows a probabilistic vision of the relationship between univariate volatility and correlation. Our results are categorized into three groups, namely (1) exchange rates and oil, (2) S and P500 indices, and (3) precious metals. A switching dynamics is seen to characterize the volatilities, while, in the case of the correlations, the series switch from one regime to another, this movement touching a peak during the period of the Subprime crisis in the US, and again during the days following the Tohoku earthquake in Japan. Our findings show that the relationships between volatility and correlation are dependent upon the nature of the series considered, sometimes corresponding to those found in econometric studies, according to which correlation increases in bear markets, at other times differing from them. - Highlights: • This study examines the volatility and correlation and their relationships of precious metals and crude oil. • Our model links the univariate volatilities with the correlations via a hidden stochastic decision tree. • This model allows a probabilistic point of view of the relationship between univariate volatility and correlation. • Results show the relationships between volatility and correlation are dependent upon the nature of the series considered

Testing for Volatility Co-movement in Bivariate Stochastic Volatility Models

OpenAIRE

Chen, Jinghui; Kobayashi, Masahito; McAleer, Michael

2017-01-01

markdownabstractThe paper considers the problem of volatility co-movement, namely as to whether two financial returns have perfectly correlated common volatility process, in the framework of multivariate stochastic volatility models and proposes a test which checks the volatility co-movement. The proposed test is a stochastic volatility version of the co-movement test proposed by Engle and Susmel (1993), who investigated whether international equity markets have volatility co-movement using t...

Stochastic volatility models and Kelvin waves

Science.gov (United States)

Lipton, Alex; Sepp, Artur

2008-08-01

We use stochastic volatility models to describe the evolution of an asset price, its instantaneous volatility and its realized volatility. In particular, we concentrate on the Stein and Stein model (SSM) (1991) for the stochastic asset volatility and the Heston model (HM) (1993) for the stochastic asset variance. By construction, the volatility is not sign definite in SSM and is non-negative in HM. It is well known that both models produce closed-form expressions for the prices of vanilla option via the Lewis-Lipton formula. However, the numerical pricing of exotic options by means of the finite difference and Monte Carlo methods is much more complex for HM than for SSM. Until now, this complexity was considered to be an acceptable price to pay for ensuring that the asset volatility is non-negative. We argue that having negative stochastic volatility is a psychological rather than financial or mathematical problem, and advocate using SSM rather than HM in most applications. We extend SSM by adding volatility jumps and obtain a closed-form expression for the density of the asset price and its realized volatility. We also show that the current method of choice for solving pricing problems with stochastic volatility (via the affine ansatz for the Fourier-transformed density function) can be traced back to the Kelvin method designed in the 19th century for studying wave motion problems arising in fluid dynamics.

Stochastic volatility models and Kelvin waves

International Nuclear Information System (INIS)

Lipton, Alex; Sepp, Artur

2008-01-01

We use stochastic volatility models to describe the evolution of an asset price, its instantaneous volatility and its realized volatility. In particular, we concentrate on the Stein and Stein model (SSM) (1991) for the stochastic asset volatility and the Heston model (HM) (1993) for the stochastic asset variance. By construction, the volatility is not sign definite in SSM and is non-negative in HM. It is well known that both models produce closed-form expressions for the prices of vanilla option via the Lewis-Lipton formula. However, the numerical pricing of exotic options by means of the finite difference and Monte Carlo methods is much more complex for HM than for SSM. Until now, this complexity was considered to be an acceptable price to pay for ensuring that the asset volatility is non-negative. We argue that having negative stochastic volatility is a psychological rather than financial or mathematical problem, and advocate using SSM rather than HM in most applications. We extend SSM by adding volatility jumps and obtain a closed-form expression for the density of the asset price and its realized volatility. We also show that the current method of choice for solving pricing problems with stochastic volatility (via the affine ansatz for the Fourier-transformed density function) can be traced back to the Kelvin method designed in the 19th century for studying wave motion problems arising in fluid dynamics

Stochastic volatility models and Kelvin waves

Energy Technology Data Exchange (ETDEWEB)

Lipton, Alex [Merrill Lynch, Mlfc Main, 2 King Edward Street, London EC1A 1HQ (United Kingdom); Sepp, Artur [Merrill Lynch, 4 World Financial Center, New York, NY 10080 (United States)], E-mail: Alex_Lipton@ml.com, E-mail: Artur_Sepp@ml.com

2008-08-29

We use stochastic volatility models to describe the evolution of an asset price, its instantaneous volatility and its realized volatility. In particular, we concentrate on the Stein and Stein model (SSM) (1991) for the stochastic asset volatility and the Heston model (HM) (1993) for the stochastic asset variance. By construction, the volatility is not sign definite in SSM and is non-negative in HM. It is well known that both models produce closed-form expressions for the prices of vanilla option via the Lewis-Lipton formula. However, the numerical pricing of exotic options by means of the finite difference and Monte Carlo methods is much more complex for HM than for SSM. Until now, this complexity was considered to be an acceptable price to pay for ensuring that the asset volatility is non-negative. We argue that having negative stochastic volatility is a psychological rather than financial or mathematical problem, and advocate using SSM rather than HM in most applications. We extend SSM by adding volatility jumps and obtain a closed-form expression for the density of the asset price and its realized volatility. We also show that the current method of choice for solving pricing problems with stochastic volatility (via the affine ansatz for the Fourier-transformed density function) can be traced back to the Kelvin method designed in the 19th century for studying wave motion problems arising in fluid dynamics.

Inherent stochasticity of superconductor-resistor switching behavior in nanowires.

Science.gov (United States)

Shah, Nayana; Pekker, David; Goldbart, Paul M

2008-11-14

We study the stochastic dynamics of superconductive-resistive switching in hysteretic current-biased superconducting nanowires undergoing phase-slip fluctuations. We evaluate the mean switching time using the master-equation formalism, and hence obtain the distribution of switching currents. We find that as the temperature is reduced this distribution initially broadens; only at lower temperatures does it show the narrowing with cooling naively expected for phase slips that are thermally activated. We also find that although several phase-slip events are generally necessary to induce switching, there is an experimentally accessible regime of temperatures and currents for which just one single phase-slip event is sufficient to induce switching, via the local heating it causes.

American option pricing with stochastic volatility processes

Directory of Open Access Journals (Sweden)

Ping LI

2017-12-01

Full Text Available In order to solve the problem of option pricing more perfectly, the option pricing problem with Heston stochastic volatility model is considered. The optimal implementation boundary of American option and the conditions for its early execution are analyzed and discussed. In view of the fact that there is no analytical American option pricing formula, through the space discretization parameters, the stochastic partial differential equation satisfied by American options with Heston stochastic volatility is transformed into the corresponding differential equations, and then using high order compact finite difference method, numerical solutions are obtained for the option price. The numerical experiments are carried out to verify the theoretical results and simulation. The two kinds of optimal exercise boundaries under the conditions of the constant volatility and the stochastic volatility are compared, and the results show that the optimal exercise boundary also has stochastic volatility. Under the setting of parameters, the behavior and the nature of volatility are analyzed, the volatility curve is simulated, the calculation results of high order compact difference method are compared, and the numerical option solution is obtained, so that the method is verified. The research result provides reference for solving the problems of option pricing under stochastic volatility such as multiple underlying asset option pricing and barrier option pricing.

American options under stochastic volatility

NARCIS (Netherlands)

Chockalingam, A.; Muthuraman, K.

2011-01-01

The problem of pricing an American option written on an underlying asset with constant price volatility has been studied extensively in literature. Real-world data, however, demonstrate that volatility is not constant, and stochastic volatility models are used to account for dynamic volatility

Have East Asian stock markets calmed down? Evidence from a regime-switching model

NARCIS (Netherlands)

Chaudhuri, K.R.; Klaassen, F.

2001-01-01

The 1997-98 East Asian crisis was accompanied by high volatility of East Asian stock returns. This paper examines whether the volatility has already come down to the level of the years before the crisis. We use a regime-switching model to account for possible structural change in the unconditional

Portfolio Optimization: A Combined Regime-Switching and Black–Litterman Model

OpenAIRE

Edwin O. Fischer; Immanuel Seidl

2013-01-01

Traditionally portfolios are optimized with the single-regime Markowitz model using the volatility as the risk measure and the historical return as the expected return. This study shows the effects that a regime-switching framework and alternative risk measures (modified value at risk and conditional value at risk) and return measures (CAPM estimates and Black–Litterman estimates) have on the asset allocation and on the absolute and relative performance of portfolios. It demonstrates that the...

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...

Pricing long-dated insurance contracts with stochastic interest rates and stochastic volatility

NARCIS (Netherlands)

van Haastrecht, A.; Lord, R.; Pelsser, A.; Schrager, D.

2009-01-01

We consider the pricing of long-dated insurance contracts under stochastic interest rates and stochastic volatility. In particular, we focus on the valuation of insurance options with long-term equity or foreign exchange exposures. Our modeling framework extends the stochastic volatility model of

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.

The multivariate supOU stochastic volatility model

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole; Stelzer, Robert

Using positive semidefinite supOU (superposition of Ornstein-Uhlenbeck type) processes to describe the volatility, we introduce a multivariate stochastic volatility model for financial data which is capable of modelling long range dependence effects. The finiteness of moments and the second order...... structure of the volatility, the log returns, as well as their "squares" are discussed in detail. Moreover, we give several examples in which long memory effects occur and study how the model as well as the simple Ornstein-Uhlenbeck type stochastic volatility model behave under linear transformations....... In particular, the models are shown to be preserved under invertible linear transformations. Finally, we discuss how (sup)OU stochastic volatility models can be combined with a factor modelling approach....

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...

CAM Stochastic Volatility Model for Option Pricing

Directory of Open Access Journals (Sweden)

Wanwan Huang

2016-01-01

Full Text Available The coupled additive and multiplicative (CAM noises model is a stochastic volatility model for derivative pricing. Unlike the other stochastic volatility models in the literature, the CAM model uses two Brownian motions, one multiplicative and one additive, to model the volatility process. We provide empirical evidence that suggests a nontrivial relationship between the kurtosis and skewness of asset prices and that the CAM model is able to capture this relationship, whereas the traditional stochastic volatility models cannot. We introduce a control variate method and Monte Carlo estimators for some of the sensitivities (Greeks of the model. We also derive an approximation for the characteristic function of the model.

A Fractionally Integrated Wishart Stochastic Volatility Model

NARCIS (Netherlands)

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

2013-01-01

textabstractThere has recently been growing interest in modeling and estimating alternative continuous time multivariate stochastic volatility models. We propose a continuous time fractionally integrated Wishart stochastic volatility (FIWSV) process. We derive the conditional Laplace transform of

Testing for Volatility Co-movement in Bivariate Stochastic Volatility Models

NARCIS (Netherlands)

J. Chen (Jinghui); M. Kobayashi (Masahito); M.J. McAleer (Michael)

2017-01-01

markdownabstractThe paper considers the problem of volatility co-movement, namely as to whether two financial returns have perfectly correlated common volatility process, in the framework of multivariate stochastic volatility models and proposes a test which checks the volatility co-movement. The

Investment timing under hybrid stochastic and local volatility

International Nuclear Information System (INIS)

Kim, Jeong-Hoon; Lee, Min-Ku; Sohn, So Young

2014-01-01

Highlights: • The effects of hybrid stochastic volatility on real option prices are studied. • The stochastic volatility consists of a fast mean-reverting component and a CEV type one. • A fast mean-reverting factor lowers real option prices and investment thresholds. • The increase of elasticity raises real option prices and investment thresholds. • The effects of the addition of a slowly varying factor depend upon the project value. - Abstract: We consider an investment timing problem under a real option model where the instantaneous volatility of the project value is given by a combination of a hidden stochastic process and the project value itself. The stochastic volatility part is given by a function of a fast mean-reverting process as well as a slowly varying process and the local volatility part is a power (the elasticity parameter) of the project value itself. The elasticity parameter controls directly the correlation between the project value and the volatility. Knowing that the project value represents the market price of a real asset in many applications and the value of the elasticity parameter depends on the asset, the elasticity parameter should be treated with caution for investment decision problems. Based on the hybrid structure of volatility, we investigate the simultaneous impact of the elasticity and the stochastic volatility on the real option value as well as the investment threshold

Portfolio Optimization with Stochastic Dividends and Stochastic Volatility

Science.gov (United States)

Varga, Katherine Yvonne

2015-01-01

We consider an optimal investment-consumption portfolio optimization model in which an investor receives stochastic dividends. As a first problem, we allow the drift of stock price to be a bounded function. Next, we consider a stochastic volatility model. In each problem, we use the dynamic programming method to derive the Hamilton-Jacobi-Bellman…

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...

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.

Testing for regime-switching CAPM on Zagreb Stock Exchange

Directory of Open Access Journals (Sweden)

Tihana Škrinjarić

2014-12-01

Full Text Available The standard Capital Asset Pricing Model assumes that a linear relationship exists between the risk (beta and the expected excess return of a stock. However, empirical findings have shown over the years that this relationship varies over time. Stock markets undergo phases of greater and smaller volatility in which beta varies accordingly (undergoes different regimes. Given that the Croatian capital market is still insufficiently investigated, the aim of this paper is to explore the possibility of a non-linear relationship between the stock risk and return. Linear and Markov-switching models (Hamilton 1989 are examined on the Zagreb Stock Exchange based on monthly data on 21 stocks, ranging from January 2005 to December 2013. In that way, investors can use the results based on the best model when making decisions about buying stocks. Since this is one of the first papers on regime-switching on the Croatian capital market, it will hopefully contribute to the existing literature on investing.

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.

Stochastic switching in biology: from genotype to phenotype

International Nuclear Information System (INIS)

Bressloff, Paul C

2017-01-01

There has been a resurgence of interest in non-equilibrium stochastic processes in recent years, driven in part by the observation that the number of molecules (genes, mRNA, proteins) involved in gene expression are often of order 1–1000. This means that deterministic mass-action kinetics tends to break down, and one needs to take into account the discrete, stochastic nature of biochemical reactions. One of the major consequences of molecular noise is the occurrence of stochastic biological switching at both the genotypic and phenotypic levels. For example, individual gene regulatory networks can switch between graded and binary responses, exhibit translational/transcriptional bursting, and support metastability (noise-induced switching between states that are stable in the deterministic limit). If random switching persists at the phenotypic level then this can confer certain advantages to cell populations growing in a changing environment, as exemplified by bacterial persistence in response to antibiotics. Gene expression at the single-cell level can also be regulated by changes in cell density at the population level, a process known as quorum sensing. In contrast to noise-driven phenotypic switching, the switching mechanism in quorum sensing is stimulus-driven and thus noise tends to have a detrimental effect. A common approach to modeling stochastic gene expression is to assume a large but finite system and to approximate the discrete processes by continuous processes using a system-size expansion. However, there is a growing need to have some familiarity with the theory of stochastic processes that goes beyond the standard topics of chemical master equations, the system-size expansion, Langevin equations and the Fokker–Planck equation. Examples include stochastic hybrid systems (piecewise deterministic Markov processes), large deviations and the Wentzel–Kramers–Brillouin (WKB) method, adiabatic reductions, and queuing/renewal theory. The major aim of

The effects of crude oil shocks on stock market shifts behaviour A regime switching approach

Energy Technology Data Exchange (ETDEWEB)

Aloui, Chaker; Jammazi, Rania [International Finance Group-Tunisia, Faculty of Management and Economic Sciences of Tunis, Boulevard du 7 novembre, El Manar University, B.P. 248, C.P. 2092, Tunis Cedex (Tunisia)

2009-09-15

In this paper we develop a two regime Markov-switching EGARCH model introduced by Henry [Henry, O., 2009. Regime switching in the relationship between equity returns and short-term interest rates. Journal of Banking and Finance 33, 405-414.] to examine the relationship between crude oil shocks and stock markets. An application to stock markets of UK, France and Japan over the sample period January 1989 to December 2007 illustrates plausible results. We detect two episodes of series behaviour one relative to low mean/high variance regime and the other to high mean/low variance regime. Furthermore, there is evidence that common recessions coincide with the low mean/high variance regime. In addition, we allow both real stock returns and probability of transitions from one regime to another to depend on the net oil price increase variable. The findings show that rises in oil price has a significant role in determining both the volatility of stock returns and the probability of transition across regimes. (author)

The effects of crude oil shocks on stock market shifts behaviour A regime switching approach

International Nuclear Information System (INIS)

Aloui, Chaker; Jammazi, Rania

2009-01-01

In this paper we develop a two regime Markov-switching EGARCH model introduced by Henry [Henry, O., 2009. Regime switching in the relationship between equity returns and short-term interest rates. Journal of Banking and Finance 33, 405-414.] to examine the relationship between crude oil shocks and stock markets. An application to stock markets of UK, France and Japan over the sample period January 1989 to December 2007 illustrates plausible results. We detect two episodes of series behaviour one relative to low mean/high variance regime and the other to high mean/low variance regime. Furthermore, there is evidence that common recessions coincide with the low mean/high variance regime. In addition, we allow both real stock returns and probability of transitions from one regime to another to depend on the net oil price increase variable. The findings show that rises in oil price has a significant role in determining both the volatility of stock returns and the probability of transition across regimes. (author)

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....

The impact of macroeconomic and conventional stock market variables on Islamic index returns under regime switching

Directory of Open Access Journals (Sweden)

Slah Bahloul

2017-03-01

Full Text Available The objective of this paper is to study the impact of conventional stock market return and volatility and various macroeconomic variables (including inflation rate, short-term interest rate, the slope of the yield curve and money supply on Islamic stock markets returns for twenty developed and emerging markets using Markov switching regression models. The empirical results for the period 2002–2014 show that both developed and emerging Islamic stock indices are influenced by conventional stock indices returns and money supply for both the low and high volatility regimes. However, the other macroeconomic variables fail to explain the dynamics of Islamic stock indices especially in the high volatility regime. Similar conclusions are obtained by using the MS-VAR model.

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.

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 ...

Distributed Consensus of Stochastic Delayed Multi-agent Systems Under Asynchronous Switching.

Science.gov (United States)

Wu, Xiaotai; Tang, Yang; Cao, Jinde; Zhang, Wenbing

2016-08-01

In this paper, the distributed exponential consensus of stochastic delayed multi-agent systems with nonlinear dynamics is investigated under asynchronous switching. The asynchronous switching considered here is to account for the time of identifying the active modes of multi-agent systems. After receipt of confirmation of mode's switching, the matched controller can be applied, which means that the switching time of the matched controller in each node usually lags behind that of system switching. In order to handle the coexistence of switched signals and stochastic disturbances, a comparison principle of stochastic switched delayed systems is first proved. By means of this extended comparison principle, several easy to verified conditions for the existence of an asynchronously switched distributed controller are derived such that stochastic delayed multi-agent systems with asynchronous switching and nonlinear dynamics can achieve global exponential consensus. Two examples are given to illustrate the effectiveness of the proposed method.

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...

The stochastic behavior of a molecular switching circuit with feedback

Directory of Open Access Journals (Sweden)

Smith Eric

2007-05-01

Full Text Available Abstract Background Using a statistical physics approach, we study the stochastic switching behavior of a model circuit of multisite phosphorylation and dephosphorylation with feedback. The circuit consists of a kinase and phosphatase acting on multiple sites of a substrate that, contingent on its modification state, catalyzes its own phosphorylation and, in a symmetric scenario, dephosphorylation. The symmetric case is viewed as a cartoon of conflicting feedback that could result from antagonistic pathways impinging on the state of a shared component. Results Multisite phosphorylation is sufficient for bistable behavior under feedback even when catalysis is linear in substrate concentration, which is the case we consider. We compute the phase diagram, fluctuation spectrum and large-deviation properties related to switch memory within a statistical mechanics framework. Bistability occurs as either a first-order or second-order non-equilibrium phase transition, depending on the network symmetries and the ratio of phosphatase to kinase numbers. In the second-order case, the circuit never leaves the bistable regime upon increasing the number of substrate molecules at constant kinase to phosphatase ratio. Conclusion The number of substrate molecules is a key parameter controlling both the onset of the bistable regime, fluctuation intensity, and the residence time in a switched state. The relevance of the concept of memory depends on the degree of switch symmetry, as memory presupposes information to be remembered, which is highest for equal residence times in the switched states. Reviewers This article was reviewed by Artem Novozhilov (nominated by Eugene Koonin, Sergei Maslov, and Ned Wingreen.

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...

Modeling and forecasting of wind power generation - Regime-switching approaches

DEFF Research Database (Denmark)

Trombe, Pierre-Julien

The present thesis addresses a number of challenges emerging from the increasing penetration of renewable energy sources into power systems. Focus is placed on wind energy and large-scale offshore wind farms. Indeed, offshore wind power variability is becoming a serious obstacle to the integration...... of more renewable energy into power systems since these systems are subjected to maintain a strict balance between electricity consumption and production, at any time. For this purpose, wind power forecasts offer an essential support to power system operators. In particular, there is a growing demand...... case study is the Horns Rev wind farm located in the North Sea. Regime-switching aspects of offshore wind power fluctuations are investigated. Several formulations of Markov-Switching models are proposed in order to better characterize the stochastic behavior of the underlying process and improve its...

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.

Time varying moments, regime switch, and crisis warning: The birth-death process with changing transition probability

Science.gov (United States)

Tang, Yinan; Chen, Ping

2014-06-01

The sub-prime crisis in the U.S. reveals the limitation of diversification strategy based on mean-variance analysis. A regime switch and a turning point can be observed using a high moment representation and time-dependent transition probability. Up-down price movements are induced by interactions among agents, which can be described by the birth-death (BD) process. Financial instability is visible by dramatically increasing 3rd to 5th moments one-quarter before and during the crisis. The sudden rising high moments provide effective warning signals of a regime-switch or a coming crisis. The critical condition of a market breakdown can be identified from nonlinear stochastic dynamics. The master equation approach of population dynamics provides a unified theory of a calm and turbulent market.

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.

Stochastic dynamics of resistive switching: fluctuations lead to optimal particle number

International Nuclear Information System (INIS)

Radtke, Paul K; Schimansky-Geier, Lutz; Hazel, Andrew L; Straube, Arthur V

2017-01-01

Resistive switching (RS) is one of the foremost candidates for building novel types of non-volatile random access memories. Any practical implementation of such a memory cell calls for a strong miniaturization, at which point fluctuations start playing a role that cannot be neglected. A detailed understanding of switching mechanisms and reliability is essential. For this reason, we formulate a particle model based on the stochastic motion of oxygen vacancies. It allows us to investigate fluctuations in the resistance states of a switch with two active zones. The vacancies’ dynamics are governed by a master equation. Upon the application of a voltage pulse, the vacancies travel collectively through the switch. By deriving a generalized Burgers equation we can interpret this collective motion as nonlinear traveling waves, and numerically verify this result. Further, we define binary logical states by means of the underlying vacancy distributions, and establish a framework of writing and reading such memory element with voltage pulses. Considerations about the discriminability of these operations under fluctuations together with the markedness of the RS effect itself lead to the conclusion, that an intermediate vacancy number is optimal for performance. (paper)

Stochastic dynamics of resistive switching: fluctuations lead to optimal particle number

Science.gov (United States)

Radtke, Paul K.; Hazel, Andrew L.; Straube, Arthur V.; Schimansky-Geier, Lutz

2017-09-01

Resistive switching (RS) is one of the foremost candidates for building novel types of non-volatile random access memories. Any practical implementation of such a memory cell calls for a strong miniaturization, at which point fluctuations start playing a role that cannot be neglected. A detailed understanding of switching mechanisms and reliability is essential. For this reason, we formulate a particle model based on the stochastic motion of oxygen vacancies. It allows us to investigate fluctuations in the resistance states of a switch with two active zones. The vacancies’ dynamics are governed by a master equation. Upon the application of a voltage pulse, the vacancies travel collectively through the switch. By deriving a generalized Burgers equation we can interpret this collective motion as nonlinear traveling waves, and numerically verify this result. Further, we define binary logical states by means of the underlying vacancy distributions, and establish a framework of writing and reading such memory element with voltage pulses. Considerations about the discriminability of these operations under fluctuations together with the markedness of the RS effect itself lead to the conclusion, that an intermediate vacancy number is optimal for performance.

Pricing Exotic Options under a High-Order Markovian Regime Switching Model

Directory of Open Access Journals (Sweden)

Wai-Ki Ching

2007-10-01

Full Text Available We consider the pricing of exotic options when the price dynamics of the underlying risky asset are governed by a discrete-time Markovian regime-switching process driven by an observable, high-order Markov model (HOMM. We assume that the market interest rate, the drift, and the volatility of the underlying risky asset's return switch over time according to the states of the HOMM, which are interpreted as the states of an economy. We will then employ the well-known tool in actuarial science, namely, the Esscher transform to determine an equivalent martingale measure for option valuation. Moreover, we will also investigate the impact of the high-order effect of the states of the economy on the prices of some path-dependent exotic options, such as Asian options, lookback options, and barrier options.

Stochastic multistep polarization switching in ferroelectrics

Science.gov (United States)

Genenko, Y. A.; Khachaturyan, R.; Schultheiß, J.; Ossipov, A.; Daniels, J. E.; Koruza, J.

2018-04-01

Consecutive stochastic 90° polarization switching events, clearly resolved in recent experiments, are described by a nucleation and growth multistep model. It extends the classical Kolmogorov-Avrami-Ishibashi approach and includes possible consecutive 90°- and parallel 180° switching events. The model predicts the results of simultaneous time-resolved macroscopic measurements of polarization and strain, performed on a tetragonal Pb (Zr ,Ti ) O3 ceramic in a wide range of electric fields over a time domain of seven orders of magnitude. It allows the determination of the fractions of individual switching processes, their characteristic switching times, activation fields, and respective Avrami indices.

Stochastic dynamical models for ecological regime shifts

DEFF Research Database (Denmark)

Møller, Jan Kloppenborg; Carstensen, Jacob; Madsen, Henrik

the physical and biological knowledge of the system, and nonlinearities introduced here can generate regime shifts or enhance the probability of regime shifts in the case of stochastic models, typically characterized by a threshold value for the known driver. A simple model for light competition between...... definition and stability of regimes become less subtle. Ecological regime shifts and their modeling must be viewed in a probabilistic manner, particularly if such model results are to be used in ecosystem management....

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.

Regime-Switching Risk: To Price or Not to Price?

Directory of Open Access Journals (Sweden)

Tak Kuen Siu

2011-01-01

“normative” issues to be addressed in pricing contingent claims under a Markovian, regime-switching, Black-Scholes-Merton model. We address this issue using a minimal relative entropy approach. Firstly, we apply a martingale representation for a double martingale to characterize the canonical space of equivalent martingale measures which may be viewed as the largest space of equivalent martingale measures to incorporate both the diffusion risk and the regime-switching risk. Then we show that an optimal equivalent martingale measure over the canonical space selected by minimizing the relative entropy between an equivalent martingale measure and the real-world probability measure does not price the regime-switching risk. The optimal measure also justifies the use of the Esscher transform for option valuation in the regime-switching market.

Portfolio Selection with Jumps under Regime Switching

Directory of Open Access Journals (Sweden)

Lin Zhao

2010-01-01

Full Text Available We investigate a continuous-time version of the mean-variance portfolio selection model with jumps under regime switching. The portfolio selection is proposed and analyzed for a market consisting of one bank account and multiple stocks. The random regime switching is assumed to be independent of the underlying Brownian motion and jump processes. A Markov chain modulated diffusion formulation is employed to model the problem.

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)

Asset allocation and regime switching on Croatian financial market

Directory of Open Access Journals (Sweden)

Tihana Škrinjarić

2016-12-01

Full Text Available It has been known for quite some time now that financial markets exhibit changes in regimes over time. A majority of the literature tends to support that financial markets undergo regimes of bull and bear markets. This characteristic should be modeled in a proper way as investors are always interested in beating the market: either by achieving better returns than others, or by minimizing their portfolio risks. There exist many mathematical and statistical models that are used as tools to achieve the mentioned goals. Introducing the regime switching methodology in existing models has proven to be facilitate achieving such goals. Therefore, the objective of this study is to utilize the regime switching methodology on the Croatian financial market to ascertain its usefulness for Croatian investors. Multivariate regime switching and non-switching models were estimated using daily data from the period 2 January 2007 to 31 December 2015. The assumption is that the investor is interested in stock and bond markets. The results from the MGARCH and regime switching MGARCH models are then compared in order to give answers as to whether the respective methodology applied to the Croatian market is useful and how it may benefit investors. Most of the results support the presumption of incorporating this particular methodology in financial modeling for the Croatia markets. This is the first research that applies the regime switching MGARCH methodology in Croatia (including the Balkan region, hence we expect that this will be a significant contribution to existing methodologies in literature.

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

Stochastic Parametrisations and Regime Behaviour of Atmospheric Models

Science.gov (United States)

Arnold, Hannah; Moroz, Irene; Palmer, Tim

2013-04-01

The presence of regimes is a characteristic of non-linear, chaotic systems (Lorenz, 2006). In the atmosphere, regimes emerge as familiar circulation patterns such as the El-Nino Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO) and Scandinavian Blocking events. In recent years there has been much interest in the problem of identifying and studying atmospheric regimes (Solomon et al, 2007). In particular, how do these regimes respond to an external forcing such as anthropogenic greenhouse gas emissions? The importance of regimes in observed trends over the past 50-100 years indicates that in order to predict anthropogenic climate change, our climate models must be able to represent accurately natural circulation regimes, their statistics and variability. It is well established that representing model uncertainty as well as initial condition uncertainty is important for reliable weather forecasts (Palmer, 2001). In particular, stochastic parametrisation schemes have been shown to improve the skill of weather forecast models (e.g. Berner et al., 2009; Frenkel et al., 2012; Palmer et al., 2009). It is possible that including stochastic physics as a representation of model uncertainty could also be beneficial in climate modelling, enabling the simulator to explore larger regions of the climate attractor including other flow regimes. An alternative representation of model uncertainty is a perturbed parameter scheme, whereby physical parameters in subgrid parametrisation schemes are perturbed about their optimal value. Perturbing parameters gives a greater control over the ensemble than multi-model or multiparametrisation ensembles, and has been used as a representation of model uncertainty in climate prediction (Stainforth et al., 2005; Rougier et al., 2009). We investigate the effect of including representations of model uncertainty on the regime behaviour of a simulator. A simple chaotic model of the atmosphere, the Lorenz '96 system, is used to study

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

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

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...

Population density approach for discrete mRNA distributions in generalized switching models for stochastic gene expression.

Science.gov (United States)

Stinchcombe, Adam R; Peskin, Charles S; Tranchina, Daniel

2012-06-01

We present a generalization of a population density approach for modeling and analysis of stochastic gene expression. In the model, the gene of interest fluctuates stochastically between an inactive state, in which transcription cannot occur, and an active state, in which discrete transcription events occur; and the individual mRNA molecules are degraded stochastically in an independent manner. This sort of model in simplest form with exponential dwell times has been used to explain experimental estimates of the discrete distribution of random mRNA copy number. In our generalization, the random dwell times in the inactive and active states, T_{0} and T_{1}, respectively, are independent random variables drawn from any specified distributions. Consequently, the probability per unit time of switching out of a state depends on the time since entering that state. Our method exploits a connection between the fully discrete random process and a related continuous process. We present numerical methods for computing steady-state mRNA distributions and an analytical derivation of the mRNA autocovariance function. We find that empirical estimates of the steady-state mRNA probability mass function from Monte Carlo simulations of laboratory data do not allow one to distinguish between underlying models with exponential and nonexponential dwell times in some relevant parameter regimes. However, in these parameter regimes and where the autocovariance function has negative lobes, the autocovariance function disambiguates the two types of models. Our results strongly suggest that temporal data beyond the autocovariance function is required in general to characterize gene switching.

Mean Square Exponential Stability of Stochastic Switched System with Interval Time-Varying Delays

Directory of Open Access Journals (Sweden)

Manlika Rajchakit

2012-01-01

Full Text Available This paper is concerned with mean square exponential stability of switched stochastic system with interval time-varying delays. The time delay is any continuous function belonging to a given interval, but not necessary to be differentiable. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton’s formula, a switching rule for the mean square exponential stability of switched stochastic system with interval time-varying delays and new delay-dependent sufficient conditions for the mean square exponential stability of the switched stochastic system are first established in terms of LMIs. Numerical example is given to show the effectiveness of the obtained result.

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.

Optimal control of switching time in switched stochastic systems with multi-switching times and different costs

Science.gov (United States)

Liu, Xiaomei; Li, Shengtao; Zhang, Kanjian

2017-08-01

In this paper, we solve an optimal control problem for a class of time-invariant switched stochastic systems with multi-switching times, where the objective is to minimise a cost functional with different costs defined on the states. In particular, we focus on problems in which a pre-specified sequence of active subsystems is given and the switching times are the only control variables. Based on the calculus of variation, we derive the gradient of the cost functional with respect to the switching times on an especially simple form, which can be directly used in gradient descent algorithms to locate the optimal switching instants. Finally, a numerical example is given, highlighting the validity of the proposed methodology.

Representing Sudden Shifts in Intensive Dyadic Interaction Data Using Differential Equation Models with Regime Switching.

Science.gov (United States)

Chow, Sy-Miin; Ou, Lu; Ciptadi, Arridhana; Prince, Emily B; You, Dongjun; Hunter, Michael D; Rehg, James M; Rozga, Agata; Messinger, Daniel S

2018-06-01

A growing number of social scientists have turned to differential equations as a tool for capturing the dynamic interdependence among a system of variables. Current tools for fitting differential equation models do not provide a straightforward mechanism for diagnosing evidence for qualitative shifts in dynamics, nor do they provide ways of identifying the timing and possible determinants of such shifts. In this paper, we discuss regime-switching differential equation models, a novel modeling framework for representing abrupt changes in a system of differential equation models. Estimation was performed by combining the Kim filter (Kim and Nelson State-space models with regime switching: classical and Gibbs-sampling approaches with applications, MIT Press, Cambridge, 1999) and a numerical differential equation solver that can handle both ordinary and stochastic differential equations. The proposed approach was motivated by the need to represent discrete shifts in the movement dynamics of [Formula: see text] mother-infant dyads during the Strange Situation Procedure (SSP), a behavioral assessment where the infant is separated from and reunited with the mother twice. We illustrate the utility of a novel regime-switching differential equation model in representing children's tendency to exhibit shifts between the goal of staying close to their mothers and intermittent interest in moving away from their mothers to explore the room during the SSP. Results from empirical model fitting were supplemented with a Monte Carlo simulation study to evaluate the use of information criterion measures to diagnose sudden shifts in dynamics.

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)

Stabilization Strategies of Supply Networks with Stochastic Switched Topology

Directory of Open Access Journals (Sweden)

Shukai Li

2013-01-01

Full Text Available In this paper, a dynamical supply networks model with stochastic switched topology is presented, in which the stochastic switched topology is dependent on a continuous time Markov process. The goal is to design the state-feedback control strategies to stabilize the dynamical supply networks. Based on Lyapunov stability theory, sufficient conditions for the existence of state feedback control strategies are given in terms of matrix inequalities, which ensure the robust stability of the supply networks at the stationary states and a prescribed H∞ disturbance attenuation level with respect to the uncertain demand. A numerical example is given to illustrate the effectiveness of the proposed method.

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

Analysis of novel stochastic switched SILI epidemic models with continuous and impulsive control

Science.gov (United States)

Gao, Shujing; Zhong, Deming; Zhang, Yan

2018-04-01

In this paper, we establish two new stochastic switched epidemic models with continuous and impulsive control. The stochastic perturbations are considered for the natural death rate in each equation of the models. Firstly, a stochastic switched SILI model with continuous control schemes is investigated. By using Lyapunov-Razumikhin method, the sufficient conditions for extinction in mean are established. Our result shows that the disease could be die out theoretically if threshold value R is less than one, regardless of whether the disease-free solutions of the corresponding subsystems are stable or unstable. Then, a stochastic switched SILI model with continuous control schemes and pulse vaccination is studied. The threshold value R is derived. The global attractivity of the model is also obtained. At last, numerical simulations are carried out to support our results.

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.

Partial Finite-Time Synchronization of Switched Stochastic Chua's Circuits via Sliding-Mode Control

Directory of Open Access Journals (Sweden)

Zhang-Lin Wan

2011-01-01

Full Text Available This paper considers the problem of partial finite-time synchronization between switched stochastic Chua's circuits accompanied by a time-driven switching law. Based on the Ito formula and Lyapunov stability theory, a sliding-mode controller is developed to guarantee the synchronization of switched stochastic master-slave Chua's circuits and for the mean of error states to obtain the partial finite-time stability. Numerical simulations demonstrate the effectiveness of the proposed methods.

Dynamics of bound vector solitons induced by stochastic perturbations: Soliton breakup and soliton switching

International Nuclear Information System (INIS)

Sun, Zhi-Yuan; Gao, Yi-Tian; Yu, Xin; Liu, Ying

2013-01-01

We respectively investigate breakup and switching of the Manakov-typed bound vector solitons (BVSs) induced by two types of stochastic perturbations: the homogenous and nonhomogenous. Symmetry-recovering is discovered for the asymmetrical homogenous case, while soliton switching is found to relate with the perturbation amplitude and soliton coherence. Simulations show that soliton switching in the circularly-polarized light system is much weaker than that in the Manakov and linearly-polarized systems. In addition, the homogenous perturbations can enhance the soliton switching in both of the Manakov and non-integrable (linearly- and circularly-polarized) systems. Our results might be helpful in interpreting dynamics of the BVSs with stochastic noises in nonlinear optics or with stochastic quantum fluctuations in Bose–Einstein condensates.

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.

A Class of Stochastic Hybrid Systems with State-Dependent Switching Noise

DEFF Research Database (Denmark)

Leth, John-Josef; Rasmussen, Jakob Gulddahl; Schiøler, Henrik

2012-01-01

In this paper, we develop theoretical results based on a proposed method for modeling switching noise for a class of hybrid systems with piecewise linear partitioned state space, and state-depending switching. We devise a stochastic model of such systems, whose global dynamics is governed...

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

Analysis of dynamic regimes in stochastically forced Kaldor model

International Nuclear Information System (INIS)

Bashkirtseva, Irina; Ryazanova, Tatyana; Ryashko, Lev

2015-01-01

We consider the business cycle Kaldor model forced by random noise. Detailed parametric analysis of deterministic system is carried out and zones of coexisting stable equilibrium and stable limit cycle are found. Noise-induced transitions between these attractors are studied using stochastic sensitivity function technique and confidence domains method. Critical values of noise intensity corresponding to noise-induced transitions “equilibrium → cycle” and “cycle → equilibrium” are estimated. Dominants in combined stochastic regimes are discussed.

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.

Phenotypic switching of populations of cells in a stochastic environment

Science.gov (United States)

Hufton, Peter G.; Lin, Yen Ting; Galla, Tobias

2018-02-01

In biology phenotypic switching is a common bet-hedging strategy in the face of uncertain environmental conditions. Existing mathematical models often focus on periodically changing environments to determine the optimal phenotypic response. We focus on the case in which the environment switches randomly between discrete states. Starting from an individual-based model we derive stochastic differential equations to describe the dynamics, and obtain analytical expressions for the mean instantaneous growth rates based on the theory of piecewise-deterministic Markov processes. We show that optimal phenotypic responses are non-trivial for slow and intermediate environmental processes, and systematically compare the cases of periodic and random environments. The best response to random switching is more likely to be heterogeneity than in the case of deterministic periodic environments, net growth rates tend to be higher under stochastic environmental dynamics. The combined system of environment and population of cells can be interpreted as host-pathogen interaction, in which the host tries to choose environmental switching so as to minimise growth of the pathogen, and in which the pathogen employs a phenotypic switching optimised to increase its growth rate. We discuss the existence of Nash-like mutual best-response scenarios for such host-pathogen games.

The causal nexus between oil prices and equity market in the U.S.: A regime switching model

International Nuclear Information System (INIS)

Balcilar, Mehmet; Ozdemir, Zeynel Abidin

2013-01-01

The aim of this paper is to analyse the causal link between monthly oil futures price changes and a sub-grouping of S and P 500 stock index changes. The causal linkage between oil and stock markets is modelled using a vector autoregressive model with time-varying parameters so as to reflect changes in Granger causality over time. A Markov switching vector autoregressive (MS-VAR) model, in which causal link between the series is stochastic and governed by an unobservable Markov chain, is used for inferring time-varying causality. Although we do not find any lead–lag type Granger causality, the results based on the MS-VAR model clearly show that oil futures price has strong regime prediction power for a sub-grouping of S and P 500 stock index during various sub-periods in the sample, while there is a weak evidence for the regime prediction power of a sub-grouping of S and P 500 stock indexes. The regime-prediction non-causality tests on the MS-VAR model show that both variables are useful for making inference about the regime process and that the evidence on regime-prediction causality is primarily found in the equation describing a sub-grouping of S and P 500 stock market returns. The evidence from the conditional non-causality tests shows that past information on the other series fails to improve the one step ahead prediction for both oil futures and stock returns. - Highlights: • We analyse the causal links between oil futures price and a sub-grouping of S and P 500 index. • The causal links are modelled using a regime switching model. • We do not find any lead–lag type Granger causality between the series. • The results show that oil futures price has regime prediction power for a sub-grouping of S and P 500 stock index

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

Regime-switching models to study psychological process

NARCIS (Netherlands)

Hamaker, E.L.; Grasman, R.P.P.P.; Kamphuis, J.H.

2010-01-01

Many psychological processes are characterized by recurrent shifts between different states. To model these processes at the level of the individual, regime-switching models may prove useful. In this chapter we discuss two of these models: the threshold autoregressive model and the Markov

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.

Floating Exchange Rate Regime

OpenAIRE

Quader, Syed Manzur

2004-01-01

In recent years, many developing countries having a history of high inflation, unfavorable balance of payment situation and a high level of foreign currencies denominated debt, have switched or are in the process of switching to a more flexible exchange rate regime. Therefore, the stability of the exchange rate and the dynamics of its volatility are more crucial than before to prevent financial crises and macroeconomic disturbances. This paper is designed to find out the reasons behind Bangla...

INFLUENCE OF REGIME SWITCHING TO RISK IN PORT-MODERN PORTFOLIO MANAGEMENT

OpenAIRE

Cristina Geambaşu; Liviu Geambaşu; Iulia Jianu

2013-01-01

The present financial crises determines an increase in analysing the application of regime switching over portfolio investments. We applied the switching regimes to measurement of risk as presented in post-modern portfolio management theory. Post-modern portfolio theory include investor’s tendency to measure risk as the chance to obtain from the investment performed a return lower than the minimum expected by him. The investor, as presented by behavioural finance, is more concerned about his ...

A regime-switching stochastic volatility model for forecasting electricity prices

DEFF Research Database (Denmark)

Exterkate, Peter; Knapik, Oskar

In a recent review paper, Weron (2014) pinpoints several crucial challenges outstanding in the area of electricity price forecasting. This research attempts to address all of them by i) showing the importance of considering fundamental price drivers in modeling, ii) developing new techniques for ...... on explanatory variables. Bayesian inference is explored in order to obtain predictive densities. The main focus of the paper is on shorttime density forecasting in Nord Pool intraday market. We show that the proposed model outperforms several benchmark models at this task....

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.

Adaptive Asymptotical Synchronization for Stochastic Complex Networks with Time-Delay and Markovian Switching

Directory of Open Access Journals (Sweden)

Xueling Jiang

2014-01-01

Full Text Available The problem of adaptive asymptotical synchronization is discussed for the stochastic complex dynamical networks with time-delay and Markovian switching. By applying the stochastic analysis approach and the M-matrix method for stochastic complex networks, several sufficient conditions to ensure adaptive asymptotical synchronization for stochastic complex networks are derived. Through the adaptive feedback control techniques, some suitable parameters update laws are obtained. Simulation result is provided to substantiate the effectiveness and characteristics of the proposed approach.

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

Carbon nanotube network-silicon oxide non-volatile switches.

Science.gov (United States)

Liao, Albert D; Araujo, Paulo T; Xu, Runjie; Dresselhaus, Mildred S

2014-12-08

The integration of carbon nanotubes with silicon is important for their incorporation into next-generation nano-electronics. Here we demonstrate a non-volatile switch that utilizes carbon nanotube networks to electrically contact a conductive nanocrystal silicon filament in silicon dioxide. We form this device by biasing a nanotube network until it physically breaks in vacuum, creating the conductive silicon filament connected across a small nano-gap. From Raman spectroscopy, we observe coalescence of nanotubes during breakdown, which stabilizes the system to form very small gaps in the network~15 nm. We report that carbon nanotubes themselves are involved in switching the device to a high resistive state. Calculations reveal that this switching event occurs at ~600 °C, the temperature associated with the oxidation of nanotubes. Therefore, we propose that, in switching to a resistive state, the nanotube oxidizes by extracting oxygen from the substrate.

Exchange rate volatility and regime change: Visegrad comparison

Czech Academy of Sciences Publication Activity Database

Kočenda, Evžen; Valachy, J.

-, č. 7 (2006), s. 1-36 R&D Projects: GA ČR GA402/06/1293 Institutional research plan: CEZ:AV0Z70850503 Keywords : exchange rate regime s * volatility * transition Subject RIV: AH - Economics http://deepblue.lib.umich.edu/bitstream/2027.42/21616/1/IPC-working-paper-007-KocendaValachy.pdf

Output regulation control for switched stochastic delay systems with dissipative property under error-dependent switching

Science.gov (United States)

Li, L. L.; Jin, C. L.; Ge, X.

2018-01-01

In this paper, the output regulation problem with dissipative property for a class of switched stochastic delay systems is investigated, based on an error-dependent switching law. Under the assumption that none subsystem is solvable for the problem, a sufficient condition is derived by structuring multiple Lyapunov-Krasovskii functionals with respect to multiple supply rates, via designing error feedback regulators. The condition is also established when dissipative property reduces to passive property. Finally, two numerical examples are given to demonstrate the feasibility and efficiency of the present method.

Examining the volatility of exchange rate: Does monetary policy matter?

OpenAIRE

Lim, Shu Yi; Sek, Siok Kun

2014-01-01

We conduct empirical analysis on examining the changes in exchange rate volatility under two monetary policy regimes, i.e. the pre- and post- inflation targeting (IT) regimes. In addition, we also investigate if the monetary decisions can have impacts on the volatility of exchange rate. The study is focused in four Asian countries that experienced drastic in the switch of monetary policy from the rigid exchange rate to flexible exchange rate and inflation targeting after the Asian financial c...

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

Non-volatile resistive switching in the Mott insulator (V1-xCrx)2O3

Science.gov (United States)

Querré, M.; Tranchant, J.; Corraze, B.; Cordier, S.; Bouquet, V.; Députier, S.; Guilloux-Viry, M.; Besland, M.-P.; Janod, E.; Cario, L.

2018-05-01

The discovery of non-volatile resistive switching in Mott insulators related to an electric-field-induced insulator to metal transition (IMT) has paved the way for their use in a new type of non-volatile memories, the Mott memories. While most of the previous studies were dedicated to uncover the resistive switching mechanism and explore the memory potential of chalcogenide Mott insulators, we present here a comprehensive study of resistive switching in the canonical oxide Mott insulator (V1-xCrx)2O3. Our work demonstrates that this compound undergoes a non-volatile resistive switching under electric field. This resistive switching is induced by a Mott transition at the local scale which creates metallic domains closely related to existing phases of the temperature-pressure phase diagram of (V1-xCrx)2O3. Our work demonstrates also reversible resistive switching in (V1-xCrx)2O3 crystals and thin film devices. Preliminary performances obtained on 880 nm thick layers with 500 nm electrodes show the strong potential of Mott memories based on the Mott insulator (V1-xCrx)2O3.

Exchange rate volatility and regime change: a Visegrad comparison

Czech Academy of Sciences Publication Activity Database

Kočenda, Evžen; Valachy, J.

2006-01-01

Roč. 34, č. 4 (2006), s. 727-753 ISSN 0147-5967 Institutional research plan: CEZ:MSM0021620846 Keywords : exchange rate s * exchange rate regime s * volatility Subject RIV: EH - Ecology, Behaviour Impact factor: 0.964, year: 2006 http://dx.doi.org/10.1016/j.jce.2006.07.003

A density-dependent switch drives stochastic clustering and polarization of signaling molecules.

Directory of Open Access Journals (Sweden)

Alexandra Jilkine

2011-11-01

Full Text Available Positive feedback plays a key role in the ability of signaling molecules to form highly localized clusters in the membrane or cytosol of cells. Such clustering can occur in the absence of localizing mechanisms such as pre-existing spatial cues, diffusional barriers, or molecular cross-linking. What prevents positive feedback from amplifying inevitable biological noise when an un-clustered "off" state is desired? And, what limits the spread of clusters when an "on" state is desired? Here, we show that a minimal positive feedback circuit provides the general principle for both suppressing and amplifying noise: below a critical density of signaling molecules, clustering switches off; above this threshold, highly localized clusters are recurrently generated. Clustering occurs only in the stochastic regime, suggesting that finite sizes of molecular populations cannot be ignored in signal transduction networks. The emergence of a dominant cluster for finite numbers of molecules is partly a phenomenon of random sampling, analogous to the fixation or loss of neutral mutations in finite populations. We refer to our model as the "neutral drift polarity model." Regulating the density of signaling molecules provides a simple mechanism for a positive feedback circuit to robustly switch between clustered and un-clustered states. The intrinsic ability of positive feedback both to create and suppress clustering is a general mechanism that could operate within diverse biological networks to create dynamic spatial organization.

Confinement and diffusion modulate bistability and stochastic switching in a reaction network with positive feedback

International Nuclear Information System (INIS)

Mlynarczyk, Paul J.; Pullen, Robert H.; Abel, Steven M.

2016-01-01

Positive feedback is a common feature in signal transduction networks and can lead to phenomena such as bistability and signal propagation by domain growth. Physical features of the cellular environment, such as spatial confinement and the mobility of proteins, play important but inadequately understood roles in shaping the behavior of signaling networks. Here, we use stochastic, spatially resolved kinetic Monte Carlo simulations to explore a positive feedback network as a function of system size, system shape, and mobility of molecules. We show that these physical properties can markedly alter characteristics of bistability and stochastic switching when compared with well-mixed simulations. Notably, systems of equal volume but different shapes can exhibit qualitatively different behaviors under otherwise identical conditions. We show that stochastic switching to a state maintained by positive feedback occurs by cluster formation and growth. Additionally, the frequency at which switching occurs depends nontrivially on the diffusion coefficient, which can promote or suppress switching relative to the well-mixed limit. Taken together, the results provide a framework for understanding how confinement and protein mobility influence emergent features of the positive feedback network by modulating molecular concentrations, diffusion-influenced rate parameters, and spatiotemporal correlations between molecules

Switching of bound vector solitons for the coupled nonlinear Schrödinger equations with nonhomogenously stochastic perturbations

International Nuclear Information System (INIS)

Sun Zhiyuan; Yu Xin; Liu Ying; Gao Yitian

2012-01-01

We investigate the dynamics of the bound vector solitons (BVSs) for the coupled nonlinear Schrödinger equations with the nonhomogenously stochastic perturbations added on their dispersion terms. Soliton switching (besides soliton breakup) can be observed between the two components of the BVSs. Rate of the maximum switched energy (absolute values) within the fixed propagation distance (about 10 periods of the BVSs) enhances in the sense of statistics when the amplitudes of stochastic perturbations increase. Additionally, it is revealed that the BVSs with enhanced coherence are more robust against the perturbations with nonhomogenous stochasticity. Diagram describing the approximate borders of the splitting and non-splitting areas is also given. Our results might be helpful in dynamics of the BVSs with stochastic noises in nonlinear optical fibers or with stochastic quantum fluctuations in Bose-Einstein condensates.

Switching of bound vector solitons for the coupled nonlinear Schrödinger equations with nonhomogenously stochastic perturbations

Science.gov (United States)

Sun, Zhi-Yuan; Gao, Yi-Tian; Yu, Xin; Liu, Ying

2012-12-01

We investigate the dynamics of the bound vector solitons (BVSs) for the coupled nonlinear Schrödinger equations with the nonhomogenously stochastic perturbations added on their dispersion terms. Soliton switching (besides soliton breakup) can be observed between the two components of the BVSs. Rate of the maximum switched energy (absolute values) within the fixed propagation distance (about 10 periods of the BVSs) enhances in the sense of statistics when the amplitudes of stochastic perturbations increase. Additionally, it is revealed that the BVSs with enhanced coherence are more robust against the perturbations with nonhomogenous stochasticity. Diagram describing the approximate borders of the splitting and non-splitting areas is also given. Our results might be helpful in dynamics of the BVSs with stochastic noises in nonlinear optical fibers or with stochastic quantum fluctuations in Bose-Einstein condensates.

Markov switching of the electricity supply curve and power prices dynamics

Science.gov (United States)

Mari, Carlo; Cananà, Lucianna

2012-02-01

Regime-switching models seem to well capture the main features of power prices behavior in deregulated markets. In a recent paper, we have proposed an equilibrium methodology to derive electricity prices dynamics from the interplay between supply and demand in a stochastic environment. In particular, assuming that the supply function is described by a power law where the exponent is a two-state strictly positive Markov process, we derived a regime switching dynamics of power prices in which regime switches are induced by transitions between Markov states. In this paper, we provide a dynamical model to describe the random behavior of power prices where the only non-Brownian component of the motion is endogenously introduced by Markov transitions in the exponent of the electricity supply curve. In this context, the stochastic process driving the switching mechanism becomes observable, and we will show that the non-Brownian component of the dynamics induced by transitions from Markov states is responsible for jumps and spikes of very high magnitude. The empirical analysis performed on three Australian markets confirms that the proposed approach seems quite flexible and capable of incorporating the main features of power prices time-series, thus reproducing the first four moments of log-returns empirical distributions in a satisfactory way.

Stochastic analysis of uncertain thermal parameters for random thermal regime of frozen soil around a single freezing pipe

Science.gov (United States)

Wang, Tao; Zhou, Guoqing; Wang, Jianzhou; Zhou, Lei

2018-03-01

The artificial ground freezing method (AGF) is widely used in civil and mining engineering, and the thermal regime of frozen soil around the freezing pipe affects the safety of design and construction. The thermal parameters can be truly random due to heterogeneity of the soil properties, which lead to the randomness of thermal regime of frozen soil around the freezing pipe. The purpose of this paper is to study the one-dimensional (1D) random thermal regime problem on the basis of a stochastic analysis model and the Monte Carlo (MC) method. Considering the uncertain thermal parameters of frozen soil as random variables, stochastic processes and random fields, the corresponding stochastic thermal regime of frozen soil around a single freezing pipe are obtained and analyzed. Taking the variability of each stochastic parameter into account individually, the influences of each stochastic thermal parameter on stochastic thermal regime are investigated. The results show that the mean temperatures of frozen soil around the single freezing pipe with three analogy method are the same while the standard deviations are different. The distributions of standard deviation have a great difference at different radial coordinate location and the larger standard deviations are mainly at the phase change area. The computed data with random variable method and stochastic process method have a great difference from the measured data while the computed data with random field method well agree with the measured data. Each uncertain thermal parameter has a different effect on the standard deviation of frozen soil temperature around the single freezing pipe. These results can provide a theoretical basis for the design and construction of AGF.

Non-stochastic switching and emergence of magnetic vortices in artificial quasicrystal spin ice

Energy Technology Data Exchange (ETDEWEB)

Bhat, V.S., E-mail: vinayak.bhat@uky.edu [Department of Physics and Astronomy, University of Kentucky, Lexington, KY 40506-0055 (United States); Farmer, B.; Smith, N.; Teipel, E.; Woods, J. [Department of Physics and Astronomy, University of Kentucky, Lexington, KY 40506-0055 (United States); Sklenar, J.; Ketterson, J.B. [Department of Physics and Astronomy, Northwestern University, Evanston, IL 60208-3112 (United States); Hastings, J.T. [Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY 40506-0055 (United States); De Long, L.E. [Department of Physics and Astronomy, University of Kentucky, Lexington, KY 40506-0055 (United States)

2014-08-15

Highlights: • We studied magnetic reversal in a fivefold rotational symmetric artificial quasicrystal spin ice. • Our experiments and simulations suggest the presence of non-stochastic switching in the quasicrystal. • Simulations reveal a strong connection between FM reversal and formation of vortex loops in the quasicrystal. • Our study shows that the magnetic reversal in the artificial quasicrystal is a collective phenomenon. - Abstract: Previous studies of artificial spin ice have been largely restricted to periodic dot lattices. Ferromagnetic switching of segments in an applied magnetic field is stochastic in periodic spin ice systems, which makes emergent phenomena, such as the formation of vortex loops, hard to control or predict. We fabricated finite, aperiodic Penrose P2 tilings as antidot lattices with fivefold rotational symmetry in permalloy thin films. Measurements of the field dependence of the static magnetization reveal reproducible knee anomalies whose number and form are temperature dependent, which suggests they mark cooperative rearrangements of the tiling magnetic texture. Our micromagnetic simulations of the P2 tiling are in good agreement with experimental magnetization data and exhibit non-stochastic magnetic switching of segments in applied field, and vortex loops that are stable over an extended field interval during magnetic reversal.

Modeling spot markets for electricity and pricing electricity derivatives

Science.gov (United States)

Ning, Yumei

Spot prices for electricity have been very volatile with dramatic price spikes occurring in restructured market. The task of forecasting electricity prices and managing price risk presents a new challenge for market players. The objectives of this dissertation are: (1) to develop a stochastic model of price behavior and predict price spikes; (2) to examine the effect of weather forecasts on forecasted prices; (3) to price electricity options and value generation capacity. The volatile behavior of prices can be represented by a stochastic regime-switching model. In the model, the means of the high-price and low-price regimes and the probabilities of switching from one regime to the other are specified as functions of daily peak load. The probability of switching to the high-price regime is positively related to load, but is still not high enough at the highest loads to predict price spikes accurately. An application of this model shows how the structure of the Pennsylvania-New Jersey-Maryland market changed when market-based offers were allowed, resulting in higher price spikes. An ARIMA model including temperature, seasonal, and weekly effects is estimated to forecast daily peak load. Forecasts of load under different assumptions about weather patterns are used to predict changes of price behavior given the regime-switching model of prices. Results show that the range of temperature forecasts from a normal summer to an extremely warm summer cause relatively small increases in temperature (+1.5%) and load (+3.0%). In contrast, the increases in prices are large (+20%). The conclusion is that the seasonal outlook forecasts provided by NOAA are potentially valuable for predicting prices in electricity markets. The traditional option models, based on Geometric Brownian Motion are not appropriate for electricity prices. An option model using the regime-switching framework is developed to value a European call option. The model includes volatility risk and allows changes

Persistence and extinction of a stochastic single-specie model under regime switching in a polluted environment.

Science.gov (United States)

Liu, Meng; Wang, Ke

2010-06-07

A new single-species model disturbed by both white noise and colored noise in a polluted environment is developed and analyzed. Sufficient criteria for extinction, stochastic nonpersistence in the mean, stochastic weak persistence in the mean, stochastic strong persistence in the mean and stochastic permanence of the species are established. The threshold between stochastic weak persistence in the mean and extinction is obtained. The results show that both white and colored environmental noises have sufficient effect to the survival results. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

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

Water exchange traded funds: A study on idiosyncratic risk using Markov switching analysis

Directory of Open Access Journals (Sweden)

Gurudeo Anand Tularam

2016-12-01

Full Text Available We investigate the relationship between idiosyncratic risk and return among four water exchange traded funds—PowerShares Water Resources Portfolio, Power Shares Global Water, First Trust ISE Water Index Fund, and Guggenheim S&P Global Water Index ETF using the Markov switching model for the period 2007–2015. The generated transition probabilities in this paper show that there is a high and low probability of switching between Regimes 1 and 3, respectively. Moreover, we find that the idiosyncratic risk for most of the exchange traded funds move from low volatility (Regime 2 to very low volatility (Regime 1 and 3. Our study also identify that the beta coefficients are positive and entire values are less than 1. Thus, it seems that water investment has a lower systematic risk and a positive effect on the water exchange traded index funds returns during different regimes.

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...

Adélie penguin foraging location predicted by tidal regime switching.

Science.gov (United States)

Oliver, Matthew J; Irwin, Andrew; Moline, Mark A; Fraser, William; Patterson, Donna; Schofield, Oscar; Kohut, Josh

2013-01-01

Penguin foraging and breeding success depend on broad-scale environmental and local-scale hydrographic features of their habitat. We investigated the effect of local tidal currents on a population of Adélie penguins on Humble Is., Antarctica. We used satellite-tagged penguins, an autonomous underwater vehicle, and historical tidal records to model of penguin foraging locations over ten seasons. The bearing of tidal currents did not oscillate daily, but rather between diurnal and semidiurnal tidal regimes. Adélie penguins foraging locations changed in response to tidal regime switching, and not to daily tidal patterns. The hydrography and foraging patterns of Adélie penguins during these switching tidal regimes suggest that they are responding to changing prey availability, as they are concentrated and dispersed in nearby Palmer Deep by variable tidal forcing on weekly timescales, providing a link between local currents and the ecology of this predator.

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.

Gene regulation and noise reduction by coupling of stochastic processes

Science.gov (United States)

Ramos, Alexandre F.; Hornos, José Eduardo M.; Reinitz, John

2015-02-01

Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.

Gene regulation and noise reduction by coupling of stochastic processes.

Science.gov (United States)

Ramos, Alexandre F; Hornos, José Eduardo M; Reinitz, John

2015-02-01

Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.

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.

On the origin of resistive switching volatility in Ni/TiO{sub 2}/Ni stacks

Energy Technology Data Exchange (ETDEWEB)

Cortese, Simone, E-mail: simone.cortese@soton.ac.uk; Trapatseli, Maria; Khiat, Ali; Prodromakis, Themistoklis [Nano Research Group, Electronics and Computer Science, University of Southampton, Southampton, Hampshire, SO17 1BJ (United Kingdom)

2016-08-14

Resistive switching and resistive random access memories have attracted huge interest for next generation nonvolatile memory applications, also thought to be able to overcome flash memories limitations when arranged in crossbar arrays. A cornerstone of their potential success is that the toggling between two distinct resistance states, usually a High Resistive State (HRS) and a Low Resistive State (LRS), is an intrinsic non-volatile phenomenon with the two states being thermodynamically stable. TiO{sub 2} is one of the most common materials known to support non-volatile RS. In this paper, we report a volatile resistive switching in a titanium dioxide thin film sandwiched by two nickel electrodes. The aim of this work is to understand the underlying physical mechanism that triggers the volatile effect, which is ascribed to the presence of a NiO layer at the bottom interface. The NiO layer alters the equilibrium between electric field driven filament formation and thermal enhanced ion diffusion, resulting in the volatile behaviour. Although the volatility is not ideal for non-volatile memory applications, it shows merit for access devices in crossbar arrays due to its high LRS/HRS ratio, which are also briefly discussed.

An Empirical Investigation into Exchange Rate Regime Choice and Exchange Rate Volatility

OpenAIRE

Helge Berger; Jan-Egbert Sturm; Jakob de Haan

2000-01-01

We test a simple model of exchange rate regime choice with data for 65 non-OECD countries covering the period 1980-94. We find that the variance of output at home and in potential target c ountries as well as the correlation between home and foreign real activity are powerful and robust predictors of exchange rate regime choice. Surprisingly, a more volatile foreign economy can be an argument in favor of a fixed exchange rate regime once similarities in the business cycle are taken into accou...

SWARCH and the implicit volatility of the Real/USD exchange rate

Directory of Open Access Journals (Sweden)

Rodrigo De Losso da Silveira Bueno

2008-10-01

Full Text Available This paper evaluates empirically the volatility prediction and the informational content of the exchange rate variation. The comparison is built on two different models. The first is a markov switching model on the conditional variance – SWARCH (Hamilton, 1994. The second model is based on the Garman e Kohlhagen (1983 option pricing model, from which one extracts the implicit volatility. The results show that the SWARCH’s performance is better in both dimensions and contrast with the literature in two aspects: first because the model with switching regime is not as usual as the ones without it, second because the best model is based on historical data rather than implicit volatility.

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.

A Cointegrated Regime-Switching Model Approach with Jumps Applied to Natural Gas Futures Prices

Directory of Open Access Journals (Sweden)

Daniel Leonhardt

2017-09-01

Full Text Available Energy commodities and their futures naturally show cointegrated price movements. However, there is empirical evidence that the prices of futures with different maturities might have, e.g., different jump behaviours in different market situations. Observing commodity futures over time, there is also evidence for different states of the underlying volatility of the futures. In this paper, we therefore allow for cointegration of the term structure within a multi-factor model, which includes seasonality, as well as joint and individual jumps in the price processes of futures with different maturities. The seasonality in this model is realized via a deterministic function, and the jumps are represented with thinned-out compound Poisson processes. The model also includes a regime-switching approach that is modelled through a Markov chain and extends the class of geometric models. We show how the model can be calibrated to empirical data and give some practical applications.

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.

Comment on "Fault Tolerant analysis for stochastic systems using switching diffusion processes' by Yang, Jiang and Cocquempot

DEFF Research Database (Denmark)

Schiøler, Henrik; Leth, John-Josef

2011-01-01

Results are given in [Yang et. al. 2009] regarding the overall stability of switched diffusion processes based on stability properties of separate processes combined through stochastic switching. This paper argues two main results to be empty, in that the presented hypotheses are logically...

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.

Fault Detection for Wireless Networked Control Systems with Stochastic Switching Topology and Time Delay

Directory of Open Access Journals (Sweden)

Pengfei Guo

2014-01-01

Full Text Available This paper deals with the fault detection problem for a class of discrete-time wireless networked control systems described by switching topology with uncertainties and disturbances. System states of each individual node are affected not only by its own measurements, but also by other nodes’ measurements according to a certain network topology. As the topology of system can be switched in a stochastic way, we aim to design H∞ fault detection observers for nodes in the dynamic time-delay systems. By using the Lyapunov method and stochastic analysis techniques, sufficient conditions are acquired to guarantee the existence of the filters satisfying the H∞ performance constraint, and observer gains are derived by solving linear matrix inequalities. Finally, an illustrated example is provided to verify the effectiveness of the theoretical results.

Diffusive flux in a model of stochastically gated oxygen transport in insect respiration

Energy Technology Data Exchange (ETDEWEB)

Berezhkovskii, Alexander M. [Mathematical and Statistical Computing Laboratory, Division of Computational Bioscience, Center for Information Technology, National Institutes of Health, Bethesda, Maryland 20892 (United States); Shvartsman, Stanislav Y. [Department of Chemical and Biological Engineering and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544 (United States)

2016-05-28

Oxygen delivery to insect tissues is controlled by transport through a branched tubular network that is connected to the atmosphere by valve-like gates, known as spiracles. In certain physiological regimes, the spiracles appear to be randomly switching between open and closed states. Quantitative analysis of this regime leads a reaction-diffusion problem with stochastically switching boundary condition. We derive an expression for the diffusive flux at long times in this problem. Our approach starts with the derivation of the passage probability for a single particle that diffuses between a stochastically gated boundary, which models the opening and closing spiracle, and the perfectly absorbing boundary, which models oxygen absorption by the tissue. This passage probability is then used to derive an expression giving the diffusive flux as a function of the geometric parameters of the tube and characteristic time scales of diffusion and gate dynamics.

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....

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...

Diffusion of test particles in stochastic magnetic fields in the percolative regime

International Nuclear Information System (INIS)

Neuer, Marcus; Spatschek, Karl H.

2006-01-01

For stochastic magnetic flux functions with percolative contours the test particle transport is investigated. The calculations make use of the stochastic Liouville approach. They start from the so-called A-Langevin equations, including stochastic magnetic field components and binary collisions. Using the decorrelation trajectory method, a relation between the Lagrangian velocity correlation function and the Eulerian magnetic field correlation is derived and introduced into the Green-Kubo formalism. Finite Larmor radius effects are included. Interesting results are presented in the percolation regime corresponding to high Kubo numbers. Previous results are found to be limiting cases for small Kubo numbers. For different percolative scenarios the diffusion is analyzed and strong influences of the percolative structures on the transport scaling are found. The finite Larmor radius effects are discussed in detail. Numerical simulations of the A-Langevin equation confirm the semianalytical predictions

Early Warning System in ASEAN Countries Using Capital Market Index Return: Modiied Markov Regime Switching Model

Directory of Open Access Journals (Sweden)

Imam Wahyudi

2014-08-01

Full Text Available Asia's  inancial  crisis  in  July  1997  affects  currency,  capital  market,  and  real  market throughout  Asian  countries.  Countries  in  southeast  region  (ASEAN,  including  Indonesia, Malaysia, Philippines, Singapore, and Thailand, are some of the countries where the crisis hit  the  most.  In  these  countries,  where  inancial  sectors  are  far  more  developed  than  real sectors  and  the  money  market  sectors,  most  of  the  economic  activities  are  conducted  in capital  market.  Movement  in  the  capital  market  could  be  a  proxy  to  describe  the  overall economic  situation  and  therefore  the  prediction  of  it  could  be  an  early  warning  system  of economic crises. This paper tries to investigate movement in ASEAN (Indonesia, Malaysia, Philippines,  Singapore,  and  Thailand  capital  market  to  build  an  early  warning  system from inancial sectors perspective. This paper will be very beneicial for the government to anticipate the forthcoming crisis. The insight of this paper is from Hamilton (1990 model of regime switching process in which he divide the movement of currency into two regimes, describe the switching transition based on Markov process and creates different model for each regimes. Differ from Hamilton, our research focuses on index return instead of currency to  model  the  regime  switching.  This  research  aimed  to  ind  the  probability  of  crisis  in  the future by combining the probability of switching and the probability distribution function of each  regime.  Probability  of  switching  is  estimated  by  categorizing  the  movement  in  index return  into  two  regimes  (negative  return  in  regime  1  and  positive  return  in  regime  2  then measuring  the  proportion  of  switching  to  regime  1  in  t  given  regime �

Proposed Suitable Methods to Detect Transient Regime Switching to Improve Power Quality with Wavelet Transform

Directory of Open Access Journals (Sweden)

Javad Safaee Kuchaksaraee

2016-10-01

Full Text Available The increasing consumption of electrical energy and the use of non-linear loads that create transient regime states in distribution networks is increasing day by day. This is the only reason due to which the analysis of power quality for energy sustainability in power networks has become more important. Transients are often created by energy injection through switching or lightning and make changes in voltage and nominal current. Sudden increase or decrease in voltage or current makes characteristics of the transient regime. This paper shed some lights on the capacitor bank switching, which is one of the main causes for oscillatory transient regime states in the distribution network, using wavelet transform. The identification of the switching current of capacitor bank and the internal fault current of the transformer to prevent the unnecessary outage of the differential relay, it propose a new smart method. The accurate performance of this method is shown by simulation in EMTP and MATLAB (matrix laboratory software.

On the source of stochastic volatility: Evidence from CAC40 index options during the subprime crisis

Science.gov (United States)

Slim, Skander

2016-12-01

This paper investigates the performance of time-changed Lévy processes with distinct sources of return volatility variation for modeling cross-sectional option prices on the CAC40 index during the subprime crisis. Specifically, we propose a multi-factor stochastic volatility model: one factor captures the diffusion component dynamics and two factors capture positive and negative jump variations. In-sample and out-of-sample tests show that our full-fledged model significantly outperforms nested lower-dimensional specifications. We find that all three sources of return volatility variation, with different persistence, are needed to properly account for market pricing dynamics across moneyness, maturity and volatility level. Besides, the model estimation reveals negative risk premium for both diffusive volatility and downward jump intensity whereas a positive risk premium is found to be attributed to upward jump intensity.

Permanence and asymptotic behaviors of stochastic predator-prey system with Markovian switching and Lévy noise

Science.gov (United States)

Wang, Sheng; Wang, Linshan; Wei, Tengda

2018-04-01

This paper concerns the dynamics of a stochastic predator-prey system with Markovian switching and Lévy noise. First, the existence and uniqueness of global positive solution to the system is proved. Then, by combining stochastic analytical techniques with M-matrix analysis, sufficient conditions of stochastic permanence and extinction are obtained. Furthermore, for the stochastic permanence case, by means of four constants related to the stationary probability distribution of the Markov chain and the parameters of the subsystems, both the superior limit and the inferior limit of the average in time of the sample path of the solution are estimated. Finally, our conclusions are illustrated through an example.

Bridging time scales in cellular decision making with a stochastic bistable switch

Directory of Open Access Journals (Sweden)

Waldherr Steffen

2010-08-01

Full Text Available Abstract Background Cellular transformations which involve a significant phenotypical change of the cell's state use bistable biochemical switches as underlying decision systems. Some of these transformations act over a very long time scale on the cell population level, up to the entire lifespan of the organism. Results In this work, we aim at linking cellular decisions taking place on a time scale of years to decades with the biochemical dynamics in signal transduction and gene regulation, occuring on a time scale of minutes to hours. We show that a stochastic bistable switch forms a viable biochemical mechanism to implement decision processes on long time scales. As a case study, the mechanism is applied to model the initiation of follicle growth in mammalian ovaries, where the physiological time scale of follicle pool depletion is on the order of the organism's lifespan. We construct a simple mathematical model for this process based on experimental evidence for the involved genetic mechanisms. Conclusions Despite the underlying stochasticity, the proposed mechanism turns out to yield reliable behavior in large populations of cells subject to the considered decision process. Our model explains how the physiological time constant may emerge from the intrinsic stochasticity of the underlying gene regulatory network. Apart from ovarian follicles, the proposed mechanism may also be of relevance for other physiological systems where cells take binary decisions over a long time scale.

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.

Diagram of collisional regimes for particle diffusion in a stochastic magnetic field

International Nuclear Information System (INIS)

Misguich, J.H.; Balescu, R.

1995-01-01

This document deals with static stochastic fields, where magnetic lines experience exponential separation and magnetic diffusion. It more particularly focuses on the diffusivity of collisional particles in such a fields and presents a general graph which describes most regimes of collisional and weakly collisional diffusion for guiding centers in a time-independent magnetic field. (TEC). 9 refs., 1 fig., 2 tabs

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.

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.

Analytic Approximation of the Solutions of Stochastic Differential Delay Equations with Poisson Jump and Markovian Switching

Directory of Open Access Journals (Sweden)

Hua Yang

2012-01-01

Full Text Available We are concerned with the stochastic differential delay equations with Poisson jump and Markovian switching (SDDEsPJMSs. Most SDDEsPJMSs cannot be solved explicitly as stochastic differential equations. Therefore, numerical solutions have become an important issue in the study of SDDEsPJMSs. The key contribution of this paper is to investigate the strong convergence between the true solutions and the numerical solutions to SDDEsPJMSs when the drift and diffusion coefficients are Taylor approximations.

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...

Directional Congestion and Regime Switching in a Long Memory Model for Electricity Prices

DEFF Research Database (Denmark)

Haldrup, Niels; Nielsen, Morten Ø.

The functioning of electricity markets has experienced increasing complexityas a result of deregulation in recent years. Consequently this affects the multilateral price behaviour across regions with physical exchange of power. It has been documented elsewhere that features such aslong memory...... and regime switching reflecting congestion and non-congestion periods are empirically relevant and hence are features that need to be taken into account when modeling price behavior. In the present paper we further elaborate on the co-existence of long memory and regime switches by focusing on the effect...... that the direction of possible congestion episodes has on the price dynamics. Under non-congestion prices are identical. The direction of possible congestion is identified by the region with excess demand of power through the sign of price differences and hence three different states can be considered: Non...

Pricing Vulnerable Options with Market Prices of Common Jump Risks under Regime-Switching Models

Directory of Open Access Journals (Sweden)

Miao Han

2018-01-01

Full Text Available This paper investigates the valuation of vulnerable European options considering the market prices of common systematic jump risks under regime-switching jump-diffusion models. The way of regime-switching Esscher transform is adopted to identify an equivalent martingale measure for pricing vulnerable European options. Explicit analytical pricing formulae for vulnerable European options are derived by risk-neutral pricing theory. For comparison, the other two cases are also considered separately. The first case considers all jump risks as unsystematic risks while the second one assumes all jumps risks to be systematic risks. Numerical examples for the valuation of vulnerable European options are provided to illustrate our results and indicate the influence of the market prices of jump risks on the valuation of vulnerable European options.

Libor at crossroads: Stochastic switching detection using information theory quantifiers

International Nuclear Information System (INIS)

Bariviera, Aurelio F.; Guercio, M. Belén; Martinez, Lisana B.; Rosso, Osvaldo A.

2016-01-01

Highlights: • 28 time series of Libor rates, classified in seven maturities and four currencies, during the last 14 years, were considered. • The analysis was performed using a novel technique in financial economics: the Complexity–Entropy Causality Plane. • Our analysis unveils an abnormal movement of Libor time series around the period of the 2007 financial crisis. • This alteration in the stochastic dynamics of Libor is contemporary of what press called “Libor scandal”. - Abstract: This paper studies the 28 time series of Libor rates, classified in seven maturities and four currencies, during the last 14 years. The analysis was performed using a novel technique in financial economics: the Complexity–Entropy Causality Plane. This planar representation allows the discrimination of different stochastic and chaotic regimes. Using a temporal analysis based on moving windows, this paper unveils an abnormal movement of Libor time series around the period of the 2007 financial crisis. This alteration in the stochastic dynamics of Libor is contemporary of what press called “Libor scandal”, i.e. the manipulation of interest rates carried out by several prime banks. We argue that our methodology is suitable as a market watch mechanism, as it makes visible the temporal redution in informational efficiency of the market.

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

Stochastic stabilization of phenotypic States: the genetic bistable switch as a case study.

Science.gov (United States)

Weber, Marc; Buceta, Javier

2013-01-01

We study by means of analytical calculation and stochastic simulations how intrinsic noise modifies the bifurcation diagram of gene regulatory processes that can be effectively described by the Langevin formalism. In a general context, our study raises the intriguing question of how biochemical fluctuations redesign the epigenetic landscape in differentiation processes. We have applied our findings to a general class of regulatory processes that includes the simplest case that displays a bistable behavior and hence phenotypic variability: the genetic auto-activating switch. Thus, we explain why and how the noise promotes the stability of the low-state phenotype of the switch and show that the bistable region is extended when increasing the intensity of the fluctuations. This phenomenology is found in a simple one-dimensional model of the genetic switch as well as in a more detailed model that takes into account the binding of the protein to the promoter region. Altogether, we prescribe the analytical means to understand and quantify the noise-induced modifications of the bifurcation points for a general class of regulatory processes where the genetic bistable switch is included.

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

Estimating Dynamic Connectivity States in fMRI Using Regime-Switching Factor Models

KAUST Repository

Ting, Chee-Ming

2017-12-06

We consider the challenges in estimating state-related changes in brain connectivity networks with a large number of nodes. Existing studies use sliding-window analysis or time-varying coefficient models which are unable to capture both smooth and abrupt changes simultaneously, and rely on ad-hoc approaches to the high-dimensional estimation. To overcome these limitations, we propose a Markov-switching dynamic factor model which allows the dynamic connectivity states in functional magnetic resonance imaging (fMRI) data to be driven by lower-dimensional latent factors. We specify a regime-switching vector autoregressive (SVAR) factor process to quantity the time-varying directed connectivity. The model enables a reliable, data-adaptive estimation of change-points of connectivity regimes and the massive dependencies associated with each regime. We develop a three-step estimation procedure: 1) extracting the factors using principal component analysis, 2) identifying connectivity regimes in a low-dimensional subspace based on the factor-based SVAR model, 3) constructing high-dimensional state connectivity metrics based on the subspace estimates. Simulation results show that our estimator outperforms K-means clustering of time-windowed coefficients, providing more accurate estimate of time-evolving connectivity. It achieves percentage of reduction in mean squared error by 60% when the network dimension is comparable to the sample size. When applied to resting-state fMRI data, our method successfully identifies modular organization in resting-state networks in consistency with other studies. It further reveals changes in brain states with variations across subjects and distinct large-scale directed connectivity patterns across states.

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.

It’s all about volatility of volatility

DEFF Research Database (Denmark)

Grassi, Stefano; Santucci de Magistris, Paolo

2015-01-01

The persistent nature of equity volatility is investigated by means of a multi-factor stochastic volatility model with time varying parameters. The parameters are estimated by means of a sequential matching procedure which adopts as auxiliary model a time-varying generalization of the HAR model f...

DETERMINANTS OF FOREIGN DIRECT INVESTMENT IN NIGERIA: A MARKOV REGIME-SWITCHING APPROACH

Directory of Open Access Journals (Sweden)

Akinlo A. Enisan

2017-04-01

Full Text Available Several studies have analyzed the movement of foreign direct investment in Nigeria using linear approach. In contrast with all existing studies in Nigeria, this paper runs several non linear FDI equations where the main determinants of FDI are determined using Markov- Regime Switching Model (MSMs. The approach enables us to observe structural changes, where exist, in FDI equations through time. Asides, where FDI regression equation is truly nonlinear, MSMs fit data better than the linear models. The paper adopts maximum likelihood methodology of Markov-Regime Model (MSM to identify possible structural changes in level and/or trends and possible changes in parameters of independent variables through the transition probabilities. The results show that FDI process in Nigeria is governed by two different regimes and a shift from one regime to another regime depends on transition probabilities. The results show that the main determinants of FDI are GDP growth, macro instability, financial development, exchange rate, inflation and discount rate. This implies liberalization that stems inflation and enhance the value of domestic currency will attract more FDI into the country.

Study of selected phenotype switching strategies in time varying environment

Energy Technology Data Exchange (ETDEWEB)

Horvath, Denis, E-mail: horvath.denis@gmail.com [Centre of Interdisciplinary Biosciences, Institute of Physics, Faculty of Science, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia); Brutovsky, Branislav, E-mail: branislav.brutovsky@upjs.sk [Department of Biophysics, Institute of Physics, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia)

2016-03-22

Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

Study of selected phenotype switching strategies in time varying environment

International Nuclear Information System (INIS)

Horvath, Denis; Brutovsky, Branislav

2016-01-01

Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

Fundamental volatility is regime specific

NARCIS (Netherlands)

Arnold, I.J.M.; MacDonald, R.; Vries, de C.G.

2006-01-01

A widely held notion holds that freely floating exchange rates are excessively volatile when judged against fundamentals and when moving from fixed to floating exchange rates. We re-examine the data and conclude that the disparity between the fundamentals and exchange rate volatility is more

The two-regime method for optimizing stochastic reaction-diffusion simulations

KAUST Repository

Flegg, M. B.

2011-10-19

Spatial organization and noise play an important role in molecular systems biology. In recent years, a number of software packages have been developed for stochastic spatio-temporal simulation, ranging from detailed molecular-based approaches to less detailed compartment-based simulations. Compartment-based approaches yield quick and accurate mesoscopic results, but lack the level of detail that is characteristic of the computationally intensive molecular-based models. Often microscopic detail is only required in a small region (e.g. close to the cell membrane). Currently, the best way to achieve microscopic detail is to use a resource-intensive simulation over the whole domain. We develop the two-regime method (TRM) in which a molecular-based algorithm is used where desired and a compartment-based approach is used elsewhere. We present easy-to-implement coupling conditions which ensure that the TRM results have the same accuracy as a detailed molecular-based model in the whole simulation domain. Therefore, the TRM combines strengths of previously developed stochastic reaction-diffusion software to efficiently explore the behaviour of biological models. Illustrative examples and the mathematical justification of the TRM are also presented.

A vector autoregressive model for electricity prices subject to long memory and regime switching

International Nuclear Information System (INIS)

Haldrup, Niels; Nielsen, Frank S.; Nielsen, Morten Oerregaard

2010-01-01

A regime dependent VAR model is suggested that allows long memory (fractional integration) in each of the observed regime states as well as the possibility of fractional cointegration. The model is motivated by the dynamics of electricity prices where the transmission of power is subject to occasional congestion periods. For a system of bilateral prices non-congestion means that electricity prices are identical whereas congestion makes prices depart. Hence, the joint price dynamics implies switching between a univariate price process under non-congestion and a bivariate price process under congestion. At the same time, it is an empirical regularity that electricity prices tend to show a high degree of long memory, and thus that prices may be fractionally cointegrated. Analysis of Nord Pool data shows that even though the prices are identical under non-congestion, the prices are not, in general, fractionally cointegrated in the congestion state. Hence, in most cases price convergence is a property following from regime switching rather than a conventional error correction mechanism. Finally, the suggested model is shown to deliver forecasts that are more precise compared to competing models. (author)

A Time Series Regime Classification Approach for Short-Term Forecasting; Identificacion de Mecanismos en Series Temporales para la Prediccion a Corto Plazo

Energy Technology Data Exchange (ETDEWEB)

Gallego, C. J.

2010-03-08

Abstract: This technical report is focused on the analysis of stochastic processes that switch between different dynamics (also called regimes or mechanisms) over time. The so-called Switching-regime models consider several underlying functions instead of one. In this case, a classification problem arises as the current regime has to be assessed at each time-step. The identification of the regimes allows the performance of regime-switching models for short-term forecasting purposes. Within this framework, identifying different regimes showed by time-series is the aim of this work. The proposed approach is based on a statistical tool called Gamma-test. One of the main advantages of this methodology is the absence of a mathematical definition for the different underlying functions. Applications with both simulated and real wind power data have been considered. Results on simulated time series show that regimes can be successfully identified under certain hypothesis. Nevertheless, this work highlights that further research has to be done when considering real wind power time-series, which usually show different behaviours (e.g. fluctuations or ramps, followed by low variance periods). A better understanding of these events eventually will improve wind power forecasting. (Author) 15 refs.

Numerical approach to optimal portfolio in a power utility regime-switching model

Science.gov (United States)

Gyulov, Tihomir B.; Koleva, Miglena N.; Vulkov, Lubin G.

2017-12-01

We consider a system of weakly coupled degenerate semi-linear parabolic equations of optimal portfolio in a regime-switching with power utility function, derived by A.R. Valdez and T. Vargiolu [14]. First, we discuss some basic properties of the solution of this system. Then, we develop and analyze implicit-explicit, flux limited finite difference schemes for the differential problem. Numerical experiments are discussed.

Anomalous transport regimes in a stochastic advection-diffusion model

International Nuclear Information System (INIS)

Dranikov, I.L.; Kondratenko, P.S.; Matveev, L.V.

2004-01-01

A general solution to the stochastic advection-diffusion problem is obtained for a fractal medium with long-range correlated spatial fluctuations. A particular transport regime is determined by two basic parameters: the exponent 2h of power-law decay of the two-point velocity correlation function and the mean advection velocity u. The values of these parameters corresponding to anomalous diffusion are determined, and anomalous behavior of the tracer distribution is analyzed for various combinations of u and h. The tracer concentration is shown to decrease exponentially at large distances, whereas power-law decay is predicted by fractional differential equations. Equations that describe the essential characteristics of the solution are written in terms of coupled space-time fractional differential operators. The analysis relies on a diagrammatic technique and makes use of scale-invariant properties of the medium

Relatively slow stochastic gene-state switching in the presence of positive feedback significantly broadens the region of bimodality through stabilizing the uninduced phenotypic state.

Science.gov (United States)

Ge, Hao; Wu, Pingping; Qian, Hong; Xie, Xiaoliang Sunney

2018-03-01

Within an isogenic population, even in the same extracellular environment, individual cells can exhibit various phenotypic states. The exact role of stochastic gene-state switching regulating the transition among these phenotypic states in a single cell is not fully understood, especially in the presence of positive feedback. Recent high-precision single-cell measurements showed that, at least in bacteria, switching in gene states is slow relative to the typical rates of active transcription and translation. Hence using the lac operon as an archetype, in such a region of operon-state switching, we present a fluctuating-rate model for this classical gene regulation module, incorporating the more realistic operon-state switching mechanism that was recently elucidated. We found that the positive feedback mechanism induces bistability (referred to as deterministic bistability), and that the parameter range for its occurrence is significantly broadened by stochastic operon-state switching. We further show that in the absence of positive feedback, operon-state switching must be extremely slow to trigger bistability by itself. However, in the presence of positive feedback, which stabilizes the induced state, the relatively slow operon-state switching kinetics within the physiological region are sufficient to stabilize the uninduced state, together generating a broadened parameter region of bistability (referred to as stochastic bistability). We illustrate the opposite phenotype-transition rate dependence upon the operon-state switching rates in the two types of bistability, with the aid of a recently proposed rate formula for fluctuating-rate models. The rate formula also predicts a maximal transition rate in the intermediate region of operon-state switching, which is validated by numerical simulations in our model. Overall, our findings suggest a biological function of transcriptional "variations" among genetically identical cells, for the emergence of bistability and

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.

On perpetual American put valuation and first-passage in a regime-switching model with jumps

OpenAIRE

Jiang, Z.; Pistorius, M. R.

2008-01-01

In this paper we consider the problem of pricing a perpetual American put option in an exponential regime-switching L\\'{e}vy model. For the case of the (dense) class of phase-type jumps and finitely many regimes we derive an explicit expression for the value function. The solution of the corresponding first passage problem under a state-dependent level rests on a path transformation and a new matrix Wiener-Hopf factorization result for this class of processes.

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.

A Vector Autoregressive Model for Electricity Prices Subject to Long Memory and Regime Switching

DEFF Research Database (Denmark)

Haldrup, Niels; Nielsen, Frank; Nielsen, Morten Ørregaard

2007-01-01

A regime dependent VAR model is suggested that allows long memory (fractional integration) in each of the regime states as well as the possibility of fractional cointegra- tion. The model is relevant in describing the price dynamics of electricity prices where the transmission of power is subject...... to occasional congestion periods. For a system of bilat- eral prices non-congestion means that electricity prices are identical whereas congestion makes prices depart. Hence, the joint price dynamics implies switching between essen- tially a univariate price process under non-congestion and a bivariate price...

Regime switching state-space models applied to psychological processes: handling missing data and making inferences

NARCIS (Netherlands)

Hamaker, E.L.; Grasman, R.P.P.P.

2012-01-01

Many psychological processes are characterized by recurrent shifts between distinct regimes or states. Examples that are considered in this paper are the switches between different states associated with premenstrual syndrome, hourly fluctuations in affect during a major depressive episode, and

Finite-Time Nonfragile Synchronization of Stochastic Complex Dynamical Networks with Semi-Markov Switching Outer Coupling

Directory of Open Access Journals (Sweden)

Rathinasamy Sakthivel

2018-01-01

Full Text Available The problem of robust nonfragile synchronization is investigated in this paper for a class of complex dynamical networks subject to semi-Markov jumping outer coupling, time-varying coupling delay, randomly occurring gain variation, and stochastic noise over a desired finite-time interval. In particular, the network topology is assumed to follow a semi-Markov process such that it may switch from one to another at different instants. In this paper, the random gain variation is represented by a stochastic variable that is assumed to satisfy the Bernoulli distribution with white sequences. Based on these hypotheses and the Lyapunov-Krasovskii stability theory, a new finite-time stochastic synchronization criterion is established for the considered network in terms of linear matrix inequalities. Moreover, the control design parameters that guarantee the required criterion are computed by solving a set of linear matrix inequality constraints. An illustrative example is finally given to show the effectiveness and advantages of the developed analytical results.

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 empirical comparison of alternate regime-switching models for electricity spot prices

Energy Technology Data Exchange (ETDEWEB)

Janczura, Joanna [Hugo Steinhaus Center, Institute of Mathematics and Computer Science, Wroclaw University of Technology, 50-370 Wroclaw (Poland); Weron, Rafal [Institute of Organization and Management, Wroclaw University of Technology, 50-370 Wroclaw (Poland)

2010-09-15

One of the most profound features of electricity spot prices are the price spikes. Markov regime-switching (MRS) models seem to be a natural candidate for modeling this spiky behavior. However, in the studies published so far, the goodness-of-fit of the proposed models has not been a major focus. While most of the models were elegant, their fit to empirical data has either been not examined thoroughly or the signs of a bad fit ignored. With this paper we want to fill the gap. We calibrate and test a range of MRS models in an attempt to find parsimonious specifications that not only address the main characteristics of electricity prices but are statistically sound as well. We find that the best structure is that of an independent spike 3-regime model with time-varying transition probabilities, heteroscedastic diffusion-type base regime dynamics and shifted spike regime distributions. Not only does it allow for a seasonal spike intensity throughout the year and consecutive spikes or price drops, which is consistent with market observations, but also exhibits the 'inverse leverage effect' reported in the literature for spot electricity prices. (author)

An empirical comparison of alternate regime-switching models for electricity spot prices

International Nuclear Information System (INIS)

Janczura, Joanna; Weron, Rafal

2010-01-01

One of the most profound features of electricity spot prices are the price spikes. Markov regime-switching (MRS) models seem to be a natural candidate for modeling this spiky behavior. However, in the studies published so far, the goodness-of-fit of the proposed models has not been a major focus. While most of the models were elegant, their fit to empirical data has either been not examined thoroughly or the signs of a bad fit ignored. With this paper we want to fill the gap. We calibrate and test a range of MRS models in an attempt to find parsimonious specifications that not only address the main characteristics of electricity prices but are statistically sound as well. We find that the best structure is that of an independent spike 3-regime model with time-varying transition probabilities, heteroscedastic diffusion-type base regime dynamics and shifted spike regime distributions. Not only does it allow for a seasonal spike intensity throughout the year and consecutive spikes or price drops, which is consistent with market observations, but also exhibits the 'inverse leverage effect' reported in the literature for spot electricity prices. (author)

Non-Volatile Ferroelectric Switching of Ferromagnetic Resonance in NiFe/PLZT Multiferroic Thin Film Heterostructures (Postprint)

Science.gov (United States)

2016-09-01

deformation potentially leads to fatigue and fracture over time. Moreover, we show that by simply applying voltage pulses, a robust, non-volatile...polarization such as PZT , BiFeO3, or doped HfO2. Our results thus provide a pathway towards ferroelectric switching of magnetism that could be useful for

Pemodelan Markov Switching Autoregressive

OpenAIRE

Ariyani, Fiqria Devi; Warsito, Budi; Yasin, Hasbi

2014-01-01

Transition from depreciation to appreciation of exchange rate is one of regime switching that ignored by classic time series model, such as ARIMA, ARCH, or GARCH. Therefore, economic variables are modeled by Markov Switching Autoregressive (MSAR) which consider the regime switching. MLE is not applicable to parameters estimation because regime is an unobservable variable. So that filtering and smoothing process are applied to see the regime probabilities of observation. Using this model, tran...

Multistable decision switches for flexible control of epigenetic differentiation.

Directory of Open Access Journals (Sweden)

Raúl Guantes

2008-11-01

Full Text Available It is now recognized that molecular circuits with positive feedback can induce two different gene expression states (bistability under the very same cellular conditions. Whether, and how, cells make use of the coexistence of a larger number of stable states (multistability is however largely unknown. Here, we first examine how autoregulation, a common attribute of genetic master regulators, facilitates multistability in two-component circuits. A systematic exploration of these modules' parameter space reveals two classes of molecular switches, involving transitions in bistable (progression switches or multistable (decision switches regimes. We demonstrate the potential of decision switches for multifaceted stimulus processing, including strength, duration, and flexible discrimination. These tasks enhance response specificity, help to store short-term memories of recent signaling events, stabilize transient gene expression, and enable stochastic fate commitment. The relevance of these circuits is further supported by biological data, because we find them in numerous developmental scenarios. Indeed, many of the presented information-processing features of decision switches could ultimately demonstrate a more flexible control of epigenetic differentiation.

Resistive switching characteristics of polymer non-volatile memory devices in a scalable via-hole structure

International Nuclear Information System (INIS)

Kim, Tae-Wook; Choi, Hyejung; Oh, Seung-Hwan; Jo, Minseok; Wang, Gunuk; Cho, Byungjin; Kim, Dong-Yu; Hwang, Hyunsang; Lee, Takhee

2009-01-01

The resistive switching characteristics of polyfluorene-derivative polymer material in a sub-micron scale via-hole device structure were investigated. The scalable via-hole sub-microstructure was fabricated using an e-beam lithographic technique. The polymer non-volatile memory devices varied in size from 40 x 40 μm 2 to 200 x 200 nm 2 . From the scaling of junction size, the memory mechanism can be attributed to the space-charge-limited current with filamentary conduction. Sub-micron scale polymer memory devices showed excellent resistive switching behaviours such as a large ON/OFF ratio (I ON /I OFF ∼10 4 ), excellent device-to-device switching uniformity, good sweep endurance, and good retention times (more than 10 000 s). The successful operation of sub-micron scale memory devices of our polyfluorene-derivative polymer shows promise to fabricate high-density polymer memory devices.

Exchange rate movements and stock market returns in a regime-switching environment: Evidence for BRICS countries

OpenAIRE

Walid Chkili; Duc Khuong Nguyen

2014-01-01

We use a regime-switching model approach to investigate the dynamic linkages between the exchange rates and stock market returns for the BRICS countries (Brazil, Russia, India, China and South Africa). The univariate analysis indicates that stock returns

Anticipating regime shifts in gene expression: The case of an autoactivating positive feedback loop

Science.gov (United States)

Sharma, Yogita; Dutta, Partha Sharathi; Gupta, A. K.

2016-03-01

Considerable evidence suggests that anticipating sudden shifts from one state to another in bistable dynamical systems is a challenging task; examples include ecosystems, financial markets, and complex diseases. In this paper, we investigate the effects of additive, multiplicative, and cross-correlated stochastic perturbations on determining the regime shifts in a bistable gene regulatory system, which gives rise to two distinct states of low and high concentrations of protein. We obtain the stationary probability density and mean first-passage time of the system. We show that increasing the additive (multiplicative) noise intensity induces a regime shift from a low (high) to a high (low) protein concentration state. However, an increase in the cross-correlation intensity always induces regime shifts from a high to a low protein concentration state. For both bifurcation-induced (often called the tipping point) and noise-induced (called stochastic switching) regime shifts, we further explore the robustness of recently developed critical-down-based early warning signal (EWS) indicators (e.g., rising variance and lag-1 autocorrelation) on our simulated time-series data. We identify that using EWS indicators, prediction of an impending bifurcation-induced regime shift is relatively easier than that of a noise-induced regime shift in the considered system. Moreover, the success of EWS indicators also strongly depends upon the nature of the noise.

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.

Pricing Options and Equity-Indexed Annuities in a Regime-switching Model by Trinomial Tree Method

Directory of Open Access Journals (Sweden)

Fei Lung Yuen

2011-12-01

Full Text Available In this paper we summarize the main idea and results of Yuen and Yang (2009, 2010a, 2010b and provide some results on pricing of Parisian options under the Markov regime-switching model (MRSM. The MRSM allows the parameters of the market model depending on a Markovian process, and the model can reflect the information of the market environment which cannot be modeled solely by linear Gaussian process. However, when the parameters of the stock price model are not constant but governed by a Markovian process, the pricing of the options becomes complex. We present a fast and simple trinomial tree model to price options in MRSM. In recent years, the pricing of modern insurance products, such as Equity-Indexed annuity (EIA and variable annuities (VAs, has become a popular topic. We show here that our trinomial tree model can been used to price EIA with strong path dependent exotic options in the regime switching model.

A STUDY OF SOLID STATE LASER PASSIVE OPTICAL Q-SWITCHING OPERATION REGIME (Part 1

Directory of Open Access Journals (Sweden)

Ion LĂNCRĂNJAN

2009-09-01

Full Text Available This paper is the first of a four series treating, theoretically with experimental comparison, the issue of solid state laser passive optical Q-switching regime. In this first paper the technique of solid state lasers passive optical Q-switching is numerically investigated considering the case of longitudinally and transversally uniform photon, population inversion and absorption centres densities. The coupled differential equations defining photon, population inversion and absorption centres densities are numerically solved being the basis of passively optical Q-switched laser functional simulation. The numerical simulations are performed using the several software packages, mostly SCILAB programs. The developed SCILAB programs can be used for a large range of saturable absorption centre and active media parameters, mainly the initial (low signal optical transmittance of the passive optical Q-switch. The developed FORTRAN and SCILAB programs can be applied for passively Q-switched solid state lasers of several types emitting at several NIR wavelengths, in domain 1 ÷ 2 μm. For validating the numerical simulation results are compared with The results of the numerical simulation are compared with experimentally obtained ones, in the case of a LiF:F2- passively Q-switched Nd:YAG. A good agreement between the two kinds of results is observed.

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 ($/£ )....

Non-exponential resistive switching in Ag2S memristors: a key to nanometer-scale non-volatile memory devices.

Science.gov (United States)

Gubicza, Agnes; Csontos, Miklós; Halbritter, András; Mihály, György

2015-03-14

The dynamics of resistive switchings in nanometer-scale metallic junctions formed between an inert metallic tip and an Ag film covered by a thin Ag2S layer are investigated. Our thorough experimental analysis and numerical simulations revealed that the resistance change upon a switching bias voltage pulse exhibits a strongly non-exponential behaviour yielding markedly different response times at different bias levels. Our results demonstrate the merits of Ag2S nanojunctions as nanometer-scale non-volatile memory cells with stable switching ratios, high endurance as well as fast response to write/erase, and an outstanding stability against read operations at technologically optimal bias and current levels.

Unifying description of the damping regimes of a stochastic particle in a periodic potential

Directory of Open Access Journals (Sweden)

Antonio Piscitelli, Massimo Pica Ciamarra

2017-09-01

Full Text Available We analyze the classical problem of the stochastic dynamics of a particle confined in a periodic potential, through the so called Il'in and Khasminskii model, with a novel semi-analytical approach. Our approach gives access to the transient and the asymptotic dynamics in all damping regimes, which are difficult to investigate in the usual Brownian model. We show that the crossover from the overdamped to the underdamped regime is associated with the loss of a typical time scale and of a typical length scale, as signaled by the divergence of the probability distribution of a certain dynamical event. In the underdamped regime, normal diffusion coexists with a non Gaussian displacement probability distribution for a long transient, as recently observed in a variety of different systems. We rationalize the microscopic physical processes leading to the non-Gaussian behavior, as well as the timescale to recover the Gaussian statistics. The theoretical results are supported by numerical calculations and are compared to those obtained for the Brownian model.

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.

Modeling Conditional Volatility of Indian Banking Sector’s Stock Market Returns

Directory of Open Access Journals (Sweden)

Singh Amanjot

2017-10-01

Full Text Available The study attempts to capture conditional variance of Indian banking sector’s stock market returns across the years 2005 to 2015 by employing different GARCH based symmetric and asymmetric models. The results report existence of persistency as well as leverage effects in the banking sector return volatility. On an expected note, the global financial crisis increased conditional volatility in the Indian banking sector during the years 2007 to 2009; further evidenced from Markov regime switches. The exponential GARCH (EGARCH model is found to be the best fit model capturing time-varying variance in the banking sector. The results support strong implications for the market participants at the time of devising portfolio management strategies.

Generation of Q-Switched Mode-Locked Erbium-Doped Fiber Laser Operating in Dark Regime

International Nuclear Information System (INIS)

Tiu, Zian Cheak; Zarei, Arman; Ahmad, Harith; Harun, Sulaiman Wadi

2016-01-01

We demonstrate a stable Q-switched mode-locked erbium-doped fiber laser (EDFL) operating in dark regime based on the nonlinear polarization rotation technique. The EDFL produces a pulse train where the Q-switching envelope is formed by multiple dark pulses. The repetition rate of the Q-switched envelope can be increased from 0.96 kHz to 3.26 kHz, whereas the pulse width reduces from 211 μs to 86 μs. The highest pulse of 479 nJ is obtained at the pump power of 55 mW. It is also observed that the dark pulses inside the Q-switching envelope consist of two parts: square and trailing dark pulses. The shortest pulse width of the dark square pulse is obtained at 40.5 μs when the pump power is fixed at 145 mW. The repetition rate of trailing dark pulses can be increased from 27.62 kHz to 50 kHz as the pump power increases from 55 mW to 145 mW. (paper)

"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

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

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.

Switching neuronal state: optimal stimuli revealed using a stochastically-seeded gradient algorithm.

Science.gov (United States)

Chang, Joshua; Paydarfar, David

2014-12-01

Inducing a switch in neuronal state using energy optimal stimuli is relevant to a variety of problems in neuroscience. Analytical techniques from optimal control theory can identify such stimuli; however, solutions to the optimization problem using indirect variational approaches can be elusive in models that describe neuronal behavior. Here we develop and apply a direct gradient-based optimization algorithm to find stimulus waveforms that elicit a change in neuronal state while minimizing energy usage. We analyze standard models of neuronal behavior, the Hodgkin-Huxley and FitzHugh-Nagumo models, to show that the gradient-based algorithm: (1) enables automated exploration of a wide solution space, using stochastically generated initial waveforms that converge to multiple locally optimal solutions; and (2) finds optimal stimulus waveforms that achieve a physiological outcome condition, without a priori knowledge of the optimal terminal condition of all state variables. Analysis of biological systems using stochastically-seeded gradient methods can reveal salient dynamical mechanisms underlying the optimal control of system behavior. The gradient algorithm may also have practical applications in future work, for example, finding energy optimal waveforms for therapeutic neural stimulation that minimizes power usage and diminishes off-target effects and damage to neighboring tissue.

L{sup 1} group consensus of multi-agent systems with switching topologies and stochastic inputs

Energy Technology Data Exchange (ETDEWEB)

Shang, Yilun, E-mail: shylmath@hotmail.com [Institute for Cyber Security, University of Texas at San Antonio, TX 78249 (United States); SUTD-MIT International Design Center, Singapore University of Technology and Design, Singapore 138682 (Singapore)

2013-10-01

Understanding how interacting subsystems of an overall system lead to cluster/group consensus is a key issue in the investigation of multi-agent systems. In this Letter, we study the L{sup 1} group consensus problem of discrete-time multi-agent systems with external stochastic inputs. Based on ergodicity theory and matrix analysis, L{sup 1} group consensus criteria are obtained for multi-agent systems with switching topologies. Some numerical examples are provided to illustrate the effectiveness and feasibility of the theoretical results.

Voltage control of metal-insulator transition and non-volatile ferroelastic switching of resistance in VOx/PMN-PT heterostructures.

Science.gov (United States)

Nan, Tianxiang; Liu, Ming; Ren, Wei; Ye, Zuo-Guang; Sun, Nian X

2014-08-04

The central challenge in realizing electronics based on strongly correlated electronic states, or 'Mottronics', lies in finding an energy efficient way to switch between the distinct collective phases with a control voltage in a reversible and reproducible manner. In this work, we demonstrate that a voltage-impulse-induced ferroelastic domain switching in the (011)-oriented 0.71Pb(Mg1/3Nb2/3)O3-0.29PbTiO3 (PMN-PT) substrates allows a robust non-volatile tuning of the metal-insulator transition in the VOx films deposited onto them. In such a VOx/PMN-PT heterostructure, the unique two-step electric polarization switching covers up to 90% of the entire poled area and contributes to a homogeneous in-plane anisotropic biaxial strain, which, in turn, enables the lattice changes and results in the suppression of metal-insulator transition in the mechanically coupled VOx films by 6 K with a resistance change up to 40% over a broad range of temperature. These findings provide a framework for realizing in situ and non-volatile tuning of strain-sensitive order parameters in strongly correlated materials, and demonstrate great potentials in delivering reconfigurable, compactable, and energy-efficient electronic devices.

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...

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.

The combination of positive and negative feedback loops confers exquisite flexibility to biochemical switches

International Nuclear Information System (INIS)

Pfeuty, Benjamin; Kaneko, Kunihiko

2009-01-01

A wide range of cellular processes require molecular regulatory pathways to convert a graded signal into a discrete response. One prevalent switching mechanism relies on the coexistence of two stable states (bistability) caused by positive feedback regulations. Intriguingly, positive feedback is often supplemented with negative feedback, raising the question of whether and how these two types of feedback can cooperate to control discrete cellular responses. To address this issue, we formulate a canonical model of a protein–protein interaction network and analyze the dynamics of a prototypical two-component circuit. The appropriate combination of negative and positive feedback loops can bring a bistable circuit close to the oscillatory regime. Notably, sharply activated negative feedback can give rise to a bistable regime wherein two stable fixed points coexist and may collide pairwise with two saddle points. This specific type of bistability is found to allow for separate and flexible control of switch-on and switch-off events, for example (i) to combine fast and reversible transitions, (ii) to enable transient switching responses and (iii) to display tunable noise-induced transition rates. Finally, we discuss the relevance of such bistable switching behavior, and the circuit topologies considered, to specific biological processes such as adaptive metabolic responses, stochastic fate decisions and cell-cycle transitions. Taken together, our results suggest an efficient mechanism by which positive and negative feedback loops cooperate to drive the flexible and multifaceted switching behaviors arising in biological systems

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.

Experimental evidence for stochastic switching of supercooled phases in NdNiO3 nanostructures

Science.gov (United States)

Kumar, Devendra; Rajeev, K. P.; Alonso, J. A.

2018-03-01

A first-order phase transition is a dynamic phenomenon. In a multi-domain system, the presence of multiple domains of coexisting phases averages out the dynamical effects, making it nearly impossible to predict the exact nature of phase transition dynamics. Here, we report the metal-insulator transition in samples of sub-micrometer size NdNiO3 where the effect of averaging is minimized by restricting the number of domains under study. We observe the presence of supercooled metallic phases with supercooling of 40 K or more. The transformation from the supercooled metallic to the insulating state is a stochastic process that happens at different temperatures and times in different experimental runs. The experimental results are understood without incorporating material specific properties, suggesting that the behavior is of universal nature. The size of the sample needed to observe individual switching of supercooled domains, the degree of supercooling, and the time-temperature window of switching are expected to depend on the parameters such as quenched disorder, strain, and magnetic field.

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),

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)

Stochastic index model for intermittent regimes: from preliminary analysis to regionalisation

Directory of Open Access Journals (Sweden)

M. Rianna

2011-04-01

Full Text Available In small and medium-sized basins or in rivers characterized by intermittent discharges, with low or negligible/null observed values for long periods of the year, the correct representation of the discharge regime is important for issues related to water management and to define the amount and quality of water available for irrigation, domestic and recreational uses. In these cases, only one index as a statistical metric is often not enough; it is thus necessary to introduce Flow Duration Curves (FDC.

The aim of this study is therefore to combine a stochastic index flow model capable of reproducing the FDC record period of a river, regardless of the persistence and seasonality of the series, with the theory of total probability in order to calculate how often a river is dry.

The paper draws from preliminary analyses, including a study to estimate the correlation between discharge indicators Q₉₅, Q₅₀ and Q₁ (discharges exceeding 95%, 50% or 1% of the time, respectively and some fundamental characteristics of the basin, as well as to identify homogeneous regions in the target area through the study of several geo-morphological features and climatic conditions. The stochastic model was then applied in one of the homogeneous regions that includes intermittent rivers.

Finally, the model was regionalized by means of regression analysis in order to calculate the FDC for ungauged basins; the reliability of this method was tested using jack-knife validation.

Parallel superconducting strip-line detectors: reset behaviour in the single-strip switch regime

International Nuclear Information System (INIS)

Casaburi, A; Heath, R M; Tanner, M G; Hadfield, R H; Cristiano, R; Ejrnaes, M; Nappi, C

2014-01-01

Superconducting strip-line detectors (SSLDs) are an important emerging technology for the detection of single molecules in time-of-flight mass spectrometry (TOF-MS). We present an experimental investigation of a SSLD laid out in a parallel configuration, designed to address selected single strip-lines operating in the single-strip switch regime. Fast laser pulses were tightly focused onto the device, allowing controllable nucleation of a resistive region at a specific location and study of the subsequent device response dynamics. We observed that in this regime, although the strip-line returns to the superconducting state after triggering, no effective recovery of the bias current occurs, in qualitative agreement with a phenomenological circuit simulation that we performed. Moreover, from theoretical considerations and by looking at the experimental pulse amplitude distribution histogram, we have the first confirmation of the fact that the phenomenological London model governs the current redistribution in these large area devices also after detection events. (paper)

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.

Feasibility and limitations of anti-fuses based on bistable non-volatile switches for power electronic applications

Science.gov (United States)

Erlbacher, T.; Huerner, A.; Bauer, A. J.; Frey, L.

2012-09-01

Anti-fuse devices based on non-volatile memory cells and suitable for power electronic applications are demonstrated for the first time using silicon technology. These devices may be applied as stand alone devices or integrated using standard junction-isolation into application-specific and smart-power integrated circuits. The on-resistance of such devices can be permanently switched by nine orders of magnitude by triggering the anti-fuse with a positive voltage pulse. Extrapolation of measurement data and 2D TCAD process and device simulations indicate that 20 A anti-fuses with 10 mΩ can be reliably fabricated in 0.35 μm technology with a footprint of 2.5 mm2. Moreover, this concept offers distinguished added-values compared to existing mechanical relays, e.g. pre-test, temporary and permanent reset functions, gradual turn-on mode, non-volatility, and extendibility to high voltage capability.

Volatility Forecast in Crises and Expansions

Directory of Open Access Journals (Sweden)

Sergii Pypko

2015-08-01

Full Text Available We build a discrete-time non-linear model for volatility forecasting purposes. This model belongs to the class of threshold-autoregressive models, where changes in regimes are governed by past returns. The ability to capture changes in volatility regimes and using more accurate volatility measures allow outperforming other benchmark models, such as linear heterogeneous autoregressive model and GARCH specifications. Finally, we show how to derive closed-form expression for multiple-step-ahead forecasting by exploiting information about the conditional distribution of returns.

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)

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...

Stochastic interaction between TAE and alpha particles

International Nuclear Information System (INIS)

Krlin, L.; Pavlo, P.; Malijevsky, I.

1996-01-01

The interaction of toroidicity-induced Alfven eigenmodes with thermonuclear alpha particles in the intrinsic stochasticity regime was investigated based on the numerical integration of the equation of motion of alpha particles in the tokamak. The first results obtained for the ITER parameters and moderate wave amplitudes indicate that the stochasticity is highest in the trapped/passing boundary region, where the alpha particles jump stochastically between the two regimes with an appreciable radial excursion (about 0.5 m amplitudes). A similar chaotic behavior was also found for substantially lower energies (about 350 keV). 7 figs., 15 refs

Impact of variable renewable production on electricity prices in Germany: a Markov switching model

International Nuclear Information System (INIS)

Martin de Lagarde, Cyril; Lantz, Frederic

2016-01-01

This paper aims at assessing the impact of renewable energy sources (RES) production on electricity spot prices. To do so, we use a two-regime Markov Switching (MS) model, that enables to disentangle the so-called 'merit-order effect' due to wind and solar photovoltaic productions (used in relative share of the electricity demand), depending on the price being high or low. We find that there are effectively two distinct price regimes that are put to light thanks to an inverse hyperbolic sine transformation that allows to treat negative prices. We also show that these two regimes coincide quite well with two regimes for the electricity demand (load). Indeed, when demand is low, prices are low and the merit-order effect is lower than when prices are high, which is consistent with the fact that the inverse supply curve is convex (i.e. has increasing slope). To illustrate this, we computed the mean marginal effects of RES production and load. On average, an increase of 1 GW of wind will decrease the price in regime 1 (resp. 2) by 0.77 euro /MWh (resp. 1 euro /MWh). The influence of solar is slightly weaker, as an extra gigawatt lowers the price of 0.73 euro /MWh in period 1, and 0.96 euro /MWh in regime 2. On the contrary, if the demand increases by 1 GW in regime 1 (resp. 2), the price increases on average by 0.93 euro /MWh (resp. 1.18 euro /MWh). Although we made sure these marginal effects are significantly different from one another, they are much more variable than the estimated coefficients of the model. Also, note that these marginal effects are only valid inside each regime when there is no switching. The latter regime partly corresponds to the high load regime, at the exception of periods during which RES production is high. The impact on volatility could also be observed: the variance of the (transformed) price is higher during the high-price regime than in the low-price one. In addition to the switching of the coefficients, we allowed the probabilities of

Endogenous Monetary Policy Regime Change

OpenAIRE

Troy Davig; Eric M. Leeper

2006-01-01

This paper makes changes in monetary policy rules (or regimes) endogenous. Changes are triggered when certain endogenous variables cross specified thresholds. Rational expectations equilibria are examined in three models of threshold switching to illustrate that (i) expectations formation effects generated by the possibility of regime change can be quantitatively important; (ii) symmetric shocks can have asymmetric effects; (iii) endogenous switching is a natural way to formally model preempt...

Windows of opportunity for synchronization in stochastically coupled maps

Science.gov (United States)

Golovneva, Olga; Jeter, Russell; Belykh, Igor; Porfiri, Maurizio

2017-02-01

Several complex systems across science and engineering display on-off intermittent coupling among their units. Most of the current understanding of synchronization in switching networks relies on the fast switching hypothesis, where the network dynamics evolves at a much faster time scale than the individual units. Recent numerical evidence has demonstrated the existence of windows of opportunity, where synchronization may be induced through non-fast switching. Here, we study synchronization of coupled maps whose coupling gains stochastically switch with an arbitrary switching period. We determine the role of the switching period on synchronization through a detailed analytical treatment of the Lyapunov exponent of the stochastic dynamics. Through closed-form expressions and numerical findings, we demonstrate the emergence of windows of opportunity and elucidate their nontrivial relationship with the stability of synchronization under static coupling. Our results are expected to provide a rigorous basis for understanding the dynamic mechanisms underlying the emergence of windows of opportunity and leverage non-fast switching in the design of evolving networks.

Stochastic Eulerian Lagrangian methods for fluid-structure interactions with thermal fluctuations

International Nuclear Information System (INIS)

Atzberger, Paul J.

2011-01-01

We present approaches for the study of fluid-structure interactions subject to thermal fluctuations. A mixed mechanical description is utilized combining Eulerian and Lagrangian reference frames. We establish general conditions for operators coupling these descriptions. Stochastic driving fields for the formalism are derived using principles from statistical mechanics. The stochastic differential equations of the formalism are found to exhibit significant stiffness in some physical regimes. To cope with this issue, we derive reduced stochastic differential equations for several physical regimes. We also present stochastic numerical methods for each regime to approximate the fluid-structure dynamics and to generate efficiently the required stochastic driving fields. To validate the methodology in each regime, we perform analysis of the invariant probability distribution of the stochastic dynamics of the fluid-structure formalism. We compare this analysis with results from statistical mechanics. To further demonstrate the applicability of the methodology, we perform computational studies for spherical particles having translational and rotational degrees of freedom. We compare these studies with results from fluid mechanics. The presented approach provides for fluid-structure systems a set of rather general computational methods for treating consistently structure mechanics, hydrodynamic coupling, and thermal fluctuations.

A Stochastic Flows Approach for Asset Allocation with Hidden Economic Environment

Directory of Open Access Journals (Sweden)

Tak Kuen Siu

2015-01-01

Full Text Available An optimal asset allocation problem for a quite general class of utility functions is discussed in a simple two-state Markovian regime-switching model, where the appreciation rate of a risky share changes over time according to the state of a hidden economy. As usual, standard filtering theory is used to transform a financial model with hidden information into one with complete information, where a martingale approach is applied to discuss the optimal asset allocation problem. Using a martingale representation coupled with stochastic flows of diffeomorphisms for the filtering equation, the integrand in the martingale representation is identified which gives rise to an optimal portfolio strategy under some differentiability conditions.

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

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

Instability in time-delayed switched systems induced by fast and random switching

Science.gov (United States)

Guo, Yao; Lin, Wei; Chen, Yuming; Wu, Jianhong

2017-07-01

In this paper, we consider a switched system comprising finitely or infinitely many subsystems described by linear time-delayed differential equations and a rule that orchestrates the system switching randomly among these subsystems, where the switching times are also randomly chosen. We first construct a counterintuitive example where even though all the time-delayed subsystems are exponentially stable, the behaviors of the randomly switched system change from stable dynamics to unstable dynamics with a decrease of the dwell time. Then by using the theories of stochastic processes and delay differential equations, we present a general result on when this fast and random switching induced instability should occur and we extend this to the case of nonlinear time-delayed switched systems as well.

OUTPUT VOLATILITY AND EXCHANGE RATE CONSIDERATIONS UNDER INFLATION TARGETING : A REVIEW

Directory of Open Access Journals (Sweden)

Marjan Petreski

2012-01-01

Full Text Available The objective of the paper is to offer a critique on the theoretical and empirical literature on inflation targeting (IT. It seems to exist a consensus in the theoretical literature that this monetary regime reduces both inflation and output volatility, mainly through building monetary policy credibility. When the role of the exchange rate is discussed, while there are some arguments that, as an instrument, it should not be explicitly stated in the central-bank loss function, theoretical arguments and evidence are still mixed as regards the effectiveness of exchange-rate management under IT. On the empirical front, the paper concludes that despite the fact that the work on IT in the last two decades has been immense in quality and quantity, still there is no quantitatively-credible study for the developing world, let alone a study that appropriately measures the regime switch from one monetary strategy to another.

Multiperiod Telser’s Safety-First Portfolio Selection with Regime Switching

Directory of Open Access Journals (Sweden)

Chuangwei Lin

2018-01-01

Full Text Available This paper investigates a multiperiod Telser’s safety-first portfolio selection model with regime switching where the returns of the assets are assumed to depend on the market states modulated by a discrete-time Markov chain. The investor aims to maximize the expected terminal wealth and does not want the probability of the terminal wealth to fall short of a disaster level to exceed a predetermined number called the risk control level. Referring to Tchebycheff inequality, we modify Telser’s safety-first model to the case that aims to maximize the expected terminal wealth subject to a constraint where the upper bound of the disaster probability is less than the risk control level. By the Lagrange multiplier technique and the embedding method, we study in detail the existence of the optimal strategy and derive the closed-form optimal strategy. Finally, by mathematical and numerical analysis, we analyze the effects of the disaster level, the risk control level, the transition matrix of the Markov chain, the expected excess return, and the variance of the risky return.

Intra-day and regime-switching dynamics in electricity price formation

International Nuclear Information System (INIS)

Karakatsani, Nektaria V.; Bunn, Derek W.

2008-01-01

This paper analyses the complex, non-linear effects of spot price drivers in wholesale electricity markets: their intra-day dynamics and transient irregularities. The context is the UK market, after the reforms introduced in March 2001, analysed with an original set of price drivers reflecting economic, technical, strategic, risk, behavioural and market design effects. Models are estimated separately as daily time-series of the 48 half-hourly trading periods. All coefficients exhibit substantial intra-day variation, relating to the heterogeneity of operating plants and market design aspects. This reveals a market responding to economic fundamentals and plant operating properties, with learning and emergent financial characteristics, as well as some strategic manipulation of capacity, most effectively exercised by the more flexible plants. Using regime-switching parameters, the effects of capacity margin and inter-day capacity adjustment are elucidated, suggesting rent-seeking behaviour, despite the relatively low prices at the time. Overall, high-frequency, aggregate fundamental price models can usefully uncover critical aspects of market performance, evolution and agent behaviour. (author)

Dynamical Analysis of a Class of Prey-Predator Model with Beddington-DeAngelis Functional Response, Stochastic Perturbation, and Impulsive Toxicant Input

Directory of Open Access Journals (Sweden)

Feifei Bian

2017-01-01

Full Text Available A stochastic prey-predator system in a polluted environment with Beddington-DeAngelis functional response is proposed and analyzed. Firstly, for the system with white noise perturbation, by analyzing the limit system, the existence of boundary periodic solutions and positive periodic solutions is proved and the sufficient conditions for the existence of boundary periodic solutions and positive periodic solutions are derived. And then for the stochastic system, by introducing Markov regime switching, the sufficient conditions for extinction or persistence of such system are obtained. Furthermore, we proved that the system is ergodic and has a stationary distribution when the concentration of toxicant is a positive constant. Finally, two examples with numerical simulations are carried out in order to illustrate the theoretical results.

Memristors Empower Spiking Neurons With Stochasticity

KAUST Repository

Al-Shedivat, Maruan

2015-06-01

Recent theoretical studies have shown that probabilistic spiking can be interpreted as learning and inference in cortical microcircuits. This interpretation creates new opportunities for building neuromorphic systems driven by probabilistic learning algorithms. However, such systems must have two crucial features: 1) the neurons should follow a specific behavioral model, and 2) stochastic spiking should be implemented efficiently for it to be scalable. This paper proposes a memristor-based stochastically spiking neuron that fulfills these requirements. First, the analytical model of the memristor is enhanced so it can capture the behavioral stochasticity consistent with experimentally observed phenomena. The switching behavior of the memristor model is demonstrated to be akin to the firing of the stochastic spike response neuron model, the primary building block for probabilistic algorithms in spiking neural networks. Furthermore, the paper proposes a neural soma circuit that utilizes the intrinsic nondeterminism of memristive switching for efficient spike generation. The simulations and analysis of the behavior of a single stochastic neuron and a winner-take-all network built of such neurons and trained on handwritten digits confirm that the circuit can be used for building probabilistic sampling and pattern adaptation machinery in spiking networks. The findings constitute an important step towards scalable and efficient probabilistic neuromorphic platforms. © 2011 IEEE.

Interplay of cross-plane polaronic transport and resistive switching in Pt–Pr0.67Ca0.33MnO3–Pt heterostructures

International Nuclear Information System (INIS)

Scherff, M; Hoffmann, J; Meyer, B; Danz, Th; Jooss, Ch

2013-01-01

The identification of the cross-plane electric transport mechanisms in different resistance states of metal–oxide sandwich structures is essential for gaining insights into the mechanisms of resistive switching (RS). Here, we present a systematic study of cross-plane electric transport properties of Pr 0.67 Ca 0.33 MnO 3 (PCMO) thin films sandwiched by precious Pt metal electrodes. We observe three different transport regimes: ohmic, nonlinear and RS. The nonlinear regime is associated with colossal magneto-resistance (CMR) and colossal electro-resistance (CER) effects. In contrast to RS, the CMR and CER are volatile resistance effects which persist only during application of strong magnetic or electric fields and they are restricted to low temperatures. At low current densities, the device resistance is dominated by small polaron hopping transport of the PCMO film. At higher electric current densities near the switching threshold, the interface resistance starts to dominate and remarkably also exhibits thermally activated transport properties. Our studies also shed light onto the interplay of colossal resistance effects and RS: at low temperatures, RS can be only induced by reduction of the PCMO resistivity through CMR and CER. This clearly demonstrates the key role of the current density for controlling the amplitude of non-volatile resistive changes. Conversely, the CMR can be used as a probe for the switching induced changes in disorder and correlations. At small switching amplitudes, we observe slight changes in polaron activation energy which can be attributed to changes at the interface. If the switching amplitude exceeds 1000% and more, the CMR effect in the device can be reversibly changed. This indicates persistent changes in electronic or lattice structure of large regions within the PCMO film. (paper)

Option Pricing with a Levy-Type Stochastic Dynamic Model for Stock Price Process Under Semi-Markovian Structural Perturbations

Science.gov (United States)

2015-11-30

models ( Beckers 1980, Dupire 1997), the volatility depends on time and stock price through a deterministic func- tional. In both cases, in addition to...T1 ≤ T2 ≤ · · · ≤ Tn−1 are the regime switch- ing times caused by the semi-Markov process prior to t. For notational convenience, we denote θ−1 = θ0...of interest are currently being investigated: (1) an evaluation of the effects of the backward recurrence time, the sojourn time distribution and the

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

Front propagation and clustering in the stochastic nonlocal Fisher equation

Science.gov (United States)

Ganan, Yehuda A.; Kessler, David A.

2018-04-01

In this work, we study the problem of front propagation and pattern formation in the stochastic nonlocal Fisher equation. We find a crossover between two regimes: a steadily propagating regime for not too large interaction range and a stochastic punctuated spreading regime for larger ranges. We show that the former regime is well described by the heuristic approximation of the system by a deterministic system where the linear growth term is cut off below some critical density. This deterministic system is seen not only to give the right front velocity, but also predicts the onset of clustering for interaction kernels which give rise to stable uniform states, such as the Gaussian kernel, for sufficiently large cutoff. Above the critical cutoff, distinct clusters emerge behind the front. These same features are present in the stochastic model for sufficiently small carrying capacity. In the latter, punctuated spreading, regime, the population is concentrated on clusters, as in the infinite range case, which divide and separate as a result of the stochastic noise. Due to the finite interaction range, if a fragment at the edge of the population separates sufficiently far, it stabilizes as a new cluster, and the processes begins anew. The deterministic cutoff model does not have this spreading for large interaction ranges, attesting to its purely stochastic origins. We show that this mode of spreading has an exponentially small mean spreading velocity, decaying with the range of the interaction kernel.

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

Stability in distribution of a stochastic hybrid competitive Lotka–Volterra model with Lévy jumps

International Nuclear Information System (INIS)

Zhao, Yu; Yuan, Sanling

2016-01-01

Stability in distribution, implying the existence of the invariant probability measure, is an important measure of stochastic hybrid system. However, the effect of Lévy jumps on the stability in distribution is still unclear. In this paper, we consider a n-species competitive Lotka–Volterra model with Lévy jumps under regime-switching. First, we prove the existence of the global positive solution, obtain the upper and lower boundedness. Then, asymptotic stability in distribution as the main result of our paper is derived under some sufficient conditions. Finally, numerical simulations are carried out to support our theoretical results and a brief discussion is given.

Enhancement of resistive switching properties in Al2O3 bilayer-based atomic switches: multilevel resistive switching

Science.gov (United States)

Vishwanath, Sujaya Kumar; Woo, Hyunsuk; Jeon, Sanghun

2018-06-01

Atomic switches are considered to be building blocks for future non-volatile data storage and internet of things. However, obtaining device structures capable of ultrahigh density data storage, high endurance, and long data retention, and more importantly, understanding the switching mechanisms are still a challenge for atomic switches. Here, we achieved improved resistive switching performance in a bilayer structure containing aluminum oxide, with an oxygen-deficient oxide as the top switching layer and stoichiometric oxide as the bottom switching layer, using atomic layer deposition. This bilayer device showed a high on/off ratio (105) with better endurance (∼2000 cycles) and longer data retention (104 s) than single-oxide layers. In addition, depending on the compliance current, the bilayer device could be operated in four different resistance states. Furthermore, the depth profiles of the hourglass-shaped conductive filament of the bilayer device was observed by conductive atomic force microscopy.

Switching between Domestic Market Activity, Export and FDI

DEFF Research Database (Denmark)

Hiller, Sanne; Yalcin, Erdal

-concentration trade-off with a stochastic productivity evolution, we analyze the transition dynamics between domestic market serving, exporting and FDI. We find that a stochastic productivity development generates hysteresis, and thereby confirm a general real option result. Market serving mode switching is driven...

Is a more stable exchange rate associated with reduced exchange rate pass-through?

OpenAIRE

Mark J. Holmes

2007-01-01

Pass-through from the nominal effective exchange rate to import prices is modelled within a regime-switching environment. Evidence suggests that exchange rate pass through can be characterised as regime-specific where the probability of switching between regimes is influenced by the extent of exchange rate volatility.

Tunable optical switching in the near-infrared spectral regime by employing plasmonic nanoantennas containing phase change materials.

Science.gov (United States)

Savaliya, Priten B; Thomas, Arun; Dua, Rishi; Dhawan, Anuj

2017-10-02

We propose the design of switchable plasmonic nanoantennas (SPNs) that can be employed for optical switching in the near-infrared regime. The proposed SPNs consist of nanoantenna structures made up of a plasmonic metal (gold) such that these nanoantennas are filled with a switchable material (vanadium dioxide). We compare the results of these SPNs with inverted SPN structures that consist of gold nanoantenna structures surrounded by a layer of vanadium dioxide (VO 2 ) on their outer surface. These nanoantennas demonstrate switching of electric-field intensity enhancement (EFIE) between two states (On and Off states), which can be induced thermally, optically or electrically. The On and Off states of the nanoantennas correspond to the metallic and semiconductor states, respectively of the VO 2 film inside or around the nanoantennas, as the VO 2 film exhibits phase transition from its semiconductor state to the metallic state upon application of thermal, optical, or electrical energy. We employ finite-difference time-domain (FDTD) simulations to demonstrate switching in the EFIE for four different SPN geometries - nanorod-dipole, bowtie, planar trapezoidal toothed log-periodic, and rod-disk - and compare their near-field distributions for the On and Off states of the SPNs. We also demonstrate that the resonance wavelength of the EFIE spectra gets substantially modified when these SPNs switch between the two states.

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...

Stochasticity induced by coherent wavepackets

International Nuclear Information System (INIS)

Fuchs, V.; Krapchev, V.; Ram, A.; Bers, A.

1983-02-01

We consider the momentum transfer and diffusion of electrons periodically interacting with a coherent longitudinal wavepacket. Such a problem arises, for example, in lower-hybrid current drive. We establish the stochastic threshold, the stochastic region δv/sub stoch/ in velocity space, the associated momentum transfer j, and the diffusion coefficient D. We concentrate principally on the weak-field regime, tau/sub autocorrelation/ < tau/sub bounce/

Stochastic efficiency: five case studies

International Nuclear Information System (INIS)

Proesmans, Karel; Broeck, Christian Van den

2015-01-01

Stochastic efficiency is evaluated in five case studies: driven Brownian motion, effusion with a thermo-chemical and thermo-velocity gradient, a quantum dot and a model for information to work conversion. The salient features of stochastic efficiency, including the maximum of the large deviation function at the reversible efficiency, are reproduced. The approach to and extrapolation into the asymptotic time regime are documented. (paper)

Inertia in strategy switching transforms the strategy evolution.

Science.gov (United States)

Zhang, Yanling; Fu, Feng; Wu, Te; Xie, Guangming; Wang, Long

2011-12-01

A recent experimental study [Traulsen et al., Proc. Natl. Acad. Sci. 107, 2962 (2010)] shows that human strategy updating involves both direct payoff comparison and the cost of switching strategy, which is equivalent to inertia. However, it remains largely unclear how such a predisposed inertia affects 2 × 2 games in a well-mixed population of finite size. To address this issue, the "inertia bonus" (strategy switching cost) is added to the learner payoff in the Fermi process. We find how inertia quantitatively shapes the stationary distribution and that stochastic stability under inertia exhibits three regimes, with each covering seven regions in the plane spanned by two inertia parameters. We also obtain the extended "1/3" rule with inertia and the speed criterion with inertia; these two findings hold for a population above two. We illustrate the above results in the framework of the Prisoner's Dilemma game. As inertia varies, two intriguing stationary distributions emerge: the probability of coexistence state is maximized, or those of two full states are simultaneously peaked. Our results may provide useful insights into how the inertia of changing status quo acts on the strategy evolution and, in particular, the evolution of cooperation.

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 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...

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)

Characterization of exchange rate regimes based on scaling and correlation properties of volatility for ASEAN-5 countries

Science.gov (United States)

Muniandy, Sithi V.; Uning, Rosemary

2006-11-01

Foreign currency exchange rate policies of ASEAN member countries have undergone tremendous changes following the 1997 Asian financial crisis. In this paper, we study the fractal and long-memory characteristics in the volatility of five ASEAN founding members’ exchange rates with respect to US dollar. The impact of exchange rate policies implemented by the ASEAN-5 countries on the currency fluctuations during pre-, mid- and post-crisis are briefly discussed. The time series considered are daily price returns, absolute returns and aggregated absolute returns, each partitioned into three segments based on the crisis regimes. These time series are then modeled using fractional Gaussian noise, fractionally integrated ARFIMA (0,d,0) and generalized Cauchy process. The first two stationary models provide the description of long-range dependence through Hurst and fractional differencing parameter, respectively. Meanwhile, the generalized Cauchy process offers independent estimation of fractal dimension and long memory exponent. In comparison, among the three models we found that the generalized Cauchy process showed greater sensitivity to transition of exchange rate regimes that were implemented by ASEAN-5 countries.

Stochastic learning in oxide binary synaptic device for neuromorphic computing.

Science.gov (United States)

Yu, Shimeng; Gao, Bin; Fang, Zheng; Yu, Hongyu; Kang, Jinfeng; Wong, H-S Philip

2013-01-01

Hardware implementation of neuromorphic computing is attractive as a computing paradigm beyond the conventional digital computing. In this work, we show that the SET (off-to-on) transition of metal oxide resistive switching memory becomes probabilistic under a weak programming condition. The switching variability of the binary synaptic device implements a stochastic learning rule. Such stochastic SET transition was statistically measured and modeled for a simulation of a winner-take-all network for competitive learning. The simulation illustrates that with such stochastic learning, the orientation classification function of input patterns can be effectively realized. The system performance metrics were compared between the conventional approach using the analog synapse and the approach in this work that employs the binary synapse utilizing the stochastic learning. The feasibility of using binary synapse in the neurormorphic computing may relax the constraints to engineer continuous multilevel intermediate states and widens the material choice for the synaptic device design.

Conductive graphene as passive saturable absorber with high instantaneous peak power and pulse energy in Q-switched regime

Science.gov (United States)

Zuikafly, Siti Nur Fatin; Khalifa, Ali; Ahmad, Fauzan; Shafie, Suhaidi; Harun, SulaimanWadi

2018-06-01

The Q-switched pulse regime is demonstrated by integrating conductive graphene as passive saturable absorber producing relatively high instantaneous peak power and pulse energy. The fabricated conductive graphene is investigated using Raman spectroscopy. The single wavelength Q-switching operates at 1558.28 nm at maximum input pump power of 151.47 mW. As the pump power is increased from threshold power of 51.6 mW to 151.47 mW, the pulse train repetition rate increases proportionally from 47.94 kHz to 67.8 kHz while the pulse width is reduced from 9.58 μs to 6.02 μs. The generated stable pulse produced maximum peak power and pulse energy of 32 mW and 206 nJ, respectively. The first beat node of the measured signal-to-noise ratio is about 62 dB indicating high pulse stability.

Complementary and bipolar regimes of resistive switching in TiN/HfO{sub 2}/TiN stacks grown by atomic-layer deposition

Energy Technology Data Exchange (ETDEWEB)

Egorov, K.V.; Kirtaev, R.V.; Markeev, A.M.; Zablotskiy, A.V. [Moscow Institute of Physics and Technology, Institutskii per. 9, 141700, Dolgoprudny (Russian Federation); Lebedinskii, Yu.Yu.; Matveyev, Yu.A.; Zenkevich, A.V. [Moscow Institute of Physics and Technology, Institutskii per. 9, 141700, Dolgoprudny (Russian Federation); National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Kashirskoye shosse 31, 115409, Moscow (Russian Federation); Orlov, O.M. [Scientific Research Institute of Molecular Electronics and Plant ' ' Micron' ' , 124462, Zelenograd (Russian Federation)

2015-04-01

Atomic-layer deposition (ALD) technique in combination with in vacuo X-ray photoelectron spectroscopy (XPS) analysis has been successfully employed to obtain fully ALD-grown planar TiN/HfO{sub 2}/TiN metal-insulator-metal structures for resistive random access memory (ReRAM) memory elements. In vacuo XPS analysis of ALD-grown TiN/HfO{sub 2}/TiN stacks reveals the presence of the ultrathin oxidized layers consisting of TiON (∝0.5 nm) and TiO{sub 2} (∝0.6 nm) at the bottom TiN/HfO{sub 2} interface (i); the nonoxidized TiN at the top HfO{sub 2}/TiN interface (ii); the oxygen deficiency in the HfO{sub 2} layer does not exceed the XPS detection limit (iii). Electroformed ALD TiN/HfO{sub 2}/TiN stacks reveal both conventional bipolar and complementary types of resistive switching. In the complementary resistive switching regime, each programming sequence is terminated by a reset operation, leaving the TiN/HfO{sub 2}/TiN stack in a high-resistance state. The observed feature can avoid detrimental leaky paths during successive reading operation, which is useful in the passive ReRAM arrays without a selector element. The bipolar regime of resistive switching is found to reveal the gradual character of the SET and RESET switching processes. Long-term potentiation and depression tests performed on ALD-grown TiN/HfO{sub 2}/TiN stacks indicate that they can be used as electronic synapse devices for the implementation of emerging neuromorphic computation systems. (copyright 2015 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

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.

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.

Stochastic Optimal Control for Online Seller under Reputational Mechanisms

Directory of Open Access Journals (Sweden)

Milan Bradonjić

2015-12-01

Full Text Available In this work we propose and analyze a model which addresses the pulsing behavior of sellers in an online auction (store. This pulsing behavior is observed when sellers switch between advertising and processing states. We assert that a seller switches her state in order to maximize her profit, and further that this switch can be identified through the seller’s reputation. We show that for each seller there is an optimal reputation, i.e., the reputation at which the seller should switch her state in order to maximize her total profit. We design a stochastic behavioral model for an online seller, which incorporates the dynamics of resource allocation and reputation. The design of the model is optimized by using a stochastic advertising model from [1] and used effectively in the Stochastic Optimal Control of Advertising [2]. This model of reputation is combined with the effect of online reputation on sales price empirically verified in [3]. We derive the Hamilton-Jacobi-Bellman (HJB differential equation, whose solution relates optimal wealth level to a seller’s reputation. We formulate both a full model, as well as a reduced model with fewer parameters, both of which have the same qualitative description of the optimal seller behavior. Coincidentally, the reduced model has a closed form analytical solution that we construct.

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)

QB1 - Stochastic Gene Regulation

Energy Technology Data Exchange (ETDEWEB)

Munsky, Brian [Los Alamos National Laboratory

2012-07-23

Summaries of this presentation are: (1) Stochastic fluctuations or 'noise' is present in the cell - Random motion and competition between reactants, Low copy, quantization of reactants, Upstream processes; (2) Fluctuations may be very important - Cell-to-cell variability, Cell fate decisions (switches), Signal amplification or damping, stochastic resonances; and (3) Some tools are available to mode these - Kinetic Monte Carlo simulations (SSA and variants), Moment approximation methods, Finite State Projection. We will see how modeling these reactions can tell us more about the underlying processes of gene regulation.

Infinite stochastic acceleration of charged particles from non-relativistic initial energies

International Nuclear Information System (INIS)

Buts, V.A.; Manujlenko, O.V.; Turkin, Yu.A.

1997-01-01

Stochastic charged particle acceleration by electro-magnetic field due to overlapping of non-linear cyclotron resonances is considered. It was shown that non-relativistic charged particles are involved in infinitive stochastic acceleration regime. This effect can be used for stochastic acceleration or for plasma heating by regular electro-magnetic fields

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.

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.

Theoretical and experimental study of stochastic effects on polarization rotation in a vectorial bistable laser

International Nuclear Information System (INIS)

Singh, Kamal P.; Ropars, Guy; Brunel, Marc; Le Floch, Albert

2006-01-01

We investigate the two-dimensional optical rotor of a weakly modulated vectorial bistable laser submitted to a single or multiple stochastic perturbations. In the Langevin-type equation of the rotor the role of an even or odd input forcing function on the system dynamics is isolated. Through these two inputs of optical and magnetic natures we verify that the stochastic resonance exists only when the periodic modulation acts on the even parity optical input. When two mutually correlated noises are simultaneously submitted to the input functions of opposite parities, we find a critical regime of the noise interplay whereby one stable state becomes noise-free. In this case, the residence time of the light vector in the noise-free state diverges which leads to a collapse of the output signal-to-noise ratio. But, in this critical regime also obtained when one noise drives both the even and odd functions, if the system symmetry is broken through an independent lever control, we can recover the switching cycle due to a new response mechanism, namely, the dual stochastic response, with a specific output signal-to-noise ratio expression. Both the theoretical analysis and the experiment show that the signal-to-noise ratio now displays a robust behavior for a large range of the input noise amplitude, and a plateau with respect to the input signal amplitude. Furthermore, we isolate an original signature of this synchronization mechanism in the residence-time distribution leading to a broadband forcing frequency range. These noise interplay effects in a double well potential are of generic nature and could be found in other nonlinear systems

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.

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.

SLUG-STOCHASTICALLY LIGHTING UP GALAXIES. I. METHODS AND VALIDATING TESTS

Energy Technology Data Exchange (ETDEWEB)

Da Silva, Robert L.; Fumagalli, Michele; Krumholz, Mark [Department of Astronomy and Astrophysics, UCO/Lick Observatory, University of California, 1156 High Street, Santa Cruz, CA 95064 (United States)

2012-02-01

The effects of stochasticity on the luminosities of stellar populations are an often neglected but crucial element for understanding populations in the low-mass or the low star formation rate regime. To address this issue, we present SLUG, a new code to 'Stochastically Light Up Galaxies'. SLUG synthesizes stellar populations using a Monte Carlo technique that properly treats stochastic sampling including the effects of clustering, the stellar initial mass function, star formation history, stellar evolution, and cluster disruption. This code produces many useful outputs, including (1) catalogs of star clusters and their properties such as their stellar initial mass distributions and their photometric properties in a variety of filters, (2) two dimensional histograms of color-magnitude diagrams of every star in the simulation, and (3) the photometric properties of field stars and the integrated photometry of the entire simulated galaxy. After presenting the SLUG algorithm in detail, we validate the code through comparisons with STARBURST99 in the well-sampled regime, and with observed photometry of Milky Way clusters. Finally, we demonstrate SLUG's capabilities by presenting outputs in the stochastic regime. SLUG is publicly distributed through the Web site http://sites.google.com/site/runslug/.

Oil shock transmission to stock market returns: Wavelet-multivariate Markov switching GARCH approach

International Nuclear Information System (INIS)

Jammazi, Rania

2012-01-01

Since oil prices are typically governed by nonlinear and chaotic behavior, it’s become rather difficult to capture the dominant properties of their fluctuations. In recent years, unprecedented interest emerged on the decomposition methods in order to capture drifts or spikes relatively to this data. Together, our understanding of the nature of crude oil price shocks and their effects on the stock market returns has evolved noticeably. We accommodate these findings to investigate two issues that have been at the center of recent debates on the effect of crude oil shocks on the stock market returns of five developed countries (USA, UK, Japan, Germany and Canada). First, we analyze whether shocks and or volatility emanating from two major crude oil markets are transmitted to the equity markets. We do this by applying, the Haar A Trous Wavelet decomposition to monthly real crude oil series in a first step, and the trivariate BEKK Markov Switching GARCH model to analyze the effect of the smooth part on the degree of the stock market instability in a second step. The motivation behind the use of the former method is that noises and erratic behavior often appeared at the edge of the signal, can affect the quality of the shock and thus increase erroneous results of the shock transmission to the stock market. The proposed model is able to circumvent the path dependency problem that can influence the prediction’s robustness and can provide useful information for investors and government agencies that have largely based their views on the notion that crude oil markets affect negatively stock market returns. Second, under the hypothesis of common increased volatility, we investigate whether these states happen around the identified international crises. Indeed, the results show that the A Haar Trous Wavelet decomposition method appears to be an important step toward improving accuracy of the smooth signal in detecting key real crude oil volatility features. Additionally

Multiple growth regimes: Insights from unified growth theory

OpenAIRE

Galor, Oded

2007-01-01

Unified Growth Theory uncovers the forces that contributed to the existence of multiple growth regimes and the emergence of convergence clubs. It suggests that differential timing of take-offs from stagnation to growth segmented economies into three fundamental regimes: slow growing economies in a Malthusian regime, fast growing countries in a sustained growth regime, and economies in the transition between these regimes. In contrast to existing research that links regime switching thresholds...

Organic non-volatile memories from ferroelectric phase-separated blends

Science.gov (United States)

Asadi, Kamal; de Leeuw, Dago M.; de Boer, Bert; Blom, Paul W. M.

2008-07-01

New non-volatile memories are being investigated to keep up with the organic-electronics road map. Ferroelectric polarization is an attractive physical property as the mechanism for non-volatile switching, because the two polarizations can be used as two binary levels. However, in ferroelectric capacitors the read-out of the polarization charge is destructive. The functionality of the targeted memory should be based on resistive switching. In inorganic ferroelectrics conductivity and ferroelectricity cannot be tuned independently. The challenge is to develop a storage medium in which the favourable properties of ferroelectrics such as bistability and non-volatility can be combined with the beneficial properties provided by semiconductors such as conductivity and rectification. Here we present an integrated solution by blending semiconducting and ferroelectric polymers into phase-separated networks. The polarization field of the ferroelectric modulates the injection barrier at the semiconductor-metal contact. The combination of ferroelectric bistability with (semi)conductivity and rectification allows for solution-processed non-volatile memory arrays with a simple cross-bar architecture that can be read out non-destructively. The concept of an electrically tunable injection barrier as presented here is general and can be applied to other electronic devices such as light-emitting diodes with an integrated on/off switch.

Theoretical and experimental investigations of stochastic boundaries in tokamaks

International Nuclear Information System (INIS)

Ghendrih, Ph.; Grosman, A.; Capes, H.

1996-01-01

The physics of stochastic boundaries are reviewed. The stochastic properties of magnetic field lines are recalled and related to the spectrum of the radial magnetic perturbation. The stochastic region, referred to as the divertor volume, is shown to be bounded to the edge plasma. Theoretical predictions for the transport of energy, current and particles in the divertor volume are analysed for both the laminar and ergodic regimes. (K.A.)

The impact of the North American shale gas revolution on regional natural gas markets: Evidence from the regime-switching model

International Nuclear Information System (INIS)

Geng, Jiang-Bo; Ji, Qiang; Fan, Ying

2016-01-01

This paper investigates the impact of the North American shale gas revolution on price movement regimes in the North American and European gas markets, using the Markov regime-switching model. It then measures price spreads between oil and gas from 1998 to 2015 to identify the impact of the revolution on the relationship between oil and regional gas prices. The results show that the typical movement regime of Henry Hub prices changes from 'slightly upward' to 'sharply downward'. In addition, the clear seasonal effect of Henry Hub prices has disappeared after the shale gas revolution. The typical movement of national balancing point (NBP) prices has changed gradually from a 'sharply upward' regime to the alternative regimes between 'sharply downward' and 'slightly upward', tending to follow oil prices. This indicates that the shale gas revolution has had little impact on NBP price movement. Meanwhile, Henry Hub prices have decoupled from WTI prices, while NBP and Brent prices have continued to exhibit a long-term equilibrium level around which they have swung in the short time-frame since the shale gas revolution. Pertinent energy policy makers and energy market participants should pay attention to these changes and adjust their trade, production and investment strategies accordingly. - Highlights: •Impact of shale gas revolution on Henry Hub and NBP price movement regime is analysed. •Impact of revolution on relationship between oil and regional gas price is identified. •Revolution changes Henry Hub movement regime, having minor impact on NBP regime. •Clear seasonal fluctuation of Henry Hub prices has disappeared since the revolution. •Henry Hub has decoupled from WTI, while NBP and Brent exhibit long-term equilibrium.

A regime-switching copula approach to modeling day-ahead prices in coupled electricity markets

DEFF Research Database (Denmark)

Pircalabu, Anca; Benth, Fred Espen

2017-01-01

significant evidence of tail dependence in all pairs of interconnected areas we consider. As a first application of the proposed model, we consider the pricing of financial transmission rights, and highlight how the choice of marginal distributions and copula impacts prices. As a second application we......The recent price coupling of many European electricity markets has triggered a fundamental change in the interaction of day-ahead prices, challenging additionally the modeling of the joint behavior of prices in interconnected markets. In this paper we propose a regime-switching AR–GARCH copula...... to model pairs of day-ahead electricity prices in coupled European markets. While capturing key stylized facts empirically substantiated in the literature, this model easily allows us to 1) deviate from the assumption of normal margins and 2) include a more detailed description of the dependence between...

Demonstration of Ultra-Fast Switching in Nano metallic Resistive Switching Memory Devices

International Nuclear Information System (INIS)

Yang, Y.

2016-01-01

Interdependency of switching voltage and time creates a dilemma/obstacle for most resistive switching memories, which indicates low switching voltage and ultra-fast switching time cannot be simultaneously achieved. In this paper, an ultra-fast (sub-100 ns) yet low switching voltage resistive switching memory device (“nano metallic ReRAM”) was demonstrated. Experimental switching voltage is found independent of pulse width (intrinsic device property) when the pulse is long but shows abrupt time dependence (“cliff”) as pulse width approaches characteristic RC time of memory device (extrinsic device property). Both experiment and simulation show that the onset of cliff behavior is dependent on physical device size and parasitic resistance, which is expected to diminish as technology nodes shrink down. We believe this study provides solid evidence that nano metallic resistive switching memory can be reliably operated at low voltage and ultra-fast regime, thus beneficial to future memory technology.

Organic non-volatile memories from ferroelectric phase separated blends

Science.gov (United States)

Asadi, Kamal; de Leeuw, Dago; de Boer, Bert; Blom, Paul

2009-03-01

Ferroelectric polarisation is an attractive physical property for non-volatile binary switching. The functionality of the targeted memory should be based on resistive switching. Conductivity and ferroelectricity however cannot be tuned independently. The challenge is to develop a storage medium in which the favourable properties of ferroelectrics such as bistability and non-volatility can be combined with the beneficial properties provided by semiconductors such as conductivity and rectification. In this contribution we present an integrated solution by blending semiconducting and ferroelectric polymers into phase separated networks. The polarisation field of the ferroelectric modulates the injection barrier at the semiconductor--metal contact. This combination allows for solution-processed non-volatile memory arrays with a simple cross-bar architecture that can be read-out non-destructively. Based on this general concept a non-volatile, reversible switchable Schottky diode with relatively fast programming time of shorter than 100 microseconds, long information retention time of longer than 10^ days, and high programming cycle endurance with non-destructive read-out is demonstrated.

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)

Intrinsic nanofilamentation in resistive switching

KAUST Repository

Wu, Xing; Cha, Dong Kyu; Bosman, Michel; Raghavan, Nagarajan; Migas, Dmitri B.; Borisenko, Victor E.; Zhang, Xixiang; Li, Kun; Pey, Kin-Leong

2013-01-01

-chip circuitry and non-volatile memory storage. Here, we provide insight into the mechanisms that govern highly reproducible controlled resistive switching via a nanofilament by using an asymmetric metal-insulator-semiconductor structure. In-situ transmission

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.

Stochastic model of energetic nuclear reactor

International Nuclear Information System (INIS)

Bojko, R.V.; Ryazanov, V.V.

2002-01-01

Behaviour of nuclear reactor was treated using the theory of branching processes. As mathematical model descriptive the neutron number in time the Markov occasional process is proposed. Application of branching occasional processes with variable regime to the description of neutron behaviour in the reactor makes possible conducting strong description of critical operation regime and demonstrates the severity of the process. Three regimes of the critical behaviour depending on the sign of manipulated variables and feedbacks were discovered. Probability regularities peculiar to the behaviour of the reactor are embodied to the suggested stochastic model [ru

Stochastic Strategy Adjustment in Coordination Games

NARCIS (Netherlands)

Kosfeld, M.

1999-01-01

We explore a model of equilibrium selection in coordination games, where agents stochastically adjust their strategies to changes in their local environment. Instead of playing perturbed best-response, we assume that agents follow a rule of "switching to better strategies more likely". We relate

Single-particle stochastic heat engine

Science.gov (United States)

Rana, Shubhashis; Pal, P. S.; Saha, Arnab; Jayannavar, A. M.

2014-10-01

We have performed an extensive analysis of a single-particle stochastic heat engine constructed by manipulating a Brownian particle in a time-dependent harmonic potential. The cycle consists of two isothermal steps at different temperatures and two adiabatic steps similar to that of a Carnot engine. The engine shows qualitative differences in inertial and overdamped regimes. All the thermodynamic quantities, including efficiency, exhibit strong fluctuations in a time periodic steady state. The fluctuations of stochastic efficiency dominate over the mean values even in the quasistatic regime. Interestingly, our system acts as an engine provided the temperature difference between the two reservoirs is greater than a finite critical value which in turn depends on the cycle time and other system parameters. This is supported by our analytical results carried out in the quasistatic regime. Our system works more reliably as an engine for large cycle times. By studying various model systems, we observe that the operational characteristics are model dependent. Our results clearly rule out any universal relation between efficiency at maximum power and temperature of the baths. We have also verified fluctuation relations for heat engines in time periodic steady state.

Investigation of Random Switching Driven by a Poisson Point Process

DEFF Research Database (Denmark)

Simonsen, Maria; Schiøler, Henrik; Leth, John-Josef

2015-01-01

This paper investigates the switching mechanism of a two-dimensional switched system, when the switching events are generated by a Poisson point process. A model, in the shape of a stochastic process, for such a system is derived and the distribution of the trajectory's position is developed...... together with marginal density functions for the coordinate functions. Furthermore, the joint probability distribution is given explicitly....

A graphene-based non-volatile memory

Science.gov (United States)

Loisel, Loïc.; Maurice, Ange; Lebental, Bérengère; Vezzoli, Stefano; Cojocaru, Costel-Sorin; Tay, Beng Kang

2015-09-01

We report on the development and characterization of a simple two-terminal non-volatile graphene switch. After an initial electroforming step during which Joule heating leads to the formation of a nano-gap impeding the current flow, the devices can be switched reversibly between two well-separated resistance states. To do so, either voltage sweeps or pulses can be used, with the condition that VSET achieve reversible switching on more than 100 cycles with resistance ratio values of 104. This approach of graphene memory is competitive as compared to other graphene approaches such as redox of graphene oxide, or electro-mechanical switches with suspended graphene. We suggest a switching model based on a planar electro-mechanical switch, whereby electrostatic, elastic and friction forces are competing to switch devices ON and OFF, and the stability in the ON state is achieved by the formation of covalent bonds between the two stretched sides of the graphene, hence bridging the nano-gap. Developing a planar electro-mechanical switch enables to obtain the advantages of electro-mechanical switches while avoiding most of their drawbacks.

Switching Phenomena in a System with No Switches

Science.gov (United States)

Preis, Tobias; Stanley, H. Eugene

2010-02-01

It is widely believed that switching phenomena require switches, but this is actually not true. For an intriguing variety of switching phenomena in nature, the underlying complex system abruptly changes from one state to another in a highly discontinuous fashion. For example, financial market fluctuations are characterized by many abrupt switchings creating increasing trends ("bubble formation") and decreasing trends ("financial collapse"). Such switching occurs on time scales ranging from macroscopic bubbles persisting for hundreds of days to microscopic bubbles persisting only for a few seconds. We analyze a database containing 13,991,275 German DAX Future transactions recorded with a time resolution of 10 msec. For comparison, a database providing 2,592,531 of all S&P500 daily closing prices is used. We ask whether these ubiquitous switching phenomena have quantifiable features independent of the time horizon studied. We find striking scale-free behavior of the volatility after each switching occurs. We interpret our findings as being consistent with time-dependent collective behavior of financial market participants. We test the possible universality of our result by performing a parallel analysis of fluctuations in transaction volume and time intervals between trades. We show that these financial market switching processes have properties similar to those of phase transitions. We suggest that the well-known catastrophic bubbles that occur on large time scales—such as the most recent financial crisis—are no outliers but single dramatic representatives caused by the switching between upward and downward trends on time scales varying over nine orders of magnitude from very large (≈102 days) down to very small (≈10 ms).

VAAs as sources of volatility and fragmentation: self-selection effects and genuine effects

NARCIS (Netherlands)

Kleinnijenhuis, J.; van de Pol, J.; van Hoof, A.; Krouwel, A.

2017-01-01

Recent studies show that using Voting Advice Applications (VAAs) affects party preferences of voters, and hence leads to party switching. Party switching is a necessary but insufficient condition for volatility (a net switch of voters to other parties) and fragmentation (more parties gaining seats)

Circuit-Host Coupling Induces Multifaceted Behavioral Modulations of a Gene Switch.

Science.gov (United States)

Blanchard, Andrew E; Liao, Chen; Lu, Ting

2018-02-06

Quantitative modeling of gene circuits is fundamentally important to synthetic biology, as it offers the potential to transform circuit engineering from trial-and-error construction to rational design and, hence, facilitates the advance of the field. Currently, typical models regard gene circuits as isolated entities and focus only on the biochemical processes within the circuits. However, such a standard paradigm is getting challenged by increasing experimental evidence suggesting that circuits and their host are intimately connected, and their interactions can potentially impact circuit behaviors. Here we systematically examined the roles of circuit-host coupling in shaping circuit dynamics by using a self-activating gene switch as a model circuit. Through a combination of deterministic modeling, stochastic simulation, and Fokker-Planck equation formalism, we found that circuit-host coupling alters switch behaviors across multiple scales. At the single-cell level, it slows the switch dynamics in the high protein production regime and enlarges the difference between stable steady-state values. At the population level, it favors cells with low protein production through differential growth amplification. Together, the two-level coupling effects induce both quantitative and qualitative modulations of the switch, with the primary component of the effects determined by the circuit's architectural parameters. This study illustrates the complexity and importance of circuit-host coupling in modulating circuit behaviors, demonstrating the need for a new paradigm-integrated modeling of the circuit-host system-for quantitative understanding of engineered gene networks. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Atomic switch: atom/ion movement controlled devices for beyond von-neumann computers.

Science.gov (United States)

Hasegawa, Tsuyoshi; Terabe, Kazuya; Tsuruoka, Tohru; Aono, Masakazu

2012-01-10

An atomic switch is a nanoionic device that controls the diffusion of metal ions/atoms and their reduction/oxidation processes in the switching operation to form/annihilate a conductive path. Since metal atoms can provide a highly conductive channel even if their cluster size is in the nanometer scale, atomic switches may enable downscaling to smaller than the 11 nm technology node, which is a great challenge for semiconductor devices. Atomic switches also possess novel characteristics, such as high on/off ratios, very low power consumption and non-volatility. The unique operating mechanisms of these devices have enabled the development of various types of atomic switch, such as gap-type and gapless-type two-terminal atomic switches and three-terminal atomic switches. Novel functions, such as selective volatile/nonvolatile, synaptic, memristive, and photo-assisted operations have been demonstrated. Such atomic switch characteristics can not only improve the performance of present-day electronic systems, but also enable development of new types of electronic systems, such as beyond von- Neumann computers. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Unipolar resistive switching in metal oxide/organic semiconductor non-volatile memories as a critical phenomenon

International Nuclear Information System (INIS)

Bory, Benjamin F.; Meskers, Stefan C. J.; Rocha, Paulo R. F.; Gomes, Henrique L.; Leeuw, Dago M. de

2015-01-01

Diodes incorporating a bilayer of an organic semiconductor and a wide bandgap metal oxide can show unipolar, non-volatile memory behavior after electroforming. The prolonged bias voltage stress induces defects in the metal oxide with an areal density exceeding 10 17  m −2 . We explain the electrical bistability by the coexistence of two thermodynamically stable phases at the interface between an organic semiconductor and metal oxide. One phase contains mainly ionized defects and has a low work function, while the other phase has mainly neutral defects and a high work function. In the diodes, domains of the phase with a low work function constitute current filaments. The phase composition and critical temperature are derived from a 2D Ising model as a function of chemical potential. The model predicts filamentary conduction exhibiting a negative differential resistance and nonvolatile memory behavior. The model is expected to be generally applicable to any bilayer system that shows unipolar resistive switching

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

The two-regime method for optimizing stochastic reaction-diffusion simulations

KAUST Repository

Flegg, M. B.; Chapman, S. J.; Erban, R.

2011-01-01

Spatial organization and noise play an important role in molecular systems biology. In recent years, a number of software packages have been developed for stochastic spatio-temporal simulation, ranging from detailed molecular-based approaches

Viscosity Solutions for a System of Integro-PDEs and Connections to Optimal Switching and Control of Jump-Diffusion Processes

International Nuclear Information System (INIS)

Biswas, Imran H.; Jakobsen, Espen R.; Karlsen, Kenneth H.

2010-01-01

We develop a viscosity solution theory for a system of nonlinear degenerate parabolic integro-partial differential equations (IPDEs) related to stochastic optimal switching and control problems or stochastic games. In the case of stochastic optimal switching and control, we prove via dynamic programming methods that the value function is a viscosity solution of the IPDEs. In our setting the value functions or the solutions of the IPDEs are not smooth, so classical verification theorems do not apply.

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

Effect of AlN layer on the bipolar resistive switching behavior in TiN thin film based ReRAM device for non-volatile memory application

Science.gov (United States)

Prakash, Ravi; Kaur, Davinder

2018-05-01

The effect of an additional AlN layer in the Cu/TiN/AlN/Pt stack configuration deposited using sputtering has been investigated. The Cu/TiN/AlN/Pt device shows a tristate resistive switching. Multilevel switching is facilitated by ionic and metallic filament formation, and the nature of the filaments formed is confirmed by performing a resistance vs. temperature measurement. Ohmic behaviour and trap controlled space charge limited current (SCLC) conduction mechanisms are confirmed as dominant conduction mechanism at low resistance state (LRS) and high resistance state (HRS). High resistance ratio (102) corresponding to HRS and LRS, good write/erase endurance (105) and non-volatile long retention (105s) are also observed. Higher thermal conductivity of the AlN layer is the main reasons for the enhancement of resistive switching performance in Cu/TiN/AlN/Pt cell. The above result suggests the feasibility of Cu/TiN/AlN/Pt devices for multilevel nonvolatile ReRAM application.

On the stochastic interaction of monochromatic Alfven waves with toroidally trapped particles

International Nuclear Information System (INIS)

Krlin, L.; Pavlo, P.; Tluchor, Z.; Gasek, Z.

1987-07-01

Monochromatic Alfven wave interaction with toroidaly trapped particles in the intrinsic stochasticity regime is discussed. Both the diffusion in velocities and in the radial position of bananas is studied. Using a suitable Hamiltonian formalism, the effect of wave parallel components E-tilde paral and B-tilde paral is investigated. The stochasticity threshold is estimated for plasma electrons and for thermonuclear alpha-particles (neglecting the effect of B-tilde paral ) by means of direct numerical integration of the corresponding canonical equations. Stochasticity causes transfer between trapped and untrapped regimes and the induced radial diffusion of bananas. The latter effect can considerably exceed neoclassical diffusion. The effect of B-tilde paral was only estimated analytically. It consisted in frequency modulation of the banana periodic motion coupled with a possible Mathieu instability. Nevertheless, for B-tilde paral corresponding to E-tilde paral , the effect seems to be weaker than the effect of E-tilde paral when the thermonuclear regime is considered. (author). 14 figs., 36 refs

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

Complexity, rate of energy exchanges and stochasticity

International Nuclear Information System (INIS)

Casartelli, M.; Sello, S.

1987-01-01

The complexity of trajectories in the phase of anharmonic crystal (mostly a Lennard-Jones chain) is analysed by the variance of microcanonical density and by new parameters P and chi defined, respectively, as the mean value of the time averages and the relative variance of the absolute exchange rate of energies among the normal modes. Evidence is given to the trapping action of residual invariant surfaces in low stochastic regime of motion. The parameter chi, moreover, proves efficient in exploring the border of stochasticity. A simple power law for P vs. the specific energy is obtained and proved to be independent of stochasticity and of the type of anharmonic potential

Deterministic and stochastic analysis of alternative climate targets under differentiated cooperation regimes

International Nuclear Information System (INIS)

Loulou, Richard; Labriet, Maryse; Kanudia, Amit

2009-01-01

This article analyzes the feasibility of attaining a variety of climate targets during the 21st century, under alternative cooperation regimes by groups of countries. Five climate targets of increasing severity are analyzed, following the EMF-22 experiment. Each target is attempted under two cooperation regimes, a First Best scenario where all countries fully cooperate from 2012 on, and a Second Best scenario where the World is partitioned into three groups, and each group of countries enters the cooperation at a different date, and implement emission abatement actions in a progressive manner, once in the coalition. The resulting ten combinations are simulated via the ETSAP-TIAM technology based, integrated assessment model. In addition to the 10 separate case analyses, the article proposes a probabilistic treatment of three targets under the First Best scenario, and shows that the three forcing targets may in fact be interpreted as a single target on global temperature change, while assuming that the climate sensitivity C s is uncertain. It is shown that such an interpretation is possible only if the probability distribution of C s is carefully chosen. The analysis of the results shows that the lowest forcing level is unattainable unless immediate coordinated action is undertaken by all countries, and even so only at a high global cost. The middle and the high forcing levels are feasible at affordable global costs, even under the Second Best scenario. Another original contribution of this article is to explain why certain combinations of technological choices are made by the model, and in particular why the climate target clearly supersedes the usually accepted objective of improving energy efficiency. The analysis shows that under some climate targets, it is not optimal to improve energy efficiency, but rather to take advantage of certain technologies that help to reach the climate objective, but that happen to be less energy efficient than even the technologies

Reversible switching of ultrastrong light-molecule coupling

DEFF Research Database (Denmark)

Schwartz, T; Hutchison, J A; Genet, C

2011-01-01

We demonstrate that photochromic molecules enable switching from the weak- to ultrastrong-coupling regime reversibly, by using all-optical control. This switch is achieved by photochemically inducing conformational changes in the molecule. Remarkably, a Rabi splitting of 700 meV is measured at room...

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.

Switching dynamics of TaOx-based threshold switching devices

Science.gov (United States)

Goodwill, Jonathan M.; Gala, Darshil K.; Bain, James A.; Skowronski, Marek

2018-03-01

Bi-stable volatile switching devices are being used as access devices in solid-state memory arrays and as the active part of compact oscillators. Such structures exhibit two stable states of resistance and switch between them at a critical value of voltage or current. A typical resistance transient under a constant amplitude voltage pulse starts with a slow decrease followed by a rapid drop and leveling off at a low steady state value. This behavior prompted the interpretation of initial delay and fast transition as due to two different processes. Here, we show that the entire transient including incubation time, transition time, and the final resistance values in TaOx-based switching can be explained by one process, namely, Joule heating with the rapid transition due to the thermal runaway. The time, which is required for the device in the conducting state to relax back to the stable high resistance one, is also consistent with the proposed mechanism.

Resistive switching in Pt/TiO{sub 2}/Pt

Energy Technology Data Exchange (ETDEWEB)

Jeong, Doo Seok

2008-08-15

Recently, the resistive switching behavior in TiO{sub 2} has drawn attention due to its application to resistive random access memory (RRAM) devices. TiO{sub 2} shows characteristic non-volatile resistive switching behavior, i.e. reversible switching between a high resistance state (HRS) and a low resistance state (LRS). Both unipolar resistive switching (URS) and bipolar resistive switching (BRS) are found to be observed in TiO{sub 2} depending on the compliance current for the electroforming. In this thesis the characteristic current-voltage (I-V) hysteresis in three different states of TiO{sub 2}, pristine, URS-activated, and BRS-activated states, was investigated and understood in terms of the migration of oxygen vacancies in TiO{sub 2}. The I-V hysteresis of pristine TiO{sub 2} was found to show volatile behavior. That is, the temporary variation of the resistance took place depending on the applied voltage. However, the I-V hysteresis of URS- and BRS-activated states showed non-volatile resistive switching behavior. Some evidences proving the evolution of oxygen gas during electroforming were obtained from time-of-flight secondary ion mass spectroscopy analysis and the variation of the morphology of switching cells induced by the electroforming. On the assumption that a large number of oxygen vacancies are introduced by the electroforming process, the I-V behavior in electroformed switching cells was simulated with varying the distribution of oxygen vacancies in electroformed TiO{sub x} (x

Optimal dividend distribution under Markov regime switching

NARCIS (Netherlands)

Jiang, Z.; Pistorius, M.

2012-01-01

We investigate the problem of optimal dividend distribution for a company in the presence of regime shifts. We consider a company whose cumulative net revenues evolve as a Brownian motion with positive drift that is modulated by a finite state Markov chain, and model the discount rate as a

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...

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....

Improving short-term forecasting during ramp events by means of Regime-Switching Artificial Neural Networks

Science.gov (United States)

Gallego, C.; Costa, A.; Cuerva, A.

2010-09-01

Since nowadays wind energy can't be neither scheduled nor large-scale storaged, wind power forecasting has been useful to minimize the impact of wind fluctuations. In particular, short-term forecasting (characterised by prediction horizons from minutes to a few days) is currently required by energy producers (in a daily electricity market context) and the TSO's (in order to keep the stability/balance of an electrical system). Within the short-term background, time-series based models (i.e., statistical models) have shown a better performance than NWP models for horizons up to few hours. These models try to learn and replicate the dynamic shown by the time series of a certain variable. When considering the power output of wind farms, ramp events are usually observed, being characterized by a large positive gradient in the time series (ramp-up) or negative (ramp-down) during relatively short time periods (few hours). Ramp events may be motivated by many different causes, involving generally several spatial scales, since the large scale (fronts, low pressure systems) up to the local scale (wind turbine shut-down due to high wind speed, yaw misalignment due to fast changes of wind direction). Hence, the output power may show unexpected dynamics during ramp events depending on the underlying processes; consequently, traditional statistical models considering only one dynamic for the hole power time series may be inappropriate. This work proposes a Regime Switching (RS) model based on Artificial Neural Nets (ANN). The RS-ANN model gathers as many ANN's as different dynamics considered (called regimes); a certain ANN is selected so as to predict the output power, depending on the current regime. The current regime is on-line updated based on a gradient criteria, regarding the past two values of the output power. 3 Regimes are established, concerning ramp events: ramp-up, ramp-down and no-ramp regime. In order to assess the skillness of the proposed RS-ANN model, a single

Inherently stochastic spiking neurons for probabilistic neural computation

KAUST Repository

Al-Shedivat, Maruan

2015-04-01

Neuromorphic engineering aims to design hardware that efficiently mimics neural circuitry and provides the means for emulating and studying neural systems. In this paper, we propose a new memristor-based neuron circuit that uniquely complements the scope of neuron implementations and follows the stochastic spike response model (SRM), which plays a cornerstone role in spike-based probabilistic algorithms. We demonstrate that the switching of the memristor is akin to the stochastic firing of the SRM. Our analysis and simulations show that the proposed neuron circuit satisfies a neural computability condition that enables probabilistic neural sampling and spike-based Bayesian learning and inference. Our findings constitute an important step towards memristive, scalable and efficient stochastic neuromorphic platforms. © 2015 IEEE.

Dynamic Effect of a Change in the Exchange Rate System: From a Fixed Regime to a Basket-Peg or a Floating Regime

OpenAIRE

Yoshino, Naoyuki; Kaji, Sahoko; Asonuma, Tamon

2015-01-01

This paper theoretically evaluates the dynamic effects of a shift in an exchange rate system from a fixed regime to a basket peg, or to a floating regime, and obtains transition paths for the shift based on a dynamic stochastic general equilibrium model of a small open economy. We apply quantitative analysis using data from the People's Republic of China and Thailand and find that a small open country would be better off shifting to a basket peg or to a floating regime than maintaining a doll...

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.

Dichotomous noise models of gene switches

Energy Technology Data Exchange (ETDEWEB)

Potoyan, Davit A., E-mail: potoyan@rice.edu; Wolynes, Peter G., E-mail: pwolynes@rice.edu [Department of Chemistry and Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005 (United States)

2015-11-21

Molecular noise in gene regulatory networks has two intrinsic components, one part being due to fluctuations caused by the birth and death of protein or mRNA molecules which are often present in small numbers and the other part arising from gene state switching, a single molecule event. Stochastic dynamics of gene regulatory circuits appears to be largely responsible for bifurcations into a set of multi-attractor states that encode different cell phenotypes. The interplay of dichotomous single molecule gene noise with the nonlinear architecture of genetic networks generates rich and complex phenomena. In this paper, we elaborate on an approximate framework that leads to simple hybrid multi-scale schemes well suited for the quantitative exploration of the steady state properties of large-scale cellular genetic circuits. Through a path sum based analysis of trajectory statistics, we elucidate the connection of these hybrid schemes to the underlying master equation and provide a rigorous justification for using dichotomous noise based models to study genetic networks. Numerical simulations of circuit models reveal that the contribution of the genetic noise of single molecule origin to the total noise is significant for a wide range of kinetic regimes.

Noise in Genetic Toggle Switch Models

Directory of Open Access Journals (Sweden)

Andrecut M.

2006-06-01

Full Text Available In this paper we study the intrinsic noise effect on the switching behavior of a simple genetic circuit corresponding to the genetic toggle switch model. The numerical results obtained from a noisy mean-field model are compared to those obtained from the stochastic Gillespie simulation of the corresponding system of chemical reactions. Our results show that by using a two step reaction approach for modeling the transcription and translation processes one can make the system to lock in one of the steady states for exponentially long times.

Thermal effects in magnetoelectric memories with stress-mediated switching

International Nuclear Information System (INIS)

Giordano, S; Dusch, Y; Tiercelin, N; Pernod, P; Preobrazhensky, V

2013-01-01

Heterostructures with magneto-electro-elastic coupling (e.g. multiferroics) are of paramount importance for developing new sensors, actuators and memories. With the progressive miniaturization of these systems it is necessary to take into account possible thermal effects, which may influence the normal operating regime. As a paradigmatic example we consider a recently introduced non-volatile memory element composed of a magnetostrictive nanoparticle embedded in a piezoelectric matrix. The distributions of the physical fields in this matrix/inclusion configuration are determined by means of the Eshelby theory, the magnetization dynamics is studied through the Landau–Lifshitz–Gilbert formalism, and the statistical mechanics is introduced with the Langevin and Fokker–Planck methodologies. As result of the combination of such techniques we determine the switching time between the states of the memory, the error probability and the energy dissipation of the writing process. They depend on the ratio k B T/v where T is the absolute temperature and v is the volume of the magnetoelastic particle. (paper)

Studies on Ytterbium-doped Fibre Laser Operating in Different Regimes

International Nuclear Information System (INIS)

Gan, Y; Xiang, W H; Zhang, G Z

2006-01-01

An ytterbium-doped fibre laser with a unidirectional ring cavity containing a polarizer placed between two in-line polarization controllers is presented. Depending on an equivalent saturable absorber, this laser operates in continuous, Q-switched mode-locked or CW mode-locked regimes. The passive method described here allowed us to choose the operating regime of the fibre laser by rotating the two polarization controllers and adjusting the pump power. Results of numerical simulations of pulse propagation in such a mode-locked fibre ring laser are presented, which reveals that the Q-switched mode-locked or CW modelocked regimes can be achieved by aligning the polarizer near the slow or the fast axes of the fibre

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.

Diffusion with intrinsic trapping in 2-d incompressible stochastic velocity fields

International Nuclear Information System (INIS)

Vlad, M.; Spineanu, F.; Misguich, J.H.; Vlad, M.; Spineanu, F.; Balescu, R.

1998-10-01

A new statistical approach that applies to the high Kubo number regimes for particle diffusion in stochastic velocity fields is presented. This 2-dimensional model describes the partial trapping of the particles in the stochastic field. the results are close to the numerical simulations and also to the estimations based on percolation theory. (authors)

The Forex Regime and EMU Expansion

NARCIS (Netherlands)

P.W. van Foreest; C.G. de Vries (Casper)

2002-01-01

textabstractThis paper provides empirical evidence that, irrespective of the foreign exchange rate regime, countries with high monetary volatility have lower relative output growth rates. It is argued that due to the forward looking nature of the foreign exchange market, exchange rate stability

Optimization of end-pumped, actively Q-switched quasi-III-level lasers.

Science.gov (United States)

Jabczynski, Jan K; Gorajek, Lukasz; Kwiatkowski, Jacek; Kaskow, Mateusz; Zendzian, Waldemar

2011-08-15

The new model of end-pumped quasi-III-level laser considering transient pumping processes, ground-state-depletion and up-conversion effects was developed. The model consists of two parts: pumping stage and Q-switched part, which can be separated in a case of active Q-switching regime. For pumping stage the semi-analytical model was developed, enabling the calculations for final occupation of upper laser level for given pump power and duration, spatial profile of pump beam, length and dopant level of gain medium. For quasi-stationary inversion, the optimization procedure of Q-switching regime based on Lagrange multiplier technique was developed. The new approach for optimization of CW regime of quasi-three-level lasers was developed to optimize the Q-switched lasers operating with high repetition rates. Both methods of optimizations enable calculation of optimal absorbance of gain medium and output losses for given pump rate. © 2011 Optical Society of America

Unstable volatility functions: the break preserving local linear estimator

DEFF Research Database (Denmark)

Casas, Isabel; Gijbels, Irene

The objective of this paper is to introduce the break preserving local linear (BPLL) estimator for the estimation of unstable volatility functions. Breaks in the structure of the conditional mean and/or the volatility functions are common in Finance. Markov switching models (Hamilton, 1989......) and threshold models (Lin and Terasvirta, 1994) are amongst the most popular models to describe the behaviour of data with structural breaks. The local linear (LL) estimator is not consistent at points where the volatility function has a break and it may even report negative values for finite samples...

The Nature of Power Spikes: a regime-switch approach

NARCIS (Netherlands)

C.M. de Jong (Cyriel)

2005-01-01

textabstractDue to its non-storable nature, electricity is a commodity with probably the most volatile spot prices, exemplified by occasional spikes. Appropriate pricing, portfolio, and risk management models have to incorporate these characteristics, and the spikes in particular. We investigate the

Piezoelectric control of magnetoelectric coupling driven non-volatile memory switching and self cooling effects in FE/FSMA multiferroic heterostructures

Science.gov (United States)

Singh, Kirandeep; Kaur, Davinder

2017-02-01

The manipulation of magnetic states and materials' spin degree-of-freedom via a control of an electric (E-) field has been recently pursued to develop magnetoelectric (ME) coupling-driven electronic data storage devices with high read/write endurance, fast dynamic response, and low energy dissipation. One major hurdle for this approach is to develop reliable materials which should be compatible with prevailing silicon (Si)-based complementary metal-oxide-semiconductor (CMOS) technology, simultaneously allowing small voltage for the tuning of magnetization switching. In this regard, multiferroic heterostructures where ferromagnetic (FM) and ferroelectric (FE) layers are alternatively grown on conventional Si substrates are promising as the piezoelectric control of magnetization switching is anticipated to be possible by an E-field. In this work, we study the ferromagnetic shape memory alloys based PbZr0.52Ti0.48O3/Ni50Mn35In15 (PZT/Ni-Mn-In) multiferroic heterostructures, and investigate their potential for CMOS compatible non-volatile magnetic data storage applications. We demonstrate the voltage-impulse controlled nonvolatile, reversible, and bistable magnetization switching at room temperature in Si-integrated PZT/Ni-Mn-In thin film multiferroic heterostructures. We also thoroughly unveil the various intriguing features in these materials, such as E-field tuned ME coupling and magnetocaloric effect, shape memory induced ferroelectric modulation, improved fatigue endurance as well as Refrigeration Capacity (RC). This comprehensive study suggests that these novel materials have a great potential for the development of unconventional nanoscale memory and refrigeration devices with self-cooling effect and enhanced refrigeration efficiency, thus providing a new venue for their applications.

Model reduction for slow–fast stochastic systems with metastable behaviour

International Nuclear Information System (INIS)

Bruna, Maria; Chapman, S. Jonathan; Smith, Matthew J.

2014-01-01

The quasi-steady-state approximation (or stochastic averaging principle) is a useful tool in the study of multiscale stochastic systems, giving a practical method by which to reduce the number of degrees of freedom in a model. The method is extended here to slow–fast systems in which the fast variables exhibit metastable behaviour. The key parameter that determines the form of the reduced model is the ratio of the timescale for the switching of the fast variables between metastable states to the timescale for the evolution of the slow variables. The method is illustrated with two examples: one from biochemistry (a fast-species-mediated chemical switch coupled to a slower varying species), and one from ecology (a predator–prey system). Numerical simulations of each model reduction are compared with those of the full system

Searching for an Appropriate Exchange Rate Regime

Directory of Open Access Journals (Sweden)

Yunjong Wang

2001-06-01

Full Text Available This paper attempts to survey current debates on the choice of exchange rate regime in emerging market economies. The issue of choosing an appropriate exchange rate regime is being actively discussed since the recent Asian crisis. As a lesson from the recent crises, one widely shared conclusion is that soft peg exchange rate regimes are extremely vulnerable in a world of volatile capital movements. Consequently, new orthodoxy based on the impossible trinity hypothesis favours two corner solutions ― greater flexibility or credible institutional assurance, like a currency board system or dollarization. Nevertheless, questions whether such corner solutions are adequate for developing countries are rising of late. "Fear of floating" is still conspicuous in many developing countries having adopted nominally a free-floating exchange rate regime. Developing countries are sensitive to exchange rate fluctuations because the cost of exchange rate volatility is greater than the benefit when compared to developed countries. Monitoring bands is a compromise solution, but it still needs further enhancement of estimation techniques for fundamental equilibrium exchange rates in order to make those estimation results more workable in practice. Other alternatives include the creation of soft peg of the G-3 currencies. Despite counterarguments, the stability of G-3 currencies could prove to be beneficial to emerging market economies.

Inverse Stochastic Resonance in Cerebellar Purkinje Cells.

Directory of Open Access Journals (Sweden)

Anatoly Buchin

2016-08-01

Full Text Available Purkinje neurons play an important role in cerebellar computation since their axons are the only projection from the cerebellar cortex to deeper cerebellar structures. They have complex internal dynamics, which allow them to fire spontaneously, display bistability, and also to be involved in network phenomena such as high frequency oscillations and travelling waves. Purkinje cells exhibit type II excitability, which can be revealed by a discontinuity in their f-I curves. We show that this excitability mechanism allows Purkinje cells to be efficiently inhibited by noise of a particular variance, a phenomenon known as inverse stochastic resonance (ISR. While ISR has been described in theoretical models of single neurons, here we provide the first experimental evidence for this effect. We find that an adaptive exponential integrate-and-fire model fitted to the basic Purkinje cell characteristics using a modified dynamic IV method displays ISR and bistability between the resting state and a repetitive activity limit cycle. ISR allows the Purkinje cell to operate in different functional regimes: the all-or-none toggle or the linear filter mode, depending on the variance of the synaptic input. We propose that synaptic noise allows Purkinje cells to quickly switch between these functional regimes. Using mutual information analysis, we demonstrate that ISR can lead to a locally optimal information transfer between the input and output spike train of the Purkinje cell. These results provide the first experimental evidence for ISR and suggest a functional role for ISR in cerebellar information processing.

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...

Photo-switch of pulsed Nd:YAG laser

International Nuclear Information System (INIS)

Ketta, W.W.J.

1989-01-01

In this work passive Q-switching and its effect on the output laser beam from a pulsed Nd:YAG laser was studied. This was achieved using the photochemically stable (BDNI) dye after dissolving it in dichloroethane. The absorption spectra of the dye solution and how suitable to use with Nd:YAG laser was also dealt with. Cooling unit for the laser system, a detector to detect the output pulse, and an electronic counter to measure the pulse duration were constructed. In the free-running regime, the divergence angle was measured. The form of the output, its energy, and how it is affected by the pumping energy were also studied. In the Q-switching regime, the relation between output and pumping energies was studied and compared to the same relation under the free-running regime. 5 tabs.; 33 figs.; 57 refs

High power semiconductor switching in the nanosecond regime

International Nuclear Information System (INIS)

Zucker, O.S.; Long, J.R.; Smith, V.L.; Page, D.J.; Roberts, J.S.

1975-12-01

Light activated multilayered silicon semiconductor devices have been used to switch at megawatt power levels with nanosecond turnon time. Current rate of rise of 700 kA/μs at 10 kA, with 1 kV across the load have been achieved. Recovery time of 1 millisec has been obtained. Applicability to fusion research needs is discussed

Stochastic mixed-mode oscillations in a three-species predator-prey model

Science.gov (United States)

Sadhu, Susmita; Kuehn, Christian

2018-03-01

The effect of demographic stochasticity, in the form of Gaussian white noise, in a predator-prey model with one fast and two slow variables is studied. We derive the stochastic differential equations (SDEs) from a discrete model. For suitable parameter values, the deterministic drift part of the model admits a folded node singularity and exhibits a singular Hopf bifurcation. We focus on the parameter regime near the Hopf bifurcation, where small amplitude oscillations exist as stable dynamics in the absence of noise. In this regime, the stochastic model admits noise-driven mixed-mode oscillations (MMOs), which capture the intermediate dynamics between two cycles of population outbreaks. We perform numerical simulations to calculate the distribution of the random number of small oscillations between successive spikes for varying noise intensities and distance to the Hopf bifurcation. We also study the effect of noise on a suitable Poincaré map. Finally, we prove that the stochastic model can be transformed into a normal form near the folded node, which can be linked to recent results on the interplay between deterministic and stochastic small amplitude oscillations. The normal form can also be used to study the parameter influence on the noise level near folded singularities.

Markov switching mean-variance frontier dynamics: theory and international evidence

OpenAIRE

M. Guidolin; F. Ria

2010-01-01

It is well-known that regime switching models are able to capture the presence of rich non-linear patterns in the joint distribution of asset returns. After reviewing key concepts and technical issues related to specifying, estimating, and using multivariate Markov switching models in financial applications, in this paper we map the presence of regimes in means, variances, and covariances of asset returns into explicit dynamics of the Markowitz mean-variance frontier. In particular, we show b...

Announced regime switch: optimal policy for transition period

Czech Academy of Sciences Publication Activity Database

Brázdik, František

-, č. 402 (2009), s. 1-49 ISSN 1211-3298 Institutional research plan: CEZ:MSM0021620846 Keywords : new Keynesian models * small open economy * monetary regime Subject RIV: AH - Economics http://www.cerge-ei.cz/pdf/wp/Wp402.pdf

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)

How input fluctuations reshape the dynamics of a biological switching system

Science.gov (United States)

Hu, Bo; Kessler, David A.; Rappel, Wouter-Jan; Levine, Herbert

2012-12-01

An important task in quantitative biology is to understand the role of stochasticity in biochemical regulation. Here, as an extension of our recent work [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.148101 107, 148101 (2011)], we study how input fluctuations affect the stochastic dynamics of a simple biological switch. In our model, the on transition rate of the switch is directly regulated by a noisy input signal, which is described as a non-negative mean-reverting diffusion process. This continuous process can be a good approximation of the discrete birth-death process and is much more analytically tractable. Within this setup, we apply the Feynman-Kac theorem to investigate the statistical features of the output switching dynamics. Consistent with our previous findings, the input noise is found to effectively suppress the input-dependent transitions. We show analytically that this effect becomes significant when the input signal fluctuates greatly in amplitude and reverts slowly to its mean.

Adaptive two-regime method: Application to front propagation

Energy Technology Data Exchange (ETDEWEB)

Robinson, Martin, E-mail: martin.robinson@maths.ox.ac.uk; Erban, Radek, E-mail: erban@maths.ox.ac.uk [Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG (United Kingdom); Flegg, Mark, E-mail: mark.flegg@monash.edu [School of Mathematical Sciences, Faculty of Science, Monash University Wellington Road, Clayton, Victoria 3800 (Australia)

2014-03-28

The Adaptive Two-Regime Method (ATRM) is developed for hybrid (multiscale) stochastic simulation of reaction-diffusion problems. It efficiently couples detailed Brownian dynamics simulations with coarser lattice-based models. The ATRM is a generalization of the previously developed Two-Regime Method [Flegg et al., J. R. Soc., Interface 9, 859 (2012)] to multiscale problems which require a dynamic selection of regions where detailed Brownian dynamics simulation is used. Typical applications include a front propagation or spatio-temporal oscillations. In this paper, the ATRM is used for an in-depth study of front propagation in a stochastic reaction-diffusion system which has its mean-field model given in terms of the Fisher equation [R. Fisher, Ann. Eugen. 7, 355 (1937)]. It exhibits a travelling reaction front which is sensitive to stochastic fluctuations at the leading edge of the wavefront. Previous studies into stochastic effects on the Fisher wave propagation speed have focused on lattice-based models, but there has been limited progress using off-lattice (Brownian dynamics) models, which suffer due to their high computational cost, particularly at the high molecular numbers that are necessary to approach the Fisher mean-field model. By modelling only the wavefront itself with the off-lattice model, it is shown that the ATRM leads to the same Fisher wave results as purely off-lattice models, but at a fraction of the computational cost. The error analysis of the ATRM is also presented for a morphogen gradient model.

Analysis of the Two-Regime Method on Square Meshes

KAUST Repository

Flegg, Mark B.

2014-01-01

The two-regime method (TRM) has been recently developed for optimizing stochastic reaction-diffusion simulations [M. Flegg, J. Chapman, and R. Erban, J. Roy. Soc. Interface, 9 (2012), pp. 859-868]. It is a multiscale (hybrid) algorithm which uses stochastic reaction-diffusion models with different levels of detail in different parts of the computational domain. The coupling condition on the interface between different modeling regimes of the TRM was previously derived for onedimensional models. In this paper, the TRM is generalized to higher dimensional reaction-diffusion systems. Coupling Brownian dynamics models with compartment-based models on regular (square) two-dimensional lattices is studied in detail. In this case, the interface between different modeling regimes contains either flat parts or right-angle corners. Both cases are studied in the paper. For flat interfaces, it is shown that the one-dimensional theory can be used along the line perpendicular to the TRM interface. In the direction tangential to the interface, two choices of the TRM parameters are presented. Their applicability depends on the compartment size and the time step used in the molecular-based regime. The two-dimensional generalization of the TRM is also discussed in the case of corners. © 2014 Society for Industrial and Applied Mathematics.

Atomic crystals resistive switching memory

International Nuclear Information System (INIS)

Liu Chunsen; Zhang David Wei; Zhou Peng

2017-01-01

Facing the growing data storage and computing demands, a high accessing speed memory with low power and non-volatile character is urgently needed. Resistive access random memory with 4F 2 cell size, switching in sub-nanosecond, cycling endurances of over 10 12 cycles, and information retention exceeding 10 years, is considered as promising next-generation non-volatile memory. However, the energy per bit is still too high to compete against static random access memory and dynamic random access memory. The sneak leakage path and metal film sheet resistance issues hinder the further scaling down. The variation of resistance between different devices and even various cycles in the same device, hold resistive access random memory back from commercialization. The emerging of atomic crystals, possessing fine interface without dangling bonds in low dimension, can provide atomic level solutions for the obsessional issues. Moreover, the unique properties of atomic crystals also enable new type resistive switching memories, which provide a brand-new direction for the resistive access random memory. (topical reviews)

Identification of fractional-order systems via a switching differential evolution subject to noise perturbations

Energy Technology Data Exchange (ETDEWEB)

Zhu, Wu, E-mail: dtzhuwu@gmail.com [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang, Jian-an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Tang, Yang, E-mail: yang.tang@pik-potsdam.de [Institute of Physics, Humboldt University, Berlin 12489 (Germany); Potsdam Institute for Climate Impact Research, Potsdam 14415 (Germany); Research Institute for Intelligent Control and System, Harbin Institute of Technology, Harbin 150006 (China); Zhang, Wenbing [Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hong Kong (China); Xu, Yulong [College of Information Science and Technology, Donghua University, Shanghai 201620 (China)

2012-10-01

In this Letter, a differential evolution variant, called switching DE (SDE), has been employed to estimate the orders and parameters in incommensurate fractional-order chaotic systems. The proposed algorithm includes a switching population utilization strategy, where the population size is adjusted dynamically based on the solution-searching status. Thus, this adaptive control method realizes the identification of fractional-order Lorenz, Lü and Chen systems in both deterministic and stochastic environments, respectively. Numerical simulations are provided, where comparisons are made with five other State-of-the-Art evolutionary algorithms (EAs) to verify the effectiveness of the proposed method. -- Highlights: ► Switching population utilization strategy is applied for differential evolution. ► The parameters are estimated in both deterministic and stochastic environments. ► Comparisons with five other EAs verify the effectiveness of the proposed method.

Identification of fractional-order systems via a switching differential evolution subject to noise perturbations

International Nuclear Information System (INIS)

Zhu, Wu; Fang, Jian-an; Tang, Yang; Zhang, Wenbing; Xu, Yulong

2012-01-01

In this Letter, a differential evolution variant, called switching DE (SDE), has been employed to estimate the orders and parameters in incommensurate fractional-order chaotic systems. The proposed algorithm includes a switching population utilization strategy, where the population size is adjusted dynamically based on the solution-searching status. Thus, this adaptive control method realizes the identification of fractional-order Lorenz, Lü and Chen systems in both deterministic and stochastic environments, respectively. Numerical simulations are provided, where comparisons are made with five other State-of-the-Art evolutionary algorithms (EAs) to verify the effectiveness of the proposed method. -- Highlights: ► Switching population utilization strategy is applied for differential evolution. ► The parameters are estimated in both deterministic and stochastic environments. ► Comparisons with five other EAs verify the effectiveness of the proposed method.

The memory of volatility

Directory of Open Access Journals (Sweden)

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.

Forecasting Tehran stock exchange volatility; Markov switching GARCH approach

Science.gov (United States)

Abounoori, Esmaiel; Elmi, Zahra (Mila); Nademi, Younes

2016-03-01

This paper evaluates several GARCH models regarding their ability to forecast volatility in Tehran Stock Exchange (TSE). These include GARCH models with both Gaussian and fat-tailed residual conditional distribution, concerning their ability to describe and forecast volatility from 1-day to 22-day horizon. Results indicate that AR(2)-MRSGARCH-GED model outperforms other models at one-day horizon. Also, the AR(2)-MRSGARCH-GED as well as AR(2)-MRSGARCH-t models outperform other models at 5-day horizon. In 10 day horizon, three models of AR(2)-MRSGARCH outperform other models. Concerning 22 day forecast horizon, results indicate no differences between MRSGARCH models with that of standard GARCH models. Regarding Risk management out-of-sample evaluation (95% VaR), a few models seem to provide reasonable and accurate VaR estimates at 1-day horizon, with a coverage rate close to the nominal level. According to the risk management loss functions, there is not a uniformly most accurate model.

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.

Intrinsic nanofilamentation in resistive switching

KAUST Repository

Wu, Xing

2013-03-15

Resistive switching materials are promising candidates for nonvolatile data storage and reconfiguration of electronic applications. Intensive studies have been carried out on sandwiched metal-insulator-metal structures to achieve high density on-chip circuitry and non-volatile memory storage. Here, we provide insight into the mechanisms that govern highly reproducible controlled resistive switching via a nanofilament by using an asymmetric metal-insulator-semiconductor structure. In-situ transmission electron microscopy is used to study in real-time the physical structure and analyze the chemical composition of the nanofilament dynamically during resistive switching. Electrical stressing using an external voltage was applied by a tungsten tip to the nanosized devices having hafnium oxide (HfO2) as the insulator layer. The formation and rupture of the nanofilaments result in up to three orders of magnitude change in the current flowing through the dielectric during the switching event. Oxygen vacancies and metal atoms from the anode constitute the chemistry of the nanofilament.

Characterizing multistationarity regimes in biochemical reaction networks.

Directory of Open Access Journals (Sweden)

Irene Otero-Muras

Full Text Available Switch like responses appear as common strategies in the regulation of cellular systems. Here we present a method to characterize bistable regimes in biochemical reaction networks that can be of use to both direct and reverse engineering of biological switches. In the design of a synthetic biological switch, it is important to study the capability for bistability of the underlying biochemical network structure. Chemical Reaction Network Theory (CRNT may help at this level to decide whether a given network has the capacity for multiple positive equilibria, based on their structural properties. However, in order to build a working switch, we also need to ensure that the bistability property is robust, by studying the conditions leading to the existence of two different steady states. In the reverse engineering of biological switches, knowledge collected about the bistable regimes of the underlying potential model structures can contribute at the model identification stage to a drastic reduction of the feasible region in the parameter space of search. In this work, we make use and extend previous results of the CRNT, aiming not only to discriminate whether a biochemical reaction network can exhibit multiple steady states, but also to determine the regions within the whole space of parameters capable of producing multistationarity. To that purpose we present and justify a condition on the parameters of biochemical networks for the appearance of multistationarity, and propose an efficient and reliable computational method to check its satisfaction through the parameter space.

Data retention in organic ferroelectric resistive switches

NARCIS (Netherlands)

Khikhlovskyi, V.; Breemen, A.J.J.M. van; Janssen, R.A.J.; Gelinck, G.H.; Kemerink, M.

2016-01-01

Solution-processed organic ferroelectric resistive switches could become the long-missing non-volatile memory elements in organic electronic devices. To this end, data retention in these devices should be characterized, understood and controlled. First, it is shown that the measurement protocol can

Analysis of the Two-Regime Method on Square Meshes

KAUST Repository

Flegg, Mark B.; Chapman, S. Jonathan; Zheng, Likun; Erban, Radek

2014-01-01

The two-regime method (TRM) has been recently developed for optimizing stochastic reaction-diffusion simulations [M. Flegg, J. Chapman, and R. Erban, J. Roy. Soc. Interface, 9 (2012), pp. 859-868]. It is a multiscale (hybrid) algorithm which uses

Predicting Equity Markets with Digital Online Media Sentiment: Evidence from Markov-switching Models

NARCIS (Netherlands)

Nooijen, S.J.; Broda, S.A.

2016-01-01

The authors examine the predictive capabilities of online investor sentiment for the returns and volatility of MSCI U.S. Equity Sector Indices by including exogenous variables in the mean and volatility specifications of a Markov-switching model. As predicted by the semistrong efficient market

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.

Two-dimensional photonic-crystal-based double switch-divider.

Science.gov (United States)

Dmitriev, Victor; Martins, Leno

2016-05-01

We propose and investigate a new multifunctional component, consisting of a T-junction of three waveguides in 2D photonic crystal with a square lattice. One waveguide is the input port, while the other two serve as output ports. This component can fulfil three functions: First, it can switch OFF the two output ports; second, our component can be used as a 3 dB divider of the input power; and third, it can switch ON any one of the two output ports. Changing the regime is achieved by a DC magnetic field that magnetizes a cylindrical ferrite resonator placed in the T-junction. We present an analysis of the scattering matrices of the component and calculated frequency characteristics in the low terahertz region. In the frequency band of about 1 GHz with a central frequency of f=98.46  GHz, the device has the following parameters: isolation of the output ports from the input port in the first regime is better than -30  dB, division of the input signal is about (-3.8±1.0)  dB in the second regime, and isolation in the regime switch ON, where any one of the two output ports is higher than -15  dB and the insertion loss is lower than -2.0  dB.

Stochastic simulation of enzyme-catalyzed reactions with disparate timescales.

Science.gov (United States)

Barik, Debashis; Paul, Mark R; Baumann, William T; Cao, Yang; Tyson, John J

2008-10-01

Many physiological characteristics of living cells are regulated by protein interaction networks. Because the total numbers of these protein species can be small, molecular noise can have significant effects on the dynamical properties of a regulatory network. Computing these stochastic effects is made difficult by the large timescale separations typical of protein interactions (e.g., complex formation may occur in fractions of a second, whereas catalytic conversions may take minutes). Exact stochastic simulation may be very inefficient under these circumstances, and methods for speeding up the simulation without sacrificing accuracy have been widely studied. We show that the "total quasi-steady-state approximation" for enzyme-catalyzed reactions provides a useful framework for efficient and accurate stochastic simulations. The method is applied to three examples: a simple enzyme-catalyzed reaction where enzyme and substrate have comparable abundances, a Goldbeter-Koshland switch, where a kinase and phosphatase regulate the phosphorylation state of a common substrate, and coupled Goldbeter-Koshland switches that exhibit bistability. Simulations based on the total quasi-steady-state approximation accurately capture the steady-state probability distributions of all components of these reaction networks. In many respects, the approximation also faithfully reproduces time-dependent aspects of the fluctuations. The method is accurate even under conditions of poor timescale separation.

Amplification of weak signals via the non-adiabatic regime of stochastic resonance in a bistable dynamical system with time delay

International Nuclear Information System (INIS)

Du Luchun; Mei Dongcheng

2011-01-01

The non-adiabatic regime of stochastic resonance (SR) in a bistable system with time delay, an additive white noise and a periodic signal was investigated. The signal power amplification η was employed to characterize the SR of the system. The simulation results indicate that (i) in the case of intermediate frequency Ω of the periodic signal, the typical behavior of SR is lowered monotonically by increasing the delay time τ; in the case of large Ω, τ weakens the SR behavior and then enhances it, with a non-monotonic behavior as a function of time delay; (ii) time delay induces SR when A is above the threshold, whereas no such resonance exists in the absence of time delay; (iii) time delay induces a transition from bimodal to unimodal configuration of η; (iv) varying the particular form of time delay results in different phenomena.

EDITORIAL: Non-volatile memory based on nanostructures Non-volatile memory based on nanostructures

Science.gov (United States)

Kalinin, Sergei; Yang, J. Joshua; Demming, Anna

2011-06-01

Non-volatile memory refers to the crucial ability of computers to store information once the power source has been removed. Traditionally this has been achieved through flash, magnetic computer storage and optical discs, and in the case of very early computers paper tape and punched cards. While computers have advanced considerably from paper and punched card memory devices, there are still limits to current non-volatile memory devices that restrict them to use as secondary storage from which data must be loaded and carefully saved when power is shut off. Denser, faster, low-energy non-volatile memory is highly desired and nanostructures are the critical enabler. This special issue on non-volatile memory based on nanostructures describes some of the new physics and technology that may revolutionise future computers. Phase change random access memory, which exploits the reversible phase change between crystalline and amorphous states, also holds potential for future memory devices. The chalcogenide Ge2Sb2Te5 (GST) is a promising material in this field because it combines a high activation energy for crystallization and a relatively low crystallization temperature, as well as a low melting temperature and low conductivity, which accommodates localized heating. Doping is often used to lower the current required to activate the phase change or 'reset' GST but this often aggravates other problems. Now researchers in Korea report in-depth studies of SiO2-doped GST and identify ways of optimising the material's properties for phase-change random access memory [1]. Resistance switching is an area that has attracted a particularly high level of interest for non-volatile memory technology, and a great deal of research has focused on the potential of TiO2 as a model system in this respect. Researchers at HP labs in the US have made notable progress in this field, and among the work reported in this special issue they describe means to control the switch resistance and show

A termination criterion for parameter estimation in stochastic models in systems biology.

Science.gov (United States)

Zimmer, Christoph; Sahle, Sven

2015-11-01

Parameter estimation procedures are a central aspect of modeling approaches in systems biology. They are often computationally expensive, especially when the models take stochasticity into account. Typically parameter estimation involves the iterative optimization of an objective function that describes how well the model fits some measured data with a certain set of parameter values. In order to limit the computational expenses it is therefore important to apply an adequate stopping criterion for the optimization process, so that the optimization continues at least until a reasonable fit is obtained, but not much longer. In the case of stochastic modeling, at least some parameter estimation schemes involve an objective function that is itself a random variable. This means that plain convergence tests are not a priori suitable as stopping criteria. This article suggests a termination criterion suited to optimization problems in parameter estimation arising from stochastic models in systems biology. The termination criterion is developed for optimization algorithms that involve populations of parameter sets, such as particle swarm or evolutionary algorithms. It is based on comparing the variance of the objective function over the whole population of parameter sets with the variance of repeated evaluations of the objective function at the best parameter set. The performance is demonstrated for several different algorithms. To test the termination criterion we choose polynomial test functions as well as systems biology models such as an Immigration-Death model and a bistable genetic toggle switch. The genetic toggle switch is an especially challenging test case as it shows a stochastic switching between two steady states which is qualitatively different from the model behavior in a deterministic model. Copyright © 2015. Published by Elsevier Ireland Ltd.

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.

Synchronization of stochastic delayed neural networks with markovian switching and its application.

Science.gov (United States)

Tang, Yang; Fang, Jian-An; Miao, Qing-Ying

2009-02-01

In this paper, the problem of adaptive synchronization for a class of stochastic neural networks (SNNs) which involve both mixed delays and Markovian jumping parameters is investigated. The mixed delays comprise the time-varying delays and distributed delays, both of which are mode-dependent. The stochastic perturbations are described in terms of Browian motion. By the adaptive feedback technique, several sufficient criteria have been proposed to ensure the synchronization of SNNs in mean square. Moreover, the proposed adaptive feedback scheme is applied to the secure communication. Finally, the corresponding simulation results are given to demonstrate the usefulness of the main results obtained.

An Element of Determinism in a Stochastic Flagellar Motor Switch.

Science.gov (United States)

Xie, Li; Altindal, Tuba; Wu, Xiao-Lun

2015-01-01

Marine bacterium Vibrio alginolyticus uses a single polar flagellum to navigate in an aqueous environment. Similar to Escherichia coli cells, the polar flagellar motor has two states; when the motor is counter-clockwise, the cell swims forward and when the motor is clockwise, the cell swims backward. V. alginolyticus also incorporates a direction randomization step at the start of the forward swimming interval by flicking its flagellum. To gain an understanding on how the polar flagellar motor switch is regulated, distributions of the forward Δf and backward Δb intervals are investigated herein. We found that the steady-state probability density functions, P(Δf) and P(Δb), of freely swimming bacteria are strongly peaked at a finite time, suggesting that the motor switch is not Poissonian. The short-time inhibition is sufficiently strong and long lasting, i.e., several hundred milliseconds for both intervals, which is readily observed and characterized. Treating motor reversal dynamics as a first-passage problem, which results from conformation fluctuations of the motor switch, we calculated P(Δf) and P(Δb) and found good agreement with the measurements.

Fast stochastic simulation of biochemical reaction systems by alternative formulations of the chemical Langevin equation

KAUST Repository

Mélykúti, Bence

2010-01-01

The Chemical Langevin Equation (CLE), which is a stochastic differential equation driven by a multidimensional Wiener process, acts as a bridge between the discrete stochastic simulation algorithm and the deterministic reaction rate equation when simulating (bio)chemical kinetics. The CLE model is valid in the regime where molecular populations are abundant enough to assume their concentrations change continuously, but stochastic fluctuations still play a major role. The contribution of this work is that we observe and explore that the CLE is not a single equation, but a parametric family of equations, all of which give the same finite-dimensional distribution of the variables. On the theoretical side, we prove that as many Wiener processes are sufficient to formulate the CLE as there are independent variables in the equation, which is just the rank of the stoichiometric matrix. On the practical side, we show that in the case where there are m1 pairs of reversible reactions and m2 irreversible reactions there is another, simple formulation of the CLE with only m1 + m2 Wiener processes, whereas the standard approach uses 2 m1 + m2. We demonstrate that there are considerable computational savings when using this latter formulation. Such transformations of the CLE do not cause a loss of accuracy and are therefore distinct from model reduction techniques. We illustrate our findings by considering alternative formulations of the CLE for a human ether a-go-go related gene ion channel model and the Goldbeter-Koshland switch. © 2010 American Institute of Physics.

Computing with volatile memristors: an application of non-pinched hysteresis

Science.gov (United States)

Pershin, Y. V.; Shevchenko, S. N.

2017-02-01

The possibility of in-memory computing with volatile memristive devices, namely, memristors requiring a power source to sustain their memory, is demonstrated theoretically. We have adopted a hysteretic graphene-based field emission structure as a prototype of a volatile memristor, which is characterized by a non-pinched hysteresis loop. A memristive model of the structure is developed and used to simulate a polymorphic circuit implementing stateful logic gates, such as the material implication. Specific regions of parameter space realizing useful logic functions are identified. Our results are applicable to other realizations of volatile memory devices, such as certain NEMS switches.

WKB theory of large deviations in stochastic populations

Science.gov (United States)

Assaf, Michael; Meerson, Baruch

2017-06-01

Stochasticity can play an important role in the dynamics of biologically relevant populations. These span a broad range of scales: from intra-cellular populations of molecules to population of cells and then to groups of plants, animals and people. Large deviations in stochastic population dynamics—such as those determining population extinction, fixation or switching between different states—are presently in a focus of attention of statistical physicists. We review recent progress in applying different variants of dissipative WKB approximation (after Wentzel, Kramers and Brillouin) to this class of problems. The WKB approximation allows one to evaluate the mean time and/or probability of population extinction, fixation and switches resulting from either intrinsic (demographic) noise, or a combination of the demographic noise and environmental variations, deterministic or random. We mostly cover well-mixed populations, single and multiple, but also briefly consider populations on heterogeneous networks and spatial populations. The spatial setting also allows one to study large fluctuations of the speed of biological invasions. Finally, we briefly discuss possible directions of future work.

WKB theory of large deviations in stochastic populations

International Nuclear Information System (INIS)

Assaf, Michael; Meerson, Baruch

2017-01-01

Stochasticity can play an important role in the dynamics of biologically relevant populations. These span a broad range of scales: from intra-cellular populations of molecules to population of cells and then to groups of plants, animals and people. Large deviations in stochastic population dynamics—such as those determining population extinction, fixation or switching between different states—are presently in a focus of attention of statistical physicists. We review recent progress in applying different variants of dissipative WKB approximation (after Wentzel, Kramers and Brillouin) to this class of problems. The WKB approximation allows one to evaluate the mean time and/or probability of population extinction, fixation and switches resulting from either intrinsic (demographic) noise, or a combination of the demographic noise and environmental variations, deterministic or random. We mostly cover well-mixed populations, single and multiple, but also briefly consider populations on heterogeneous networks and spatial populations. The spatial setting also allows one to study large fluctuations of the speed of biological invasions. Finally, we briefly discuss possible directions of future work. (topical review)

Multivariate moment closure techniques for stochastic kinetic models

International Nuclear Information System (INIS)

Lakatos, Eszter; Ale, Angelique; Kirk, Paul D. W.; Stumpf, Michael P. H.

2015-01-01

Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporally evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs

Multivariate moment closure techniques for stochastic kinetic models

Energy Technology Data Exchange (ETDEWEB)

Lakatos, Eszter, E-mail: e.lakatos13@imperial.ac.uk; Ale, Angelique; Kirk, Paul D. W.; Stumpf, Michael P. H., E-mail: m.stumpf@imperial.ac.uk [Department of Life Sciences, Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London SW7 2AZ (United Kingdom)

2015-09-07

Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporally evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs.

The asymmetric reactions of mean and volatility of stock returns to domestic and international information based on a four-regime double-threshold GARCH model

Science.gov (United States)

Chen, Cathy W. S.; Yang, Ming Jing; Gerlach, Richard; Jim Lo, H.

2006-07-01

In this paper, we investigate the asymmetric reactions of mean and volatility of stock returns in five major markets to their own local news and the US information via linear and nonlinear models. We introduce a four-regime Double-Threshold GARCH (DTGARCH) model, which allows asymmetry in both the conditional mean and variance equations simultaneously by employing two threshold variables, to analyze the stock markets’ reactions to different types of information (good/bad news) generated from the domestic markets and the US stock market. By applying the four-regime DTGARCH model, this study finds that the interaction between the information of domestic and US stock markets leads to the asymmetric reactions of stock returns and their variability. In addition, this research also finds that the positive autocorrelation reported in the previous studies of financial markets may in fact be mis-specified, and actually due to the local market's positive response to the US stock market.

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

Repetitive plasma opening switch for powerful high-voltage pulse generators

International Nuclear Information System (INIS)

Dolgachev, G.I.; Zakatov, L.P.; Nitishinskii, M.S.; Ushakov, A.G.

1998-01-01

Results are presented of experimental studies of plasma opening switches that serve to sharpen the pulses of inductive microsecond high-voltage pulse generators. It is demonstrated that repetitive plasma opening switches can be used to create super-powerful generators operating in a quasi-continuous regime. An erosion switching mechanism and the problem of magnetic insulation in repetitive switches are considered. Achieving super-high peak power in plasma switches makes it possible to develop new types of high-power generators of electron beams and X radiation. Possible implementations and the efficiency of these generators are discussed

Atomic switch networks as complex adaptive systems

Science.gov (United States)

Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

2018-03-01

Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.

Exchange rate regimes and macroeconomic instabilities in Sub-Saharan Africa

Directory of Open Access Journals (Sweden)

Yaya Camara Seydou

2015-01-01

Full Text Available This article addresses macroeconomic instabilities according to exchange rate regimes in Sub-Saharan Africa (SSA. Based on International Monetary Fund's exchange rate regimes de facto classification, the global sample, SSA, is first divided into two subsamples, which are countries within CFA franc zone (ZCFA and those outside CFA franc zone (HZCFA, and then into four categories, which are the Western Economic and Monetary Union (WAEMU, the Central African Economic and Monetary Community, the countries CFA franc zone with fix exchange rate regimes(HZCFA-FIX, and the countries outside CFA franc zone with flexible exchange rate regimes(HZCFA-FLEX. By applying advanced statistical and econometric methods upon internal and external macroeconomic equilibrium conditions, we show that the inflation, the GDP (or the output and the real exchange rate (RER are very volatile in SSA. However, we found out that they are more volatile in the group HZCFA comparatively to the group ZCFA. We also found out that they are higher in the group HZCFA-FIX than the group HZCFA-FLEX. Moreover, we found out that a high instability of the inflation is combined with those of the output and the RER.

Resistive Switching Characteristics in Electrochemically Synthesized ZnO Films

Directory of Open Access Journals (Sweden)

Shuhan Jing

2015-04-01

Full Text Available The semiconductor industry has long been seeking a new kind of non-volatile memory technology with high-density, high-speed, and low-power consumption. This study demonstrated the electrochemical synthesis of ZnO films without adding any soft or hard templates. The effect of deposition temperatures on crystal structure, surface morphology and resistive switching characteristics were investigated. Our findings reveal that the crystallinity, surface morphology and resistive switching characteristics of ZnO thin films can be well tuned by controlling deposition temperature. A conducting filament based model is proposed to explain the switching mechanism in ZnO thin films.

Dual-functional Memory and Threshold Resistive Switching Based on the Push-Pull Mechanism of Oxygen Ions

KAUST Repository

Huang, Yi-Jen; Chao, Shih-Chun; Lien, Der-Hsien; Wen, Cheng-Yen; He, Jr-Hau; Lee, Si-Chen

2016-01-01

The combination of nonvolatile memory switching and volatile threshold switching functions of transition metal oxides in crossbar memory arrays is of great potential for replacing charge-based flash memory in very-large-scale integration. Here, we

Regime-Based Versus Static Asset Allocation: Letting the Data Speak

DEFF Research Database (Denmark)

Nystrup, Peter; Hansen, Bo William; Madsen, Henrik

2015-01-01

Regime shifts present a big challenge to traditional strategic asset allocation. This article investigates whether regimebased asset allocation can effectively respond to changes in financial regimes at the portfolio level, in an effort to provide better long-term results than more static...... approaches can offer. The authors center their regime-based approach around a regime-switching model with time-varying parameters that can match financial markets’ tendency to change behavior abruptly and the fact that the new behavior often persists for several periods after a change. In an asset universe...

Solving stochastic inflation for arbitrary potentials

International Nuclear Information System (INIS)

Martin, Jerome; Musso, Marcello

2006-01-01

A perturbative method for solving the Langevin equation of inflationary cosmology in the presence of backreaction is presented. In the Gaussian approximation, the method permits an explicit calculation of the probability distribution of the inflaton field for an arbitrary potential, with or without the volume effects taken into account. The perturbative method is then applied to various concrete models, namely, large field, small field, hybrid, and running mass inflation. New results on the stochastic behavior of the inflaton field in those models are obtained. In particular, it is confirmed that the stochastic effects can be important in new inflation while it is demonstrated they are negligible in (vacuum dominated) hybrid inflation. The case of stochastic running mass inflation is discussed in some details and it is argued that quantum effects blur the distinction between the four classical versions of this model. It is also shown that the self-reproducing regime is likely to be important in this case

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.

Nonlinear signaling on biological networks: The role of stochasticity and spectral clustering

Science.gov (United States)

Hernandez-Hernandez, Gonzalo; Myers, Jesse; Alvarez-Lacalle, Enrique; Shiferaw, Yohannes

2017-03-01

Signal transduction within biological cells is governed by networks of interacting proteins. Communication between these proteins is mediated by signaling molecules which bind to receptors and induce stochastic transitions between different conformational states. Signaling is typically a cooperative process which requires the occurrence of multiple binding events so that reaction rates have a nonlinear dependence on the amount of signaling molecule. It is this nonlinearity that endows biological signaling networks with robust switchlike properties which are critical to their biological function. In this study we investigate how the properties of these signaling systems depend on the network architecture. Our main result is that these nonlinear networks exhibit bistability where the network activity can switch between states that correspond to a low and high activity level. We show that this bistable regime emerges at a critical coupling strength that is determined by the spectral structure of the network. In particular, the set of nodes that correspond to large components of the leading eigenvector of the adjacency matrix determines the onset of bistability. Above this transition the eigenvectors of the adjacency matrix determine a hierarchy of clusters, defined by its spectral properties, which are activated sequentially with increasing network activity. We argue further that the onset of bistability occurs either continuously or discontinuously depending upon whether the leading eigenvector is localized or delocalized. Finally, we show that at low network coupling stochastic transitions to the active branch are also driven by the set of nodes that contribute more strongly to the leading eigenvector. However, at high coupling, transitions are insensitive to network structure since the network can be activated by stochastic transitions of a few nodes. Thus this work identifies important features of biological signaling networks that may underlie their biological

Stochastic Turing Patterns: Analysis of Compartment-Based Approaches

KAUST Repository

Cao, Yang; Erban, Radek

2014-01-01

© 2014, Society for Mathematical Biology. Turing patterns can be observed in reaction-diffusion systems where chemical species have different diffusion constants. In recent years, several studies investigated the effects of noise on Turing patterns and showed that the parameter regimes, for which stochastic Turing patterns are observed, can be larger than the parameter regimes predicted by deterministic models, which are written in terms of partial differential equations (PDEs) for species concentrations. A common stochastic reaction-diffusion approach is written in terms of compartment-based (lattice-based) models, where the domain of interest is divided into artificial compartments and the number of molecules in each compartment is simulated. In this paper, the dependence of stochastic Turing patterns on the compartment size is investigated. It has previously been shown (for relatively simpler systems) that a modeler should not choose compartment sizes which are too small or too large, and that the optimal compartment size depends on the diffusion constant. Taking these results into account, we propose and study a compartment-based model of Turing patterns where each chemical species is described using a different set of compartments. It is shown that the parameter regions where spatial patterns form are different from the regions obtained by classical deterministic PDE-based models, but they are also different from the results obtained for the stochastic reaction-diffusion models which use a single set of compartments for all chemical species. In particular, it is argued that some previously reported results on the effect of noise on Turing patterns in biological systems need to be reinterpreted.

Stochastic Turing Patterns: Analysis of Compartment-Based Approaches

KAUST Repository

Cao, Yang

2014-11-25

© 2014, Society for Mathematical Biology. Turing patterns can be observed in reaction-diffusion systems where chemical species have different diffusion constants. In recent years, several studies investigated the effects of noise on Turing patterns and showed that the parameter regimes, for which stochastic Turing patterns are observed, can be larger than the parameter regimes predicted by deterministic models, which are written in terms of partial differential equations (PDEs) for species concentrations. A common stochastic reaction-diffusion approach is written in terms of compartment-based (lattice-based) models, where the domain of interest is divided into artificial compartments and the number of molecules in each compartment is simulated. In this paper, the dependence of stochastic Turing patterns on the compartment size is investigated. It has previously been shown (for relatively simpler systems) that a modeler should not choose compartment sizes which are too small or too large, and that the optimal compartment size depends on the diffusion constant. Taking these results into account, we propose and study a compartment-based model of Turing patterns where each chemical species is described using a different set of compartments. It is shown that the parameter regions where spatial patterns form are different from the regions obtained by classical deterministic PDE-based models, but they are also different from the results obtained for the stochastic reaction-diffusion models which use a single set of compartments for all chemical species. In particular, it is argued that some previously reported results on the effect of noise on Turing patterns in biological systems need to be reinterpreted.

Robust incentives and the design of a climate change governance regime

International Nuclear Information System (INIS)

Nemet, Gregory F.

2010-01-01

In building a governance regime to address climate change, should we prioritize the development of global institutions or national ones? This paper focuses on two neglected characteristics to inform the governance problem: the incentives for investment in low-carbon energy technology and the influence of historical policy volatility. Examining a case study of an important low-carbon energy technology, wind power, this study finds: (1) policy volatility has been substantial, (2) policy changes were uncorrelated across jurisdictions, suggesting that (3) investors could have substantially reduced their exposure to the risk of policy volatility by operating globally. While it also has downsides, a poorly coordinated international policy regime has the advantage of reducing the risk associated with a global policy failure. Beyond this case study, the importance of this positive effect depends on: the probability of policy failures in each country, the correlations among them, and the probability of a global policy failure. (author)

Dynamic two state stochastic models for ecological regime shifts

DEFF Research Database (Denmark)

Møller, Jan Kloppenborg; Carstensen, Niels Jacob; Madsen, Henrik

2009-01-01

of the model illustrates that hysteresis effect and regime shifts can be obtained for a limited range of parameter values only. The effect of multiplicative noise components entering at different levels of the model is presented and discussed. Including noise leads to very different results on the stability...

Hybrid colored noise process with space-dependent switching rates

Science.gov (United States)

Bressloff, Paul C.; Lawley, Sean D.

2017-07-01

A fundamental issue in the theory of continuous stochastic process is the interpretation of multiplicative white noise, which is often referred to as the Itô-Stratonovich dilemma. From a physical perspective, this reflects the need to introduce additional constraints in order to specify the nature of the noise, whereas from a mathematical perspective it reflects an ambiguity in the formulation of stochastic differential equations (SDEs). Recently, we have identified a mechanism for obtaining an Itô SDE based on a form of temporal disorder. Motivated by switching processes in molecular biology, we considered a Brownian particle that randomly switches between two distinct conformational states with different diffusivities. In each state, the particle undergoes normal diffusion (additive noise) so there is no ambiguity in the interpretation of the noise. However, if the switching rates depend on position, then in the fast switching limit one obtains Brownian motion with a space-dependent diffusivity of the Itô form. In this paper, we extend our theory to include colored additive noise. We show that the nature of the effective multiplicative noise process obtained by taking both the white-noise limit (κ →0 ) and fast switching limit (ɛ →0 ) depends on the order the two limits are taken. If the white-noise limit is taken first, then we obtain Itô, and if the fast switching limit is taken first, then we obtain Stratonovich. Moreover, the form of the effective diffusion coefficient differs in the two cases. The latter result holds even in the case of space-independent transition rates, where one obtains additive noise processes with different diffusion coefficients. Finally, we show that yet another form of multiplicative noise is obtained in the simultaneous limit ɛ ,κ →0 with ɛ /κ2 fixed.

International portfolio flows and exchange rate volatility for emerging markets

OpenAIRE

Caporale, Guglielmo Maria; Ali, Faek Menla; Spagnolo, Fabio; Spagnolo, Nicola

2015-01-01

This paper investigates the effects of equity and bond portfolio inflows on exchange rate volatility, using monthly bilateral data for the US vis-a-vis eight Asian developing and emerging countries (India, Indonesia, South Korea, Pakistan, Hong Kong, Thailand, the Philippines, and Taiwan) over the period 1993:01-2012:11, and estimating a time-varying transition probability Markov-switching model. We find that net equity (bond) inflows drive the exchange rate to a high (low) volatility state. ...

Stochastic E2F activation and reconciliation of phenomenological cell-cycle models.

Science.gov (United States)

Lee, Tae J; Yao, Guang; Bennett, Dorothy C; Nevins, Joseph R; You, Lingchong

2010-09-21

The transition of the mammalian cell from quiescence to proliferation is a highly variable process. Over the last four decades, two lines of apparently contradictory, phenomenological models have been proposed to account for such temporal variability. These include various forms of the transition probability (TP) model and the growth control (GC) model, which lack mechanistic details. The GC model was further proposed as an alternative explanation for the concept of the restriction point, which we recently demonstrated as being controlled by a bistable Rb-E2F switch. Here, through a combination of modeling and experiments, we show that these different lines of models in essence reflect different aspects of stochastic dynamics in cell cycle entry. In particular, we show that the variable activation of E2F can be described by stochastic activation of the bistable Rb-E2F switch, which in turn may account for the temporal variability in cell cycle entry. Moreover, we show that temporal dynamics of E2F activation can be recast into the frameworks of both the TP model and the GC model via parameter mapping. This mapping suggests that the two lines of phenomenological models can be reconciled through the stochastic dynamics of the Rb-E2F switch. It also suggests a potential utility of the TP or GC models in defining concise, quantitative phenotypes of cell physiology. This may have implications in classifying cell types or states.

Gold price effect on stock market: A Markov switching vector error correction approach

Science.gov (United States)

Wai, Phoong Seuk; Ismail, Mohd Tahir; Kun, Sek Siok

2014-06-01

Gold is a popular precious metal where the demand is driven not only for practical use but also as a popular investments commodity. While stock market represents a country growth, thus gold price effect on stock market behavior as interest in the study. Markov Switching Vector Error Correction Models are applied to analysis the relationship between gold price and stock market changes since real financial data always exhibit regime switching, jumps or missing data through time. Besides, there are numerous specifications of Markov Switching Vector Error Correction Models and this paper will compare the intercept adjusted Markov Switching Vector Error Correction Model and intercept adjusted heteroskedasticity Markov Switching Vector Error Correction Model to determine the best model representation in capturing the transition of the time series. Results have shown that gold price has a positive relationship with Malaysia, Thailand and Indonesia stock market and a two regime intercept adjusted heteroskedasticity Markov Switching Vector Error Correction Model is able to provide the more significance and reliable result compare to intercept adjusted Markov Switching Vector Error Correction Models.

Convergence of the Stochastic Six-Vertex Model to the ASEP

Energy Technology Data Exchange (ETDEWEB)

Aggarwal, Amol, E-mail: amolaggarwal@g.harvard.edu [Harvard University Cambridge (United States)

2017-06-15

In this note we establish the convergence of the stochastic six-vertex model to the one-dimensional asymmetric simple exclusion process, under a certain limit regime recently predicted by Borodin-Corwin-Gorin. This convergence holds for arbitrary initial data.

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

Stochastic ice stream dynamics.

Science.gov (United States)

Mantelli, Elisa; Bertagni, Matteo Bernard; Ridolfi, Luca

2016-08-09

Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution.

Low-power non-volatile spintronic memory: STT-RAM and beyond

International Nuclear Information System (INIS)

Wang, K L; Alzate, J G; Khalili Amiri, P

2013-01-01

The quest for novel low-dissipation devices is one of the most critical for the future of semiconductor technology and nano-systems. The development of a low-power, universal memory will enable a new paradigm of non-volatile computation. Here we consider STT-RAM as one of the emerging candidates for low-power non-volatile memory. We show different configurations for STT memory and demonstrate strategies to optimize key performance parameters such as switching current and energy. The energy and scaling limits of STT-RAM are discussed, leading us to argue that alternative writing mechanisms may be required to achieve ultralow power dissipation, a necessary condition for direct integration with CMOS at the gate level for non-volatile logic purposes. As an example, we discuss the use of the giant spin Hall effect as a possible alternative to induce magnetization reversal in magnetic tunnel junctions using pure spin currents. Further, we concentrate on magnetoelectric effects, where electric fields are used instead of spin-polarized currents to manipulate the nanomagnets, as another candidate solution to address the challenges of energy efficiency and density. The possibility of an electric-field-controlled magnetoelectric RAM as a promising candidate for ultralow-power non-volatile memory is discussed in the light of experimental data demonstrating voltage-induced switching of the magnetization and reorientation of the magnetic easy axis by electric fields in nanomagnets. (paper)

Mudanças de Regime no Câmbio Brasileiro

OpenAIRE

Carlos Hamilton V. Araújo; Getúlio B. da Silveira Filho

2002-01-01

In this paper the eight variants of the Brazilian exchange rate are analyzed. After putting the evolution of this indicator into historical context, univariate analysis of the level and the volatility of the series is implemented. In this task, the research especially emphasizes the effects of the outliers, as well as on the eventual changes in the regime - in the level and/or in the volatility - likely associated with the outliers observed from January 1969 to September 2001. Moreover, some ...

Orientation of KRb molecules in a switched electrostatic field

International Nuclear Information System (INIS)

Huang Yun-Xia; Xu Shu-Wu; Yang Xiao-Hua

2013-01-01

We theoretically investigate the orientation of the cold KRb molecules induced in a switched electrostatic field by numerically solving the full time-dependent Schrödinger equation. The results show that the periodic field-free molecular orientation can be realized for the KRb molecules by rapidly switching off the electrostatic field. Meanwhile, by varying the switching times of the electrostatic field, the adiabatic and nonadiabatic interactions of the molecules with the applied field can be realized. Moreover, the influences of the electrostatic field strength and the rotational temperature to the degree of the molecular orientation are studied. The investigations show that increasing the electrostatic field will increase the degree of the molecular orientation, both in the constant-field regime and in the field-free regime, while the increasing of the rotational temperature of the cold molecules will greatly decrease the degree of the molecular orientation. (atomic and molecular physics)

Resistance switching in silver - manganite contacts

International Nuclear Information System (INIS)

Gomez-Marlasca, F; Levy, P

2009-01-01

We investigate the electric pulse induced resistance switching in a transition metal oxide-metal contact at room temperature - a non volatile, reversible and multilevel memory device. Using a simple multiterminal configuration, we find that the complementary effect -in which the contact resistance of each pulsed electrode displays variations of opposite sign- is strongly influenced by the history of the pulsing procedure. Loops performed by varying the magnitude and sign of the stimulus at each pulsed electrode allow to disentangle their sole contribution at different stages of the process. Electromigration of oxygen ions and vacancies is discussed as participating at the core of the underlying mechanisms for resistance switching.

Resistance switching in silver - manganite contacts

Energy Technology Data Exchange (ETDEWEB)

Gomez-Marlasca, F [Materia Condensada GIA GAIANN CAC -CNEA, and Instituto de Nanociencia y Nanotecnologia, CNEA, Gral Paz 1499 (1650) San Martin, Pcia. Buenos Aires (Argentina); Levy, P, E-mail: levy@cnea.gov.a

2009-05-01

We investigate the electric pulse induced resistance switching in a transition metal oxide-metal contact at room temperature - a non volatile, reversible and multilevel memory device. Using a simple multiterminal configuration, we find that the complementary effect -in which the contact resistance of each pulsed electrode displays variations of opposite sign- is strongly influenced by the history of the pulsing procedure. Loops performed by varying the magnitude and sign of the stimulus at each pulsed electrode allow to disentangle their sole contribution at different stages of the process. Electromigration of oxygen ions and vacancies is discussed as participating at the core of the underlying mechanisms for resistance switching.

Stochastic calculus in physics

International Nuclear Information System (INIS)

Fox, R.F.

1987-01-01

The relationship of Ito-Stratonovich stochastic calculus to studies of weakly colored noise is explained. A functional calculus approach is used to obtain an effective Fokker-Planck equation for the weakly colored noise regime. In a smooth limit, this representation produces the Stratonovich version of the Ito-Stratonovich calculus for white noise. It also provides an approach to steady state behavior for strongly colored noise. Numerical simulation algorithms are explored, and a novel suggestion is made for efficient and accurate simulation of white noise equations

Impact of information cost and switching of trading strategies in an artificial stock market

Science.gov (United States)

Liu, Yi-Fang; Zhang, Wei; Xu, Chao; Vitting Andersen, Jørgen; Xu, Hai-Chuan

2014-08-01

This paper studies the switching of trading strategies and its effect on the market volatility in a continuous double auction market. We describe the behavior when some uninformed agents, who we call switchers, decide whether or not to pay for information before they trade. By paying for the information they behave as informed traders. First we verify that our model is able to reproduce some of the stylized facts in real financial markets. Next we consider the relationship between switching and the market volatility under different structures of investors. We find that there exists a positive relationship between the market volatility and the percentage of switchers. We therefore conclude that the switchers are a destabilizing factor in the market. However, for a given fixed percentage of switchers, the proportion of switchers that decide to buy information at a given moment of time is negatively related to the current market volatility. In other words, if more agents pay for information to know the fundamental value at some time, the market volatility will be lower. This is because the market price is closer to the fundamental value due to information diffusion between switchers.

An analysis of switching and non-switching slot machine player behaviour.

Science.gov (United States)

Coates, Ewan; Blaszczynski, Alex

2013-12-01

Learning theory predicts that, given the repeated choice to bet between two concurrently available slot machines, gamblers will learn to bet more money on the machine with higher expected return (payback percentage) or higher win probability per spin (volatility). The purpose of this study was to investigate whether this occurs when the two machines vary orthogonally on payback percentage and volatility. The sample comprised 52 first year psychology students (mean age = 20.3 years, 20 females, 32 males) who had played a gaming machine at least once in the previous 12 months. Participants were administered a battery of questionnaires designed to assess level of knowledge on the characteristics and operation of poker machines, frequency of poker machine play in the past 12 months, personality traits of impulsivity and capacity for cognitive reflection, and gambling beliefs. For the experimental task, participants were instructed to play on two PC-simulated electronic gaming machines (EGMs or slot machines) that differed on payback percentage and volatility, with the option of freely switching between EGMs after a practice phase. Results indicated that participants were able to easily discriminate between machines and manifested a preference to play machines offering higher payback or volatility. These findings diverged from previous findings of no preference for play on higher payback/volatility machines, potentially due to of the current study's absence of the option to make multi-line and multi-credit bets. It was concluded that return rate parameters like payback percentage and volatility strongly influenced slot machine preference in the absence of betting options like multi-line bets, though more research is needed to determine the effects of such betting options on player distribution of money between multiple EGMs.

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

Energy Technology Data Exchange (ETDEWEB)

Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc [Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003 (United States)

2016-03-14

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

Structure of picosecond pulses of a Q-switched and mode-locked diode-pumped Nd:YAG laser

Energy Technology Data Exchange (ETDEWEB)

Donin, V I; Yakovin, D V; Gribanov, A V [Institute of Automation and Electrometry, Siberian Branch of the Russian Academy of Sciences, Novosibirsk (Russian Federation)

2015-12-31

The pulse duration of a diode-pumped Nd:YAG laser, in which Q-switching with mode-locking (QML regime) is achieved using a spherical mirror and a travelling-wave acousto-optic modulator, is directly measured with a streak camera. It is found that the picosecond pulses can have a non-single-pulse structure, which is explained by excitation of several competing transverse modes in the Q-switching regime with a pulse repetition rate of 1 kHz. In the case of cw mode-locking (without Q-switching), a new (auto-QML) regime is observed, in which the pulse train repetition rate is determined by the frequency of the relaxation oscillations of the laser field while the train contains single picosecond pulses. (control of laser radiation parameters)

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

Limits for Stochastic Reaction Networks

DEFF Research Database (Denmark)

Cappelletti, Daniele

Reaction systems have been introduced in the 70s to model biochemical systems. Nowadays their range of applications has increased and they are fruitfully used in dierent elds. The concept is simple: some chemical species react, the set of chemical reactions form a graph and a rate function...... is associated with each reaction. Such functions describe the speed of the dierent reactions, or their propensities. Two modelling regimes are then available: the evolution of the dierent species concentrations can be deterministically modelled through a system of ODE, while the counts of the dierent species...... at a certain time are stochastically modelled by means of a continuous-time Markov chain. Our work concerns primarily stochastic reaction systems, and their asymptotic properties. In Paper I, we consider a reaction system with intermediate species, i.e. species that are produced and fast degraded along a path...

Testing nonlinearities between Brazilian exchange rate and inflation volatilities

Directory of Open Access Journals (Sweden)

Christiane R. Albuquerque

2006-12-01

Full Text Available There are few studies, directly addressing exchange rate and inflation volatilities, and lack of consensus among them. However, this kind of study is necessary, especially under an inflation-targeting system where the monetary authority must know well price behavior. This article analyses the relation between exchange rate and inflation volatilities using a bivariate GARCH model, and therefore modeling conditional volatilities, fact largely unexplored by the literature. We find a semi-concave relation between those series, and this nonlinearity may explain their apparently disconnection under a floating exchange rate system. The article also shows that traditional tests, with non-conditional volatilities, are not robust.Existem poucos estudos, e pouco consenso, sobre a relação entre as volatilidades cambial e da inflação. Todavia, tais estudos são necessários, especialmente em um regime de metas de inflação onde a autoridade monetária deve conhecer detalhadamente o comportamento dos preços. Existem poucos estudos, e pouco consenso, sobre a relação entre as volatilidades cambial e da inflação. Todavia, tais estudos são necessários, especialmente em um regime de metas de inflação onde a autoridade monetária deve conhecer detalhadamente o comportamento dos preços. Este artigo analisa a relação entre aquelas volatilidades usando um modelo Garch bivariado, modelando, portanto, as volatilidades condicionais, enfoque pouco explorado pela literatura. Encontramos uma relação semi-côncava entre as séries, e esta não-linearidade pode explicar o aparente descolamento das mesmas em períodos de regime cambial flutuante. O artigo também mostra que os testes tradicionais, com volatilidades não-condicionais, não são robustos.

Sharp asymptotics for stochastic dynamics with parallel updating rule

NARCIS (Netherlands)

Nardi, F.R.; Spitoni, C.

2012-01-01

In this paper we study the metastability problem for a stochastic dynamics with a parallel updating rule; in particular we consider a finite volume Probabilistic Cellular Automaton (PCA) in a small external field at low temperature regime. We are interested in the nucleation of the system, i.e., the

Sharp Asymptotics for Stochastic Dynamics with Parallel Updating Rule

NARCIS (Netherlands)

Nardi, F.R.; Spitoni, C.

2012-01-01

In this paper we study the metastability problem for a stochastic dynamics with a parallel updating rule; in particular we consider a finite volume Probabilistic Cellular Automaton (PCA) in a small external field at low temperature regime. We are interested in the nucleation of the system, i.e.,

The restoration of the gold standard after the US Civil War : A volatility analysis

NARCIS (Netherlands)

Meulemann, Max; Uebele, Martin; Wilfling, Bernd

This paper presents a new view on the gold price of greenbacks during and after the American Civil War by analyzing exchange-rate volatility rather than exchange-rate levels. Our empirical investigation detects regimes of high and low volatility alternating in a way that is consistent with a

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...

Integrated Metabolomics and Morphogenesis Reveal Volatile Signaling of the Nematode-Trapping Fungus Arthrobotrys oligospora.

Science.gov (United States)

Wang, Bai-Le; Chen, Yong-Hong; He, Jia-Ning; Xue, Hua-Xi; Yan, Ni; Zeng, Zhi-Jun; Bennett, Joan W; Zhang, Ke-Qin; Niu, Xue-Mei

2018-05-01

The adjustment of metabolic patterns is fundamental to fungal biology and plays vital roles in adaptation to diverse ecological challenges. Nematode-trapping fungi can switch their lifestyle from saprophytic to pathogenic by developing specific trapping devices induced by nematodes to infect their prey as a response to nutrient depletion in nature. However, the chemical identity of the specific fungal metabolites used during the switch remains poorly understood. We hypothesized that these important signal molecules might be volatile in nature. Gas chromatography-mass spectrometry was used to carry out comparative analysis of fungal metabolomics during the saprophytic and pathogenic lifestyles of the model species Arthrobotrys oligospora Two media commonly used in research on this species, cornmeal agar (CMA) and potato dextrose agar (PDA), were chosen for use in this study. The fungus produced a small group of volatile furanone and pyrone metabolites that were associated with the switch from the saprophytic to the pathogenic stage. A. oligospora fungi grown on CMA tended to produce more traps and employ attractive furanones to improve the utilization of traps, while fungi grown on PDA developed fewer traps and used nematode-toxic furanone metabolites to compensate for insufficient traps. Another volatile pyrone metabolite, maltol, was identified as a morphological regulator for enhancing trap formation. Deletion of the gene AOL_s00079g496 in A. oligospora led to increased amounts of the furanone attractant (2-fold) in mutants and enhanced the attractive activity (1.5-fold) of the fungus, while it resulted in decreased trap formation. This investigation provides new insights regarding the comprehensive tactics of fungal adaptation to environmental stress, integrating both morphological and metabolomic mechanisms. IMPORTANCE Nematode-trapping fungi are a unique group of soil-living fungi that can switch from the saprophytic to the pathogenic lifestyle once they come

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).

Modeling of plasma flow switches at low, intermediate and high energies

International Nuclear Information System (INIS)

Bowers, R.L.; Brownell, J.H.; Greene, A.E.; Peterson, D.L.; Roderick, N.; Turchi, P.

1992-01-01

Inductively stored pulsed power technology has been used over the past thirty years to produce multi-megaamp currents to implode low inductance loads and produce x-radiation. Because of the large difference in timescales for the delivery of magnetic energy to the load and the desire for high power x-radiation output (short timescale for the implosion), most inductively stored systems require at least one opening switch. The design and understanding of fast, efficient opening switches for multi-megaamp systems represents a long standing problem in pulsed power research. The Los Alamos Foil Implosion Project uses inductively stored magnetic energy to implode thin metallic liners. A plasma flow switch (PFS) has been investigated as the final pulse shaping step for this systems. The PFS consists of a wire array and a barrier foil located upstream from the load region. Several stages can be identified in the performance of the plasma flow switch. These are: (1) the vaporization of the wire array; (2) the assembly of the initiated plasma on tie barrier foil to form the switch plasma; (3) the motion of the switch plasma down the coaxial barrel; and (4) current switching to the load (the actual switching stage). The fourth stage affects the switch's efficiency, as well as the quality of the load implosion. Instabilities may develop during any of these four stages, and their presence may seriously degrade the structure of the switch plasma. Two primary criteria may be used to characterize good switching. The first is switching efficiency. A second criterion is transferred to the load during or after switching. This paper summarizes the computational design of the PFS experiments carried out on Pegasus 1. We conclude by considering the implications of these results for the design of a PFS for the higher energy regime (Procyon) regime

Sharp asymptotics for stochastic dynamics with parallel updating rule

NARCIS (Netherlands)

Nardi, F.R.; Spitoni, C.

2012-01-01

In this paper we study the metastability problem for a stochastic dynamics with a parallel updating rule; in particular we consider a ¿nite volume Probabilistic Cellular Automaton (PCA) in a small external ¿eld at low temperature regime. We are interested in the nucleation of the system, i.e., the

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

On relative spatial diffusion in plasma and fluid turbulences: clumps, Richardson's law and intrinsic stochasticity

International Nuclear Information System (INIS)

Misguich, J.H.; Balescu, R.

1981-02-01

Three different time regimes are presented for relative spatial diffusion of charged particles in fluctuating electric fields, which behave like tau 3 , exp (tau) and tau 3 , respectively. The first regime, corresponding to a quasi-linear description of the trajectories, is analogous to the one observed in fluid turbulence and is valid in the limit of a small amplitude turbulent spectrum, or for not too small initial separation of the particles. The third regime, appearing for long times, describes the diffusion of independent particles at very large separations. Its existence is ensured by the nonlinear renormalization of the propagators. The second, intermediate, regime appears in a stochastic treatment of the renormalization effect for particles with a very small spatial and velocity difference, and describes Dupree's clumps diffusion. The appearance of the corresponding regime is similar to that of the Suzuki scaling regime of non-linear Langevin equations. It is also shown that the clumps have a behaviour similar to an intrinsic stochasticity, but which is of extrinsic nature. Similar failure of the quasi-linear approximation for spacific velocity domains has been previously studied and solved for classical Landau collisions, as well as for pitch angle diffusion where renormalization effects have been proved also to be important

Pemodelan Markov Switching Dengan Time-varying Transition Probability

OpenAIRE

Savitri, Anggita Puri; Warsito, Budi; Rahmawati, Rita

2016-01-01

Exchange rate or currency is an economic variable which reflects country's state of economy. It fluctuates over time because of its ability to switch the condition or regime caused by economic and political factors. The changes in the exchange rate are depreciation and appreciation. Therefore, it could be modeled using Markov Switching with Time-Varying Transition Probability which observe the conditional changes and use information variable. From this model, time-varying transition probabili...

Ultrafast optical switching in three-dimensional photonic crystals

OpenAIRE

Mazurenko, D.A.