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Parameter Estimation In Stochastic Differential Equations
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Book Synopsis Parameter Estimation in Stochastic Differential Equations by : Jaya P. N. Bishwal
Download or read book Parameter Estimation in Stochastic Differential Equations written by Jaya P. N. Bishwal and published by Springer. This book was released on 2007-09-26 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.
Book Synopsis Parameter Estimation in Stochastic Volatility Models by : Jaya P. N. Bishwal
Download or read book Parameter Estimation in Stochastic Volatility Models written by Jaya P. N. Bishwal and published by Springer Nature. This book was released on 2022-08-06 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While there is ample research to document stochastic differential equation models driven by Brownian motion based on discrete observations of the underlying diffusion process, these traditional methods often fail to estimate the unknown parameters in the unobserved volatility processes. This text studies the second order rate of weak convergence to normality to obtain refined inference results like confidence interval, as well as nontraditional continuous time stochastic volatility models driven by fractional Levy processes. By incorporating jumps and long memory into the volatility process, these new methods will help better predict option pricing and stock market crash risk. Some simulation algorithms for numerical experiments are provided.
Book Synopsis Parameter Estimation in Fractional Diffusion Models by : Kęstutis Kubilius
Download or read book Parameter Estimation in Fractional Diffusion Models written by Kęstutis Kubilius and published by Springer. This book was released on 2018-01-04 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. For many years now, standard Brownian motion has been (and still remains) a popular model of randomness used to investigate processes in the natural sciences, financial markets, and the economy. The substantial limitation in the use of stochastic diffusion models with Brownian motion is due to the fact that the motion has independent increments, and, therefore, the random noise it generates is “white,” i.e., uncorrelated. However, many processes in the natural sciences, computer networks and financial markets have long-term or short-term dependences, i.e., the correlations of random noise in these processes are non-zero, and slowly or rapidly decrease with time. In particular, models of financial markets demonstrate various kinds of memory and usually this memory is modeled by fractional Brownian diffusion. Therefore, the book constructs diffusion models with memory and provides simple and suitable parameter estimation methods in these models, making it a valuable resource for all researchers in this field. The book is addressed to specialists and researchers in the theory and statistics of stochastic processes, practitioners who apply statistical methods of parameter estimation, graduate and post-graduate students who study mathematical modeling and statistics.
Book Synopsis Asymptotic Parameter Estimation Theory for Stochastic Differential Equations [microform] by : Raphael Abel Kasonga
Download or read book Asymptotic Parameter Estimation Theory for Stochastic Differential Equations [microform] written by Raphael Abel Kasonga and published by National Library of Canada. This book was released on 1986 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Parameter Estimation for Stochastic Processes by : Yu. A. Kutoyants
Download or read book Parameter Estimation for Stochastic Processes written by Yu. A. Kutoyants and published by . This book was released on 1984 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Estimating the Parameters of Stochastic Differential Equations by Monte Carlo Methods by : A. Stan Hurn
Download or read book Estimating the Parameters of Stochastic Differential Equations by Monte Carlo Methods written by A. Stan Hurn and published by . This book was released on 1995 with total page 7 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Stochastic Analysis with Financial Applications by : Arturo Kohatsu-Higa
Download or read book Stochastic Analysis with Financial Applications written by Arturo Kohatsu-Higa and published by Springer Science & Business Media. This book was released on 2011-07-22 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. The book also covers the areas of backward stochastic differential equations via the (non-linear) G-Brownian motion and the case of jump processes. Concerning the applications to finance, many of the articles deal with the valuation and hedging of credit risk in various forms, and include recent results on markets with transaction costs.
Book Synopsis Statistical Methods for Stochastic Differential Equations by : Mathieu Kessler
Download or read book Statistical Methods for Stochastic Differential Equations written by Mathieu Kessler and published by CRC Press. This book was released on 2012-05-17 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to the topic at hand and builds gradually towards discussing recent research. The book covers Wiener-driven equations as well as stochastic differential equations with jumps, including continuous-time ARMA processes and COGARCH processes. It presents a spectrum of estimation methods, including nonparametric estimation as well as parametric estimation based on likelihood methods, estimating functions, and simulation techniques. Two chapters are devoted to high-frequency data. Multivariate models are also considered, including partially observed systems, asynchronous sampling, tests for simultaneous jumps, and multiscale diffusions. Statistical Methods for Stochastic Differential Equations is useful to the theoretical statistician and the probabilist who works in or intends to work in the field, as well as to the applied statistician or financial econometrician who needs the methods to analyze biological or financial time series.
Book Synopsis Stochastic Models: Estimation and Control: by : Maybeck
Download or read book Stochastic Models: Estimation and Control: written by Maybeck and published by Academic Press. This book was released on 1982-08-10 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Models: Estimation and Control: v. 2
Book Synopsis Modeling, Estimation, and Their Applications for Distributed Parameter Systems by : Yoshikazu Sawaragi
Download or read book Modeling, Estimation, and Their Applications for Distributed Parameter Systems written by Yoshikazu Sawaragi and published by Springer. This book was released on 1978 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Modeling with Itô Stochastic Differential Equations by : E. Allen
Download or read book Modeling with Itô Stochastic Differential Equations written by E. Allen and published by Springer Science & Business Media. This book was released on 2007-03-08 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains a procedure for constructing realistic stochastic differential equation models for randomly varying systems in biology, chemistry, physics, engineering, and finance. Introductory chapters present the fundamental concepts of random variables, stochastic processes, stochastic integration, and stochastic differential equations. These concepts are explained in a Hilbert space setting which unifies and simplifies the presentation.
Book Synopsis Applied Stochastic Differential Equations by : Simo Särkkä
Download or read book Applied Stochastic Differential Equations written by Simo Särkkä and published by Cambridge University Press. This book was released on 2019-05-02 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic differential equations are differential equations whose solutions are stochastic processes. They exhibit appealing mathematical properties that are useful in modeling uncertainties and noisy phenomena in many disciplines. This book is motivated by applications of stochastic differential equations in target tracking and medical technology and, in particular, their use in methodologies such as filtering, smoothing, parameter estimation, and machine learning. It builds an intuitive hands-on understanding of what stochastic differential equations are all about, but also covers the essentials of Itô calculus, the central theorems in the field, and such approximation schemes as stochastic Runge–Kutta. Greater emphasis is given to solution methods than to analysis of theoretical properties of the equations. The book's practical approach assumes only prior understanding of ordinary differential equations. The numerous worked examples and end-of-chapter exercises include application-driven derivations and computational assignments. MATLAB/Octave source code is available for download, promoting hands-on work with the methods.
Book Synopsis Parameter Estimation in Nonlinear Dynamic Systems by : W. J. H. Stortelder
Download or read book Parameter Estimation in Nonlinear Dynamic Systems written by W. J. H. Stortelder and published by . This book was released on 1998 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Theory and Statistical Applications of Stochastic Processes by : Yuliya Mishura
Download or read book Theory and Statistical Applications of Stochastic Processes written by Yuliya Mishura and published by John Wiley & Sons. This book was released on 2018-01-04 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is concerned with the theory of stochastic processes and the theoretical aspects of statistics for stochastic processes. It combines classic topics such as construction of stochastic processes, associated filtrations, processes with independent increments, Gaussian processes, martingales, Markov properties, continuity and related properties of trajectories with contemporary subjects: integration with respect to Gaussian processes, Itȏ integration, stochastic analysis, stochastic differential equations, fractional Brownian motion and parameter estimation in diffusion models.
Book Synopsis Recursive Estimation and Control for Stochastic Systems by : Hanfu Chen
Download or read book Recursive Estimation and Control for Stochastic Systems written by Hanfu Chen and published by John Wiley & Sons. This book was released on 1985 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: This self-contained reference for statisticians and engineers in system and control theory, analyzes the effect of convergent recursive estimation algorithms and stochastic approximation on the dependent noise case and the classic independent case. It discusses control and adaptive control problems related to recursive estimation, and introduces the combined probabilistic and differential equation method of data analysis.
Book Synopsis Parameter Estimation in Engineering and Science by : James Vere Beck
Download or read book Parameter Estimation in Engineering and Science written by James Vere Beck and published by James Beck. This book was released on 1977 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to and survey of parameter estimation; Probability; Introduction to statistics; Parameter estimation methods; Introduction to linear estimation; Matrix analysis for linear parameter estimation; Minimization of sum of squares functions for models nonlinear in parameters; Design of optimal experiments.
Book Synopsis Stochastic Analysis with Financial Applications by : Arturo Kohatsu-Higa
Download or read book Stochastic Analysis with Financial Applications written by Arturo Kohatsu-Higa and published by Birkhäuser. This book was released on 2011-07-22 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. The book also covers the areas of backward stochastic differential equations via the (non-linear) G-Brownian motion and the case of jump processes. Concerning the applications to finance, many of the articles deal with the valuation and hedging of credit risk in various forms, and include recent results on markets with transaction costs.
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