Statistical Methods For Stochastic Differential Equations
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Statistical Methods For Stochastic Differential Equations
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Author : Mathieu Kessler
language : en
Publisher: CRC Press
Release Date : 2012-05-17
Statistical Methods For Stochastic Differential Equations written by Mathieu Kessler and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-17 with Mathematics categories.
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.
Simulation And Inference For Stochastic Differential Equations
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Author : Stefano M. Iacus
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-27
Simulation And Inference For Stochastic Differential Equations written by Stefano M. Iacus and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-27 with Computers categories.
This book covers a highly relevant and timely topic that is of wide interest, especially in finance, engineering and computational biology. The introductory material on simulation and stochastic differential equation is very accessible and will prove popular with many readers. While there are several recent texts available that cover stochastic differential equations, the concentration here on inference makes this book stand out. No other direct competitors are known to date. With an emphasis on the practical implementation of the simulation and estimation methods presented, the text will be useful to practitioners and students with minimal mathematical background. What’s more, because of the many R programs, the information here is appropriate for many mathematically well educated practitioners, too.
Numerical Solution Of Stochastic Differential Equations
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Author : Peter E. Kloeden
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-15
Numerical Solution Of Stochastic Differential Equations written by Peter E. Kloeden and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-15 with Mathematics categories.
The numerical analysis of stochastic differential equations (SDEs) differs significantly from that of ordinary differential equations. This book provides an easily accessible introduction to SDEs, their applications and the numerical methods to solve such equations. From the reviews: "The authors draw upon their own research and experiences in obviously many disciplines... considerable time has obviously been spent writing this in the simplest language possible." --ZAMP
Statistical Analysis Of Observations Of Increasing Dimension
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Author : V.L. Girko
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Statistical Analysis Of Observations Of Increasing Dimension written by V.L. Girko and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.
Statistical Analysis of Observations of Increasing Dimension is devoted to the investigation of the limit distribution of the empirical generalized variance, covariance matrices, their eigenvalues and solutions of the system of linear algebraic equations with random coefficients, which are an important function of observations in multidimensional statistical analysis. A general statistical analysis is developed in which observed random vectors may not have density and their components have an arbitrary dependence structure. The methods of this theory have very important advantages in comparison with existing methods of statistical processing. The results have applications in nuclear and statistical physics, multivariate statistical analysis in the theory of the stability of solutions of stochastic differential equations, in control theory of linear stochastic systems, in linear stochastic programming, in the theory of experiment planning.
Recent Advances In Stochastic Modeling And Data Analysis
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Author : Christos H. Skiadas
language : en
Publisher: World Scientific
Release Date : 2007
Recent Advances In Stochastic Modeling And Data Analysis written by Christos H. Skiadas and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Mathematics categories.
This volume presents the most recent applied and methodological issues in stochastic modeling and data analysis. The contributions cover various fields such as stochastic processes and applications, data analysis methods and techniques, Bayesian methods, biostatistics, econometrics, sampling, linear and nonlinear models, networks and queues, survival analysis, and time series. The volume presents new results with potential for solving real-life problems and provides novel methods for solving these problems by analyzing the relevant data. The use of recent advances in different fields is emphasized, especially new optimization and statistical methods, data warehouse, data mining and knowledge systems, neural computing, and bioinformatics. Sample Chapter(s). Chapter 1: An approach to Stochastic Process using Quasi-Arithmetic Means (373 KB). Contents: Stochastic Processes and Models; Distributions; Insurance; Stochastic Modeling for Healthcare Management; Markov and Semi Markov Models; Parametric/Non-Parametric; Dynamical Systems/Forecasting; Modeling and Stochastic Modeling; Statistical Applications in Socioeconimic Problems; Sampling and Optimization Problems; Data Mining and Applications; Clustering and Classification; Applications of Data Analysis; Miscellaneous. Readership: Researchers in probability and statistics, stochastics and fuzzy logic.
Parameter Estimation In Stochastic Differential Equations
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Author : Jaya P. N. Bishwal
language : en
Publisher: Springer
Release Date : 2007-09-26
Parameter Estimation In Stochastic Differential Equations written by Jaya P. N. Bishwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-26 with Mathematics categories.
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.
Numerical Solution Of Stochastic Differential Equations With Jumps In Finance
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Author : Eckhard Platen
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-23
Numerical Solution Of Stochastic Differential Equations With Jumps In Finance written by Eckhard Platen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-23 with Mathematics categories.
In financial and actuarial modeling and other areas of application, stochastic differential equations with jumps have been employed to describe the dynamics of various state variables. The numerical solution of such equations is more complex than that of those only driven by Wiener processes, described in Kloeden & Platen: Numerical Solution of Stochastic Differential Equations (1992). The present monograph builds on the above-mentioned work and provides an introduction to stochastic differential equations with jumps, in both theory and application, emphasizing the numerical methods needed to solve such equations. It presents many new results on higher-order methods for scenario and Monte Carlo simulation, including implicit, predictor corrector, extrapolation, Markov chain and variance reduction methods, stressing the importance of their numerical stability. Furthermore, it includes chapters on exact simulation, estimation and filtering. Besides serving as a basic text on quantitative methods, it offers ready access to a large number of potential research problems in an area that is widely applicable and rapidly expanding. Finance is chosen as the area of application because much of the recent research on stochastic numerical methods has been driven by challenges in quantitative finance. Moreover, the volume introduces readers to the modern benchmark approach that provides a general framework for modeling in finance and insurance beyond the standard risk-neutral approach. It requires undergraduate background in mathematical or quantitative methods, is accessible to a broad readership, including those who are only seeking numerical recipes, and includes exercises that help the reader develop a deeper understanding of the underlying mathematics.
Statistics Of Random Processes Ii
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Author : Robert Shevilevich Lipt︠s︡er
language : en
Publisher: Springer Science & Business Media
Release Date : 2001
Statistics Of Random Processes Ii written by Robert Shevilevich Lipt︠s︡er and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Mathematics categories.
"Written by two renowned experts in the field, the books under review contain a thorough and insightful treatment of the fundamental underpinnings of various aspects of stochastic processes as well as a wide range of applications. Providing clear exposition, deep mathematical results, and superb technical representation, they are masterpieces of the subject of stochastic analysis and nonlinear filtering....These books...will become classics." --SIAM REVIEW
Parameter Estimation In Fractional Diffusion Models
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Author : Kęstutis Kubilius
language : en
Publisher: Springer
Release Date : 2018-01-04
Parameter Estimation In Fractional Diffusion Models written by Kęstutis Kubilius and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-04 with Mathematics categories.
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.
Statistics For Finance
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Author : Erik Lindström
language : en
Publisher: CRC Press
Release Date : 2018-09-03
Statistics For Finance written by Erik Lindström and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Business & Economics categories.
Statistics for Finance develops students’ professional skills in statistics with applications in finance. Developed from the authors’ courses at the Technical University of Denmark and Lund University, the text bridges the gap between classical, rigorous treatments of financial mathematics that rarely connect concepts to data and books on econometrics and time series analysis that do not cover specific problems related to option valuation. The book discusses applications of financial derivatives pertaining to risk assessment and elimination. The authors cover various statistical and mathematical techniques, including linear and nonlinear time series analysis, stochastic calculus models, stochastic differential equations, Itō’s formula, the Black–Scholes model, the generalized method-of-moments, and the Kalman filter. They explain how these tools are used to price financial derivatives, identify interest rate models, value bonds, estimate parameters, and much more. This textbook will help students understand and manage empirical research in financial engineering. It includes examples of how the statistical tools can be used to improve value-at-risk calculations and other issues. In addition, end-of-chapter exercises develop students’ financial reasoning skills.