Stochastic Differential Equations And Processes

Author : Rong SITU
Publisher : Springer Science & Business Media
Page : 444 pages
File Size : 52,7 Mb
Release : 2006-05-06
Category : Technology & Engineering
ISBN : 9780387251752

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Theory of Stochastic Differential Equations with Jumps and Applications by Rong SITU Pdf

Stochastic differential equations (SDEs) are a powerful tool in science, mathematics, economics and finance. This book will help the reader to master the basic theory and learn some applications of SDEs. In particular, the reader will be provided with the backward SDE technique for use in research when considering financial problems in the market, and with the reflecting SDE technique to enable study of optimal stochastic population control problems. These two techniques are powerful and efficient, and can also be applied to research in many other problems in nature, science and elsewhere.

Author : N. Ikeda,S. Watanabe
Publisher : Elsevier
Page : 572 pages
File Size : 42,6 Mb
Release : 2014-06-28
Category : Mathematics
ISBN : 9781483296159

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Stochastic Differential Equations and Diffusion Processes by N. Ikeda,S. Watanabe Pdf

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

Author : Mathieu Kessler,Alexander Lindner,Michael Sorensen
Publisher : CRC Press
Page : 507 pages
File Size : 46,5 Mb
Release : 2012-05-17
Category : Mathematics
ISBN : 9781439849767

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Statistical Methods for Stochastic Differential Equations by Mathieu Kessler,Alexander Lindner,Michael Sorensen Pdf

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 th

Author : Simo Särkkä,Arno Solin
Publisher : Cambridge University Press
Page : 327 pages
File Size : 51,8 Mb
Release : 2019-05-02
Category : Business & Economics
ISBN : 9781316510087

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Applied Stochastic Differential Equations by Simo Särkkä,Arno Solin Pdf

With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.

Author : Peter E. Kloeden,Eckhard Platen
Publisher : Springer Science & Business Media
Page : 666 pages
File Size : 48,7 Mb
Release : 2013-04-17
Category : Mathematics
ISBN : 9783662126165

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Numerical Solution of Stochastic Differential Equations by Peter E. Kloeden,Eckhard Platen Pdf

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

Author : Avner Friedman
Publisher : Academic Press
Page : 248 pages
File Size : 55,7 Mb
Release : 2014-06-20
Category : Mathematics
ISBN : 9781483217871

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Stochastic Differential Equations and Applications by Avner Friedman Pdf

Stochastic Differential Equations and Applications, Volume 1 covers the development of the basic theory of stochastic differential equation systems. This volume is divided into nine chapters. Chapters 1 to 5 deal with the basic theory of stochastic differential equations, including discussions of the Markov processes, Brownian motion, and the stochastic integral. Chapter 6 examines the connections between solutions of partial differential equations and stochastic differential equations, while Chapter 7 describes the Girsanov’s formula that is useful in the stochastic control theory. Chapters 8 and 9 evaluate the behavior of sample paths of the solution of a stochastic differential system, as time increases to infinity. This book is intended primarily for undergraduate and graduate mathematics students.

Author : Wojbor A. Woyczyński
Publisher : CRC Press
Page : 138 pages
File Size : 55,9 Mb
Release : 2022-03-09
Category : Mathematics
ISBN : 9781000475357

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Diffusion Processes, Jump Processes, and Stochastic Differential Equations by Wojbor A. Woyczyński Pdf

Diffusion Processes, Jump Processes, and Stochastic Differential Equations provides a compact exposition of the results explaining interrelations between diffusion stochastic processes, stochastic differential equations and the fractional infinitesimal operators. The draft of this book has been extensively classroom tested by the author at Case Western Reserve University in a course that enrolled seniors and graduate students majoring in mathematics, statistics, engineering, physics, chemistry, economics and mathematical finance. The last topic proved to be particularly popular among students looking for careers on Wall Street and in research organizations devoted to financial problems. Features Quickly and concisely builds from basic probability theory to advanced topics Suitable as a primary text for an advanced course in diffusion processes and stochastic differential equations Useful as supplementary reading across a range of topics.

Author : K. A. Brownlee
Publisher : Unknown
Page : 616 pages
File Size : 44,5 Mb
Release : 1984
Category : Experimental design
ISBN : UCSD:31822001754118

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Statistical Theory and Methodology in Science and Engineering by K. A. Brownlee Pdf

Mathematical ideas; Statistical ideas; The binomial, hypergeometric, and poisson distributions; An introduction to queuing theory; The multinomial distribution and contingency tables; Some tests of the hypothesis of randomness: control charts; Some nonparametric tests; The partitioning of sums of squares; tests of equality of variances and means; One-way analysis of variance; Simple linear regression; The bivariate normal distribution and the correlation coefficient; Regression on several independent variables; Two-way and nested analysis of variance; Three-way and four-way analysis of variance; Partially hierarchical situations; Some simple experimental designs; Appendix.

Author : Sasha Cyganowski,Peter Kloeden,Jerzy Ombach
Publisher : Springer Science & Business Media
Page : 323 pages
File Size : 54,5 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9783642561443

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From Elementary Probability to Stochastic Differential Equations with MAPLE® by Sasha Cyganowski,Peter Kloeden,Jerzy Ombach Pdf

This is an introduction to probabilistic and statistical concepts necessary to understand the basic ideas and methods of stochastic differential equations. Based on measure theory, which is introduced as smoothly as possible, it provides practical skills in the use of MAPLE in the context of probability and its applications. It offers to graduates and advanced undergraduates an overview and intuitive background for more advanced studies.

Author : Ludwig Arnold
Publisher : Wiley-Interscience
Page : 250 pages
File Size : 51,7 Mb
Release : 1974-04-23
Category : Mathematics
ISBN : MINN:319510001592419

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Stochastic Differential Equations by Ludwig Arnold Pdf

Fundamentals of probability theory; Markov processes and diffusion processes; Wiener process and white noise; Stochastic integrals; The stochastic integral as a stochastic process, stochastic differentials; Stochastic differential equations, existence and uniqueness of solutions; Properties of the solutions of stochastic differential equations; Linear stochastic differentials equations; The solutions of stochastic differentail equations as Markov and diffusion processes; Questions of modeling and approximation; Stability of stochastic dynamic systems; Optimal filtering of a disturbed signal; Optimal control of stochastic dynamic systems.

Author : Kiyosi Itō
Publisher : American Mathematical Soc.
Page : 51 pages
File Size : 50,9 Mb
Release : 1951
Category : Differential equations
ISBN : 9780821812044

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On Stochastic Differential Equations by Kiyosi Itō Pdf

Author : Imre Csiszar,Gy. Michaletzky
Publisher : Springer Science & Business Media
Page : 358 pages
File Size : 52,7 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461219804

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Stochastic Differential and Difference Equations by Imre Csiszar,Gy. Michaletzky Pdf

Author : E. Allen
Publisher : Springer Science & Business Media
Page : 239 pages
File Size : 50,9 Mb
Release : 2007-03-08
Category : Mathematics
ISBN : 9781402059537

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Modeling with Itô Stochastic Differential Equations by E. Allen Pdf

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.

Author : Mathieu Kessler,Alexander Lindner,Michael Sorensen
Publisher : CRC Press
Page : 509 pages
File Size : 48,9 Mb
Release : 2012-05-17
Category : Mathematics
ISBN : 9781439849408

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Statistical Methods for Stochastic Differential Equations by Mathieu Kessler,Alexander Lindner,Michael Sorensen Pdf

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.

Author : Łukasz Delong
Publisher : Springer Science & Business Media
Page : 285 pages
File Size : 54,6 Mb
Release : 2013-06-12
Category : Mathematics
ISBN : 9781447153313

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Backward Stochastic Differential Equations with Jumps and Their Actuarial and Financial Applications by Łukasz Delong Pdf

Backward stochastic differential equations with jumps can be used to solve problems in both finance and insurance. Part I of this book presents the theory of BSDEs with Lipschitz generators driven by a Brownian motion and a compensated random measure, with an emphasis on those generated by step processes and Lévy processes. It discusses key results and techniques (including numerical algorithms) for BSDEs with jumps and studies filtration-consistent nonlinear expectations and g-expectations. Part I also focuses on the mathematical tools and proofs which are crucial for understanding the theory. Part II investigates actuarial and financial applications of BSDEs with jumps. It considers a general financial and insurance model and deals with pricing and hedging of insurance equity-linked claims and asset-liability management problems. It additionally investigates perfect hedging, superhedging, quadratic optimization, utility maximization, indifference pricing, ambiguity risk minimization, no-good-deal pricing and dynamic risk measures. Part III presents some other useful classes of BSDEs and their applications. This book will make BSDEs more accessible to those who are interested in applying these equations to actuarial and financial problems. It will be beneficial to students and researchers in mathematical finance, risk measures, portfolio optimization as well as actuarial practitioners.