The Multiple Stochastic Integral

The Multiple Stochastic Integral

Author: David Douglas Engel

Publisher: American Mathematical Soc.

Published: 1982

Total Pages: 91

ISBN-13: 0821822659

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The author establishes a relation between the theory of multiple stochastic integration and the theory of Banach space valued measures.


Introduction to Stochastic Integration

Introduction to Stochastic Integration

Author: Hui-Hsiung Kuo

Publisher: Springer Science & Business Media

Published: 2006-02-04

Total Pages: 290

ISBN-13: 0387310576

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Also called Ito calculus, the theory of stochastic integration has applications in virtually every scientific area involving random functions. This introductory textbook provides a concise introduction to the Ito calculus. From the reviews: "Introduction to Stochastic Integration is exactly what the title says. I would maybe just add a ‘friendly’ introduction because of the clear presentation and flow of the contents." --THE MATHEMATICAL SCIENCES DIGITAL LIBRARY


Stochastic Integration

Stochastic Integration

Author: Michel Metivier

Publisher: Academic Press

Published: 2014-07-10

Total Pages: 209

ISBN-13: 1483218783

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Probability and Mathematical Statistics: A Series of Monographs and Textbooks: Stochastic Integration focuses on the processes, methodologies, and approaches involved in stochastic integration. The publication first takes a look at the Ito formula, stochastic integral equations, and martingales and semimartingales. Discussions focus on Meyer process and decomposition theorem, inequalities, examples of stochastic differential equations, general stochastic integral equations, and applications of the Ito formula. The text then elaborates on stochastic measures, including stochastic measures and related integration and the Riesz representation theorem. The manuscript tackles the special features of infinite dimensional stochastic integration, as well as the isometric integral of a Hubert-valued square integrable martingale, cylindrical processes, and stochastic integral with respect to 2-cylindrical martingales with finite quadratic variation. The book is a valuable reference for mathematicians and researchers interested in stochastic integration.


Stochastic Processes for Physicists

Stochastic Processes for Physicists

Author: Kurt Jacobs

Publisher: Cambridge University Press

Published: 2010-02-18

Total Pages: 203

ISBN-13: 1139486799

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Stochastic processes are an essential part of numerous branches of physics, as well as in biology, chemistry, and finance. This textbook provides a solid understanding of stochastic processes and stochastic calculus in physics, without the need for measure theory. In avoiding measure theory, this textbook gives readers the tools necessary to use stochastic methods in research with a minimum of mathematical background. Coverage of the more exotic Levy processes is included, as is a concise account of numerical methods for simulating stochastic systems driven by Gaussian noise. The book concludes with a non-technical introduction to the concepts and jargon of measure-theoretic probability theory. With over 70 exercises, this textbook is an easily accessible introduction to stochastic processes and their applications, as well as methods for numerical simulation, for graduate students and researchers in physics.


Chaos Expansions, Multiple Wiener-Ito Integrals, and Their Applications

Chaos Expansions, Multiple Wiener-Ito Integrals, and Their Applications

Author: Christian Houdre

Publisher: CRC Press

Published: 1994-04-05

Total Pages: 396

ISBN-13: 9780849380723

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The study of chaos expansions and multiple Wiener-Ito integrals has become a field of considerable interest in applied and theoretical areas of probability, stochastic processes, mathematical physics, and statistics. Divided into four parts, this book features a wide selection of surveys and recent developments on these subjects. Part 1 introduces the concepts, techniques, and applications of multiple Wiener-Ito and related integrals. The second part includes papers on chaos random variables appearing in many limiting theorems. Part 3 is devoted to mixing, zero-one laws, and path continuity properties of chaos processes. The final part presents several applications to stochastic analysis.


Stochastic Integrals

Stochastic Integrals

Author: H. P. McKean

Publisher: Academic Press

Published: 2014-06-20

Total Pages: 157

ISBN-13: 1483259234

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Stochastic Integrals discusses one area of diffusion processes: the differential and integral calculus based upon the Brownian motion. The book reviews Gaussian families, construction of the Brownian motion, the simplest properties of the Brownian motion, Martingale inequality, and the law of the iterated logarithm. It also discusses the definition of the stochastic integral by Wiener and by Ito, the simplest properties of the stochastic integral according to Ito, and the solution of the simplest stochastic differential equation. The book explains diffusion, Lamperti's method, forward equation, Feller's test for the explosions, Cameron-Martin's formula, the Brownian local time, and the solution of dx=e(x) db + f(x) dt for coefficients with bounded slope. It also tackles Weyl's lemma, diffusions on a manifold, Hasminski's test for explosions, covering Brownian motions, Brownian motions on a Lie group, and Brownian motion of symmetric matrices. The book gives as example of a diffusion on a manifold with boundary the Brownian motion with oblique reflection on the closed unit disk of R squared. The text is suitable for economists, scientists, or researchers involved in probabilistic models and applied mathematics.


Stochastic Integration Theory

Stochastic Integration Theory

Author: Peter Medvegyev

Publisher: Oxford University Press, USA

Published: 2007-07-26

Total Pages: 629

ISBN-13: 0199215251

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This graduate level text covers the theory of stochastic integration, an important area of Mathematics that has a wide range of applications, including financial mathematics and signal processing. Aimed at graduate students in Mathematics, Statistics, Probability, Mathematical Finance, and Economics, the book not only covers the theory of the stochastic integral in great depth but also presents the associated theory (martingales, Levy processes) and important examples (Brownianmotion, Poisson process).