Diffusions, Markov Processes and Martingales: Ito Calculus v. 2
Wiley (Publisher)
Published on 14. October 1987
Book
Hardback
490 pages
978-0-471-91482-2 (ISBN)
Description
The main themes of this book are stochastic integrals, stochastic differential equations, excursion theory and 'the general theory of processes'. Much effort has gone into the attempt to make these subjects accessible by providing many concrete examples illustrating techniques of calculation, and by treating all topics (including stochastic differential geometry) from the ground up, starting from the simplest case. In particular, the theory is developed first for the 'continuous' case, by far the most important in practice, while the general theory (and its applications) forms the last chapter. Many of the examples and many of the proofs are new and some important methods of calculation appear for the first time in a book. Stochastic differential equations are widely used in practice: in electrical engineering; in controlling systems subject to random 'noise'; in modelling economic systems; and in several branches of physics and chemistry. They are also used to great effect in other branches of mathematics, such as the theory of partial differential equations, differential geometry and complex analysis.
Researchers and practitioners in all these fields will find it a useful and highly readable reference work.
Researchers and practitioners in all these fields will find it a useful and highly readable reference work.
More details
Series
Language
English
Place of publication
Chichester
United Kingdom
Publishing group
John Wiley and Sons Ltd
Target group
College/higher education
Professional and scholarly
Illustrations
illustrations, bibliography, index
Dimensions
Height: 57 mm
Width: 36 mm
Weight
840 gr
ISBN-13
978-0-471-91482-2 (9780471914822)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Content
INTRODUCTION TO ITO CALCULUS: Some Motivating Remarks; Some Fundamental Ideas: Previsible Processes, Localizabtion, etc; The Elementary Theory of Finite-Variation Processes; Stochastic Integrals: The L2 Theory; Stochastic Integrals with Respect to Continuous Semimartingales; Applications of Ito 's Formula; STOCHASTIC DIFFERENTIAL EQUATIONS AND DIFFUSIONS: Introduction; Pathwise Uniqueness, Strong SDEs, Flows; Weak Solutions, Uniqueness in Law; Martingale Problems, Markov Property; Overture to Stochastic Differential Geometry; One-Dimensional SDEs; One-Dimensional Diffusions; THE GENERAL THEORY: Orientation; The Debut and Section Theorems; Optional Projections and Filtering; Characterizing Previsible Times; Dual Previsible Projections; The Meyer Decomposition Theorem; Stochastic Integration: The General Case; Excursion Theory.