Diffusions, Markov Processes, and Martingales, Volume 2: Ito Calculus / Edition 2

Diffusions, Markov Processes, and Martingales, Volume 2: Ito Calculus / Edition 2

by L. C. G. Rogers, David Williams
     
 

ISBN-10: 0521775930

ISBN-13: 9780521775939

Pub. Date: 06/28/2014

Publisher: Cambridge University Press

The second volume concentrates on stochastic integrals, stochastic differential equations, excursion theory and the general theory of processes. These subjects are made accessible in the many concrete examples that illustrate techniques of calculation, and in the treatment of all topics from the ground up, starting from simple cases. Many of the examples and proofs

Overview

The second volume concentrates on stochastic integrals, stochastic differential equations, excursion theory and the general theory of processes. These subjects are made accessible in the many concrete examples that illustrate techniques of calculation, and in the treatment of all topics from the ground up, starting from simple cases. Many of the examples and proofs are new; some important calculational techniques appear for the first time in this book.

Product Details

ISBN-13:
9780521775939
Publisher:
Cambridge University Press
Publication date:
06/28/2014
Series:
Cambridge Mathematical Library Series
Edition description:
Revised Edition
Pages:
494
Product dimensions:
5.98(w) x 8.98(h) x 0.94(d)

Table of Contents

Some frequently used notation; 4. Introduction to Ito calculus; 4.1. Some motivating remarks; 4.2. Some fundamental ideas: previsible processes, localization, etc.; 4.3. The elementary theory of finite-variation processes; 4.4. Stochastic integrals: the L2 theory; 4.5. Stochastic integrals with respect to continuous semimartingales; 4.6. Applications of Ito's formula; 5. Stochastic differential equations and diffusions; 5.1. Introduction; 5.2. Pathwise uniqueness, strong SDEs, flows; 5.3. Weak solutions, uniqueness in law; 5.4. Martingale problems, Markov property; 5.5. Overture to stochastic differential geometry; 5.6. One-dimensional SDEs; 5.7. One-dimensional diffusions; 6. The general theory; 6.1. Orientation; 6.2. Debut and section theorems; 6.3. Optional projections and filtering; 6.4. Characterising previsible times; 6.5. Dual previsible projections; 6.6. The Meyer decomposition theorem; 6.7. Stochastic integration: the general case; 6.8. Ito excursion theory; References; Index.

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