Brownian Motion, Martingales, and Stochastic Calculus

Authors: Le Gall, Jean-François
Provides a concise and rigorous presentation of stochastic integration and stochastic calculus for continuous semimartingales
Presents major applications of stochastic calculus to Brownian motion and related stochastic processes
Includes important aspects of Markov processes with applications to stochastic differential equations and to connections with partial differential equations

This book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales. The main tools of stochastic calculus, including Itô’s formula, the optional stopping theorem and Girsanov’s theorem, are treated in detail alongside many illustrative examples. The book also contains an introduction to Markov processes, with applications to solutions of stochastic differential equations and to connections between Brownian motion and partial differential equations. The theory of local times of semimartingales is discussed in the last chapter.
Since its invention by Itô, stochastic calculus has proven to be one of the most important techniques of modern probability theory, and has been used in the most recent theoretical advances as well as in applications to other fields such as mathematical finance. Brownian Motion, Martingales, and Stochastic Calculus provides a strong theoretical background to the reader interested in such developments.
Beginning graduate or advanced undergraduate students will benefit from this detailed approach to an essential area of probability theory. The emphasis is on concise and efficient presentation, without any concession to mathematical rigor. The material has been taught by the author for several years in graduate courses at two of the most prestigious French universities. The fact that proofs are given with full details makes the book particularly suitable for self-study. The numerous exercises help the reader to get acquainted with the tools of stochastic calculus.

Number of Illustrations and Tables
4 b/w illustrations, 1 illustrations in colour
Topics
Probability Theory and Stochastic Processes
Quantitative Finance
Measure and Integration
Mathematical Modeling and Industrial Mathematics
Systems Theory, Control

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