9781470410544-1470410540-An Introduction to Stochastic Differential Equations

An Introduction to Stochastic Differential Equations

ISBN-13: 9781470410544
ISBN-10: 1470410540
Author: Lawrence C. Evans
Publication date: 2014
Publisher: American Mathematical Society
Format: Paperback 151 pages
Category: Mathematics
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Book details

ISBN-13: 9781470410544
ISBN-10: 1470410540
Author: Lawrence C. Evans
Publication date: 2014
Publisher: American Mathematical Society
Format: Paperback 151 pages
Category: Mathematics

Summary

An Introduction to Stochastic Differential Equations (ISBN-13: 9781470410544 and ISBN-10: 1470410540), written by authors Lawrence C. Evans, was published by American Mathematical Society in 2014. With an overall rating of 3.5 stars, it's a notable title among other Mathematics books. You can easily purchase or rent An Introduction to Stochastic Differential Equations (Paperback) from BooksRun, along with many other new and used Mathematics books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $19.28.

Description

This short book provides a quick, but very readable introduction to stochastic differential equations, that is, to differential equations subject to additive "white noise" and related random disturbances. The exposition is concise and strongly focused upon the interplay between probabilistic intuition and mathematical rigor. Topics include a quick survey of measure theoretic probability theory, followed by an introduction to Brownian motion and the Itô stochastic calculus, and finally the theory of stochastic differential equations. The text also includes applications to partial differential equations, optimal stopping problems and options pricing. This book can be used as a text for senior undergraduates or beginning graduate students in mathematics, applied mathematics, physics, financial mathematics, etc., who want to learn the basics of stochastic differential equations. The reader is assumed to be fairly familiar with measure theoretic mathematical analysis, but is not assumed to have any particular knowledge of probability theory (which is rapidly developed in Chapter 2 of the book).

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