Backward stochastic differential equations : from linear to fully nonlinear theory /

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Bibliographic Details
Author / Creator:Zhang, Jianfeng (Mathematician), author.
Imprint:New York, NY : Springer, 2017.
Description:1 online resource (xvi, 388 pages)
Language:English
Series:Probability theory and stochastic modelling, 2199-3130 ; volume 86
Probability theory and stochastic modelling ; v. 86.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11350107
Hidden Bibliographic Details
ISBN:9781493972562
1493972561
9781493972555
1493972553
9781493984329
1493984322
9781493972548
1493972545
Digital file characteristics:text file
PDF
Notes:Includes bibliographical references and index.
Online resource; title from PDF title page (SpringerLink, viewed August 31, 2017).
Summary:This book provides a systematic and accessible approach to stochastic differential equations, backward stochastic differential equations, and their connection with partial differential equations, as well as the recent development of the fully nonlinear theory, including nonlinear expectation, second order backward stochastic differential equations, and path dependent partial differential equations. Their main applications and numerical algorithms, as well as many exercises, are included. The book focuses on ideas and clarity, with most results having been solved from scratch and most theories being motivated from applications. It can be considered a starting point for junior researchers in the field, and can serve as a textbook for a two-semester graduate course in probability theory and stochastic analysis. It is also accessible for graduate students majoring in financial engineering.
Other form:Print version: Zhang, Jianfeng (Mathematician). Backward stochastic differential equations. New York, NY : Springer, 2017 1493972545 9781493972548
Standard no.:10.1007/978-1-4939-7256-2