Backward Stochastic Differential Equations

From Linear to Fully Nonlinear Theory

Nonfiction, Science & Nature, Mathematics, Applied, Statistics
Cover of the book Backward Stochastic Differential Equations by Jianfeng Zhang, Springer New York
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Author: Jianfeng Zhang ISBN: 9781493972562
Publisher: Springer New York Publication: August 22, 2017
Imprint: Springer Language: English
Author: Jianfeng Zhang
ISBN: 9781493972562
Publisher: Springer New York
Publication: August 22, 2017
Imprint: Springer
Language: English

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.

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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.

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