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Jianfeng Zhang
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Backward Stochastic Differential Equations (Probability Theory and Stochastic Modelling, 86) 1st ed. 2017 Edition

by Zhang (Author)
4.4 4.4 out of 5 stars 4 ratings
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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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  1. ISBN-10
    1493972545
  2. ISBN-13
    978-1493972548
  3. Edition
    1st ed. 2017
  4. Publisher
    Springer
  5. Publication date
    August 22, 2017
  6. Part of series
    Probability Theory and Stochastic Modelling
  7. Language
    English
  8. Dimensions
    6.14 x 1.1 x 9.21 inches
  9. Print length
    404 pages
  10. See all details
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Editorial Reviews

Review

“This book (written by one of the leading experts in the field) constitutes a very handy and self-contained resource on BSDEs, both for people who want to get acquainted with the theory of BSDEs and Ph.D. students who aim to work in this field. … Overall the book is very well written and pleasant to read, and will likely become a classical reference on the topic.” (Anthony Réveillac, Mathematical Reviews, December, 2018)

“The book prefers clarity over generality in order to be more accessible and readable for the readers who are expected to be mainly Ph.D. students and junior researches in stochastic analysis.” (Martin Ondreját, zbMATH 1390.60004, 2018)

From the Back Cover

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.

Product details

  • Publisher ‏ : ‎ Springer; 1st ed. 2017 edition (August 22, 2017)
  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 404 pages
  • ISBN-10 ‏ : ‎ 1493972545
  • ISBN-13 ‏ : ‎ 978-1493972548
  • Item Weight ‏ : ‎ 1.34 pounds
  • Dimensions ‏ : ‎ 6.14 x 1.1 x 9.21 inches
  • Customer Reviews:
    4.4 4.4 out of 5 stars 4 ratings

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Jianfeng Zhang

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