Backward Stochastic Differential Equations | From Linear to Fully Nonlinear Theory

Jianfeng Zhang

ISBN 10: 1493972545 / ISBN 13: 9781493972548

Editore: Springer US, 2017

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Backward Stochastic Differential Equations | From Linear to Fully Nonlinear Theory | Jianfeng Zhang | Buch | xvi | Englisch | 2017 | Springer US | EAN 9781493972548 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Codice articolo 109727995

Dati bibliografici

• Titolo: Backward Stochastic Differential Equations | From Linear to Fully Nonlinear Theory
• Editore: Springer US
• Data di pubblicazione: 2017
• Lingua: Inglese
• ISBN 10: 1493972545
• ISBN 13: 9781493972548
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 241 L x 160 A x 28 P (millimetri) 241 millimetri di larghezza per 160 millimetri di altezza per 28 millimetri di profondità
• Peso: 770 grammi
• Cataloghi dei venditori:
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Descrizione articolo

Riassunto

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.

Informazioni sull?autore

Jianfeng Zhang is a professor of Mathematics at the University of Southern California, Los Angeles.  His research interests include stochastic analysis, backward stochastic differential equations, stochastic numerics, and mathematical finance.