Backward Stochastic Differential Equations

Jianfeng Zhang

ISBN 10: 1493984322 / ISBN 13: 9781493984329

Editore: Springer New York, Springer US Aug 2018, 2018

Riguardo questo articolo

Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 404 pp. Englisch.

Codice articolo 9781493984329

Dati bibliografici

• Titolo: Backward Stochastic Differential Equations
• Editore: Springer New York, Springer US Aug 2018
• Data di pubblicazione: 2018
• Lingua: Inglese
• ISBN 10: 1493984322
• ISBN 13: 9781493984329
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 22 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 22 millimetri di profondità
• Peso: 610 grammi

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.