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020 _a9781493984329
040 _aNISER LIBRARY
_beng
_cNISER LIBRARY
082 0 4 _a519.21
_bZHA-B
100 1 _aZhang, Jianfeng
245 1 0 _aBackward stochastic differential equations :
_bfrom linear to fully nonlinear theory
260 _aNew York, NY :
_bSpringer,
_c2017.
300 _axv, 386 pages
490 0 _aProbability theory and stochastic modelling,
_x2199-3130 ;
_v86
520 _aThis 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.
588 _aDescription based on publisher-supplied MARC data.
650 0 _aEconomic theory.
650 0 _aEconomics, Mathematical.
650 0 _aGame theory.
650 0 _aNumerical analysis.
650 0 _aPartial differential equations.
650 0 _aProbabilities.
650 1 4 _aProbability theory and stochastic processes.
650 2 4 _aEconomic theory, quantitative economics, mathematical methods
650 2 4 _aGame theory, economics, social and behav. Sciences.
650 2 4 _aQuantitative finance.
650 2 4 _aStochastic differential equations
650 2 4 _aViscosity solutions
856 _3Table of content
_uhttps://link.springer.com/content/pdf/bfm:978-1-4939-7256-2/1
856 _3Reviews
_uhttps://www.goodreads.com/book/show/43972073-backward-stochastic-differential-equations?ref=nav_sb_ss_1_13#CommunityReviews
942 _2udc
_cBK
999 _c35698
_d35698