國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Backward stochastic differential equ...

SpringerLink (Online service)

Backward stochastic differential equationsfrom linear to fully nonlinear theory /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Backward stochastic differential equationsby Jianfeng Zhang.
其他題名:	from linear to fully nonlinear theory /
作者:	Zhang, Jianfeng.
出版者:	New York, NY :Springer New York :2017.
面頁冊數:	xvi, 388 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Stochastic differential equations.
電子資源:	http://dx.doi.org/10.1007/978-1-4939-7256-2
ISBN:	9781493972562$q(electronic bk.)

Backward stochastic differential equationsfrom linear to fully nonlinear theory /
Zhang, Jianfeng.

Backward stochastic differential equationsfrom linear to fully nonlinear theory /[electronic resource] :by Jianfeng Zhang. - New York, NY :Springer New York :2017. - xvi, 388 p. :ill., digital ;24 cm. - Probability theory and stochastic modelling,v.862199-3130 ;. - Probability theory and stochastic modelling ;v.70..

Preliminaries -- Part I The Basic Theory of SDEs and BSDEs -- Basics of Stochastic Calculus -- Stochastic Differential Equations -- Backward Stochastic Differential Equations -- Markov BSDEs and PDEs -- Part II Further Theory of BSDEs -- Reflected BSDEs -- BSDEs with Quadratic Growth in Z -- Forward Backward SDEs -- Part III The Fully Nonlinear Theory of BSDEs -- Stochastic Calculus Under Weak Formulation -- Nonlinear Expectation -- Path Dependent PDEs -- Second Order BSDEs. Bibliography -- Index.

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.

ISBN: 9781493972562$q(electronic bk.)

Standard No.: 10.1007/978-1-4939-7256-2doiSubjects--Topical Terms:

185784
Stochastic differential equations.

LC Class. No.: QA274.23

Dewey Class. No.: 519.22

Backward stochastic differential equationsfrom linear to fully nonlinear theory /
LDR:02482nmm a2200337 a 4500 001 521339
003 DE-He213
005 20180319155916.0
006 m d
007 cr nn 008maaau
008 180504s2017 nyu s 0 eng d
020 $a 9781493972562$q(electronic bk.)
020 $a 9781493972548$q(paper)
024 7 $a 10.1007/978-1-4939-7256-2 $2 doi
035 $a 978-1-4939-7256-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA274.23
072 7 $a PBT $2 bicssc
072 7 $a PBWL $2 bicssc
072 7 $a MAT029000 $2 bisacsh
082 0 4 $a 519.22 $2 23
090 $a QA274.23 $b .Z63 2017
100 1 $a Zhang, Jianfeng. $3 677870
245 1 0 $a Backward stochastic differential equations $h [electronic resource] : $b from linear to fully nonlinear theory / $c by Jianfeng Zhang.
260 $a New York, NY : $b Springer New York : $b Imprint: Springer, $c 2017.
300 $a xvi, 388 p. : $b ill., digital ; $c 24 cm.
490 1 $a Probability theory and stochastic modelling, $x 2199-3130 ; $v v.86
505 0 $a Preliminaries -- Part I The Basic Theory of SDEs and BSDEs -- Basics of Stochastic Calculus -- Stochastic Differential Equations -- Backward Stochastic Differential Equations -- Markov BSDEs and PDEs -- Part II Further Theory of BSDEs -- Reflected BSDEs -- BSDEs with Quadratic Growth in Z -- Forward Backward SDEs -- Part III The Fully Nonlinear Theory of BSDEs -- Stochastic Calculus Under Weak Formulation -- Nonlinear Expectation -- Path Dependent PDEs -- Second Order BSDEs. Bibliography -- Index.
520 $a 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.
650 0 $a Stochastic differential equations. $3 185784
650 1 4 $a Mathematics. $3 184409
650 2 4 $a Probability Theory and Stochastic Processes. $3 274061
650 2 4 $a Quantitative Finance. $3 274071
650 2 4 $a Game Theory, Economics, Social and Behav. Sciences. $3 274083
650 2 4 $a Partial Differential Equations. $3 274075
650 2 4 $a Numerical Analysis. $3 275681
650 2 4 $a Economic Theory/Quantitative Economics/Mathematical Methods. $3 731081
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Probability theory and stochastic modelling ; $v v.70. $3 683306
856 4 0 $u http://dx.doi.org/10.1007/978-1-4939-7256-2
950 $a Mathematics and Statistics (Springer-11649)