4 edition of **Backward stochastic differential equations** found in the catalog.

Backward stochastic differential equations

- 267 Want to read
- 29 Currently reading

Published
**1997** by Longman in Harlow .

Written in English

- Stochastic differential equations.

**Edition Notes**

Includes bibliographies.

Statement | Nicole El Karoui and Laurent Mazliak (editors). |

Series | Pitman research notes in mathematics series -- 364. |

Contributions | El Karoui, Nicole., Mazliak, Laurent. |

The Physical Object | |
---|---|

Pagination | 221 p. ; |

Number of Pages | 221 |

ID Numbers | |

Open Library | OL18118117M |

ISBN 10 | 0582307333 |

LC Control Number | 97009748 |

Stochastic Controls Hamiltonian Systems and HJB Equations. Authors: Yong, Jiongmin, Zhou, Xun Yu Free Preview. Buy this book eB59 € price for Spain (gross) Buy eBook ISBN ; Digitally watermarked, DRM-free; Included format: PDF; ebooks can be used on all reading devices. 2 days ago In this paper, we generalize to Gaussian Volterra processes the existence and uniqueness of solutions for a class of non linear backward stochastic differential equations (BSDE) and we establish the relation between the non linear BSDE and the partial differential equation (PDE). A comparison theorem for the solution of the BSDE is proved and the continuity of its law is studied. In this paper we are concerned with the maximum principle for quasi-linear backward stochastic partial differential equations (BSPDEs for short) of parabolic type. We first prove the existence and uniqueness of the weak solution to quasi-linear BSPDEs with the null Dirichlet condition on the lateral boundary. Downloadable (with restrictions)! We consider the optimal stopping problem with non-linear f-expectation (induced by a BSDE) without making any regularity assumptions on the payoff process ξ and in the case of a general filtration. We show that the value family can be aggregated by an optional process Y. We characterize the process Y as the Ef-Snell envelope of ξ.

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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 by: Backward stochastic differential equations book Stochastic Differential Equations: From Linear to Fully Nonlinear Theory (Probability Theory and Stochastic Modelling Book 86) - Kindle edition by Zhang, Jianfeng.

Download it once and read it on your Kindle device, PC, phones or tablets.5/5(1). The book deals with forward-backward stochastic differential equations, exactly what the title suggests.

The prerequisites in stochastic processes Backward stochastic differential equations book modest, knowledge at the level of Oksendal's Stochastic differential Eqiuations is more than by: Backward stochastic differential equations (BSDEs) provide a general mathematical framework for solving pricing and risk management questions of financial Backward stochastic differential equations book.

They are of growing importance for nonlinear pricing problems such as CVA computations that have been developed since the crisis.5/5(1). 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 : Springer-Verlag New York.

Forward-Backward Stochastic Differential Equations and their Applications (Lecture Notes in Mathematics Book ) - Kindle edition by Ma, Jin, Yong, Jiongmin. Download it once and read it on your Kindle device, PC, phones or tablets.4/5(2). This book provides a systematic and accessible approach to stochastic differential equations, backward stochastic differential equations, and their connection with partial differential equations.

Description: Backward stochastic differential equations with jumps can be used to Backward stochastic differential equations book problems in both finance and insurance. Part I of this book presents the theory of BSDEs with Lipschitz generators driven by a Brownian Backward stochastic differential equations book and a compensated random measure, with an emphasis on those generated by step processes and Lévy processes.

The theory of backward stochastic diﬀerential equations (BSDEs Backward stochastic differential equations book short) and nonlinear expectation has gone through rapid development in so many dif- ferent areas of research and applications, such as probability and statistics, partial diﬀerential equations (PDE), functional analysis, numerical analysisFile Size: KB.

Backward stochastic diﬀeren tial equations (in short BSDE’s) were ﬁrst introduced by ut in [7] as equation for the adjoint process in the stochastic version of Pon tryagin.

Backward Stochastic Differential Equations By N El Karoui, Laurent Mazliak. Hardback $ This product is currently out of stock. This book presents the texts of seminars presented during the years and at the Université Paris VI and is the first attempt to present a survey on this subject.

Starting from the classical. Member of the Institut Universitaire de France, Pardoux has Backward stochastic differential equations book more than papers on nonlinear filtering, stochastic partial differential equations, anticipating stochastic calculus, backward stochastic differential equations, homogenization and probabilistic models in evolutionary biology, and three books.

Backward Stochastic Differential Equations - CRC Press Book This book presents the texts of seminars presented during the years and at the Université Paris VI and is the first attempt to present a survey on this subject. 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.

A stochastic differential equation (SDE) is a differential equation in which one or more of the terms is a stochastic process, resulting in a solution which is also a stochastic are used to model various phenomena such as unstable stock prices or physical systems subject to thermal lly, SDEs contain a variable which represents random white noise calculated as.

In: Backward Stochastic Differential Equations (Paris, –). Pitman Research Notes in Mathematics Series, vol.pp. – Longman, Harlow () Google ScholarCited by: Stochastic Differential Equations, Backward SDEs, Partial Differential Equations (Stochastic Modelling and Applied Probability Book 69) - Kindle edition by Pardoux, Etienne, Rӑşcanu, Aurel.

Download it once and read it on your Kindle device, PC, phones or tablets. Use features like bookmarks, note taking and highlighting while reading Stochastic Differential Equations, Backward SDEs, Price: $ Backward stochastic differential equations (BSDEs) provide a general mathematical framework for solving pricing and risk management questions of financial derivatives.

They are of growing importance for nonlinear pricing problems such as CVA computations that have been developed since the : Springer-Verlag Berlin Heidelberg. Backward stochastic differential equations (BSDEs) in the sense of Pardoux-Peng [Backward stochastic differential equations and quasilinear parabolic partial differential equations.

From the book reviews: “The book presents a self-contained overview of the modern state of the theory of backward stochastic differential equations (BSDEs) for jump-diffusion random processes and aims to show applications of the theory to financial and actuarial problems.

useful to both students and researchers in applied probability dealing with actuarial and financial problems.” (Ya Brand: Springer-Verlag London. Stochastic calculus and stochastic differential equations (SDEs) were first introduced by K.

Itô in the s, in order to construct the path of diffusion processes (which are continuous time Markov processes with continuous trajectories taking their values in a finite dimensional vector space or manifold), which had been studied from a more.

BackwardStochasticDiﬀerentialEquations: an Introduction Nicolas Perkowski Abstract This is a short introduction to the theory of Backward Stochastic Diﬀer.

In this paper, we study the solution of coupled forward-backward stochastic differential equation driven by G-Brownian motion with monotone s, we prove that the solution is Author: Bingjun Wang, Mingxia Yuan.

Pardoux, S. Peng, Backward stochastic differential equations and quasilinear parabolic partial differential equations, in Stochastic Partial Differential Equations and Their Applications.

Lecture Notes in Control and Information Sciences, vol. (Springer, Berlin, ), pp. – Google ScholarAuthor: Samuel N. Cohen, Robert J. Elliott, Robert J. Elliott. Backward stochastic differential equations with jumps can be used to solve problems in both finance and insurance.

Part I of this book presents the theory of BSDEs with Lipschitz generators driven by a Brownian motion and a compensated random measure, with an emphasis on those generated by step processes and Lévy processes. Buy Backward Stochastic Differential Equations: From Linear to Fully Nonlinear Theory (Probability Theory and Stochastic Modelling) 1st ed.

by Zhang, Jianfeng (ISBN: ) from Amazon's Book Store. Everyday low prices and free delivery on eligible : Jianfeng Zhang. This volume is a survey/monograph on the recently developed theory of forward-backward stochastic differential equations (FBSDEs).

Basic techniques such as the method of optimal control, the 'Four Step Scheme', and the method of continuation are presented in full. Related topics such as backward.

REPRESENTATION THEOREMS FOR BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS BY JIN MA1 AND JIANFENG ZHANG Purdue University and University of Minnesota In this paper we investigate a class of backward stochastic differential equations (BSDE)whose terminal values are allowed to depend on the history of a forward Size: KB.

NUMERICAL METHOD FOR BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS BY JIN MA,1 PHILIP PROTTER,2 JAIME SAN MARTÍN AND SOLEDAD TORRES3 Purdue University, Cornell University, Universidad de Chile and Universidad de Valparaíso We propose a method for numerical approximation of backward stochas-tic differential equations.

More precisely, Chaps. 12 to 14 develop, within a rigorous mathematical framework, the connection between backward stochastic differential equations and partial differential equations.

This is done in a jump-diffusion setting with regime switching, which covers all the models considered in the by: 1. Presenting seminars given in and at the University of Paris VI, this text surveys the subject of backward stochastic differential equations.

It may be read as an introduction to the topic as well as a reference to more recent developments of the theory. Backward Stochastic Differential Equations by Nicole El Karoui,available at Book Depository with free delivery worldwide.

backward stochastic differential equations (BSDE) may be reformulated as ordinary functional equations on certain path spaces.

In this dissertation, we use the new approach to study the following general type of backward stochastic differential equations with, on a general filtered probability space, wher is a prescribedFile Size: KB.

In this paper, we are interested in solving backward stochastic differential equations (BSDEs for short) under weak assumptions on the data.

The first part of the paper is devoted to the development of some new technical aspects of stochastic calculus related to by: The Kolmogorov backward equation (KBE) (diffusion) and its adjoint sometimes known as the Kolmogorov forward equation (diffusion) are partial differential equations (PDE) that arise in the theory of continuous-time continuous-state Markov were published by Andrey Kolmogorov in Later it was realized that the forward equation was already known to physicists under the name.

Problem 6 is a stochastic version of F.P. Ramsey’s classical control problem from In Chapter X we formulate the general stochastic control prob-lem in terms of stochastic diﬁerential equations, and we apply the results of Chapters VII and VIII to show that the problem can be reduced to solvingFile Size: 1MB.

We study linear-quadratic stochastic optimal control problems with bilinear state dependence where the underlying stochastic differential equation (SDE) has multiscale features. We show that, in the same way in which the underlying dynamics can be well approximated by a reduced-order dynamics in the scale separation limit (using classical homogenization results), the associated optimal Author: Omar Kebiri, Lara Neureither, Carsten Hartmann.

On the other hand, in Bellman's dynamic programming, there is a partial differential equation (PDE), of first order in the (finite-dimensional) deterministic case and of second or der in the stochastic case.

This is known as a Hamilton-Jacobi-Bellman (HJB) equation. Backward stochastic differential equations (BSDEs) provide a general mathematical framework for solving pricing and risk management questions of financial derivatives.

They are of growing importance for nonlinear pricing problems such as CVA computations that have been developed since the : Stephane Crepey. The differential equations we consider in most of the book are of the form Y′(t) = f(t,Y(t)), where Y(t) is an unknown function that is being sought.

The given function f(t,y) of two variables deﬁnes the differential equation, and exam ples are given in Chapter 1. This equation is called a ﬁrst-order differential equation because it File Size: 1MB. Get this from a library! Pdf Stochastic Differential Equations and their Applications.

[Jin Ma; Jiongmin Yong] -- This volume is a survey/monograph on the recently developed theory of forward-backward stochastic differential equations (FBSDEs). Basic techniques such as the method of optimal control, the "Four.In the book "Stochastic Differential Equations" by Bernt Øksendal, the Kolmogorov's backward equation is stated as following: Besides, it seems that the definition of Kolmogorov's backward equation is in another form on Wiki: Kolmogorov backward equations (diffusion).

stochastic .Get ebook from a library! Financial modeling: a backward stochastic differential equations perspective. [Stéphane Crépey] -- Backward stochastic differential equations (BSDEs) provide a general mathematical framework for solving pricing and risk management questions of financial derivatives.

They are of growing importance.