Stochastic Differential Equations, Backward SDEs, Partial Differential Equations Stochastic Differential Equations, Backward SDEs, Partial Differential Equations

Stochastic Differential Equations, Backward SDEs, Partial Differential Equations

    • $119.99
    • $119.99

Publisher Description

This research monograph presents results to researchers in stochastic calculus, forward and backward stochastic differential equations, connections between diffusion processes and second order partial differential equations (PDEs), and financial mathematics. It pays special attention to the relations between SDEs/BSDEs and second order PDEs under minimal regularity assumptions, and also extends those results to equations with multivalued coefficients. The authors present in particular the theory of reflected SDEs in the above mentioned framework and include exercises at the end of each chapter.

Stochastic calculus and stochastic differential equations (SDEs) were first introduced by K. Itô in the 1940s, 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 analytic point of view by Kolmogorov in the 1930s. Since then, this topic has become an important subject of Mathematics and Applied Mathematics, because of its mathematical richness and its importance for applications in many areas of Physics, Biology, Economics and Finance, where random processes play an increasingly important role. One important aspect is the connection between diffusion processes and linear partial differential equations of second order, which is in particular the basis for Monte Carlo numerical methods for linear PDEs. Since the pioneering work of Peng and Pardoux in the early 1990s, a new type of SDEs called backward stochastic differential equations (BSDEs) has emerged. The two main reasons why this new class of equations is important are the connection between BSDEs and semilinear PDEs, and the fact that BSDEs constitute a natural generalization of the famous Black and Scholes model from Mathematical Finance, and thus offer a natural mathematical framework for the formulation of many new models in Finance.

GENRE
Science & Nature
RELEASED
2014
June 24
LANGUAGE
EN
English
LENGTH
684
Pages
PUBLISHER
Springer International Publishing
SELLER
Springer Nature B.V.
SIZE
19.3
MB

More Books Like This

Backward Stochastic Differential Equations Backward Stochastic Differential Equations
2017
Stochastic Partial Differential Equations: An Introduction Stochastic Partial Differential Equations: An Introduction
2015
Direct Methods in the Theory of Elliptic Equations Direct Methods in the Theory of Elliptic Equations
2011
Harnack Inequalities for Stochastic Partial Differential Equations Harnack Inequalities for Stochastic Partial Differential Equations
2013
Stochastic Control Theory Stochastic Control Theory
2014
Infinite Dimensional Dynamical Systems Infinite Dimensional Dynamical Systems
2012

More Books by Etienne Pardoux & Aurel Rӑşcanu