Backward stochastic differential equations with constraints on the gains-process

Open Access

1 October 1998

journal article
Published by Institute of Mathematical Statistics in The Annals of Probability

Vol. 26 (4) , 1522-1551
https://doi.org/10.1214/aop/1022855872

Abstract

We consider backward stochastic differential equations with convex constraints on the gains (or intensity-of-noise) process. Existence and uniqueness of a minimal solution are established in the case of a drift coefficient which is Lipschitz continuous in the state and gains processes and convex in the gains process. It is also shown that the minimal solution can be characterized as the unique solution of a functional stochastic control-type equation. This representation is related to the penalization method for constructing solutions of stochastic differential equations, involves change of measure techniques, and employs notions and results from convex analysis, such as the support function of the convex set of constraints and its various properties.

Keywords

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