Backward stochastic differential equations with constraints on the gains-process

Jakša Cvitanić, Ioannis Karatzas, H. Mete Soner

Research output: Contribution to journalArticlepeer-review

44 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1522-1551
Number of pages30
JournalAnnals of Probability
Issue number4
StatePublished - Oct 1998
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


  • Backward SDEs
  • Convex constraints
  • Stochastic control


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