A maximum principle for optimal control problem of fully coupled forward-backward stochastic systems with partial information

QingXin Meng*

*Corresponding author for this work

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

The paper is concerned with a stochastic optimal control problem in which the controlled system is described by a fully coupled nonlinear forward-backward stochastic differential equation driven by a Brownian motion. It is required that all admissible control processes are adapted to a given subfiltration of the filtration generated by the underlying Brownian motion. For this type of partial information control, one sufficient (a verification theorem) and one necessary conditions of optimality are proved. The control domain need to be convex and the forward diffusion coefficient of the system can contain the control variable.

Original languageEnglish
Pages (from-to)1579-1588
Number of pages10
JournalScience in China, Series A: Mathematics
Volume52
Issue number7
DOIs
Publication statusPublished - Jul 2009

Keywords

  • Maximum principle
  • Partial information
  • Stochastic optimal control

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