Optimal control problem of fully coupled forward-backward stochastic systems with Poisson jumps under partial information

Qingxin Meng*, Yongzheng Sun

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

4 Citations (Scopus)

Abstract

In this paper, we study a class of stochastic optimal control problem with jumps under partial information. More precisely, the controlled systems are described by a fully coupled nonlinear multi- dimensional forward-backward stochastic differential equation driven by a Poisson random measure and an independent multi-dimensional Brownian motion, and all admissible control processes are required to be adapted to a given subfiltration of the filtration generated by the underlying Poisson random measure and Brownian motion. For this type of partial information stochastic optimal control problem, we give a necessary and sufficient maximum principle. All the coefficients appearing in the systems are allowed to depend on the control variables and the control domain is convex.

Original languageEnglish
Title of host publicationProceedings of the 30th Chinese Control Conference, CCC 2011
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1317-1322
Number of pages6
ISBN (Electronic)9789881725592
ISBN (Print)9781457706776
Publication statusPublished - 2011
Event30th Chinese Control Conference, CCC 2011 - Yantai, China
Duration: 22 Jul 201124 Jul 2011

Other

Other30th Chinese Control Conference, CCC 2011
CountryChina
CityYantai
Period22/07/1124/07/11

Keywords

  • Backward stochastic differential equation
  • Maximum principle
  • Partial information
  • Poisson process
  • Stochastic optimal control

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