BACKWARD SDES FOR OPTIMAL CONTROL OF PARTIALLY OBSERVED PATH-DEPENDENT STOCHASTIC SYSTEMS: A CONTROL RANDOMIZATION APPROACH

• 成果类型: Article
• 署名作者: Bandini, Elena; Cosso, Andrea; Fuhrman, Marco; Huyen Pham
• 署名单位: Luiss Guido Carli University; Polytechnic University of Milan; University of Milan; Universite Paris Cite; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Sorbonne Universite; Luiss Guido Carli University
• 刊物名称: ANNALS OF APPLIED PROBABILITY
• ISSN/ISSBN: 1050-5164
• DOI: 10.1214/17-AAP1340
• 发表日期: 2018
• 页码: 1634-1678
• 关键词: nonlinear hjb equations; differential-equations; nonpositive jumps; Bellman equations; REPRESENTATION; BSDEs; EXISTENCE

摘要

We introduce a suitable backward stochastic differential equation (BSDE) to represent the value of an optimal control problem with partial observation for a controlled stochastic equation driven by Brownian motion. Our model is general enough to include cases with latent factors in mathematical finance. By a standard reformulation based on the reference probability method, it also includes the classical model where the observation process is affected by a Brownian motion (even in presence of a correlated noise), a case where a BSDE representation of the value was not available so far. This approach based on BSDEs allows for greater generality beyond the Markovian case, in particular our model may include path-dependence in the coefficients (both with respect to the state and the control), and does not require any nondegeneracy condition on the controlled equation. We use a randomization method, previously adopted only for cases of full observation, and consisting in a first step, in replacing the control by an exogenous process independent of the driving noise and in formulating an auxiliary (randomized) control problem where optimization is performed over changes of equivalent probability measures affecting the characteristics of the exogenous process. Our first main result is to prove the equivalence between the original partially observed control problem and the randomized problem. In a second step, we prove that the latter can be associated by duality to a BSDE, which then characterizes the value of the original problem as well.