Optimal Controls of Stochastic Differential Equations with Jumps and Random Coefficients: Stochastic Hamilton-Jacobi-Bellman Equations with Jumps

被引:3
|
作者
Meng, Qingxin [1 ]
Dong, Yuchao [2 ]
Shen, Yang [3 ,4 ]
Tang, Shanjian [5 ]
机构
[1] Huzhou Univ, Dept Math Sci, Huzhou 313000, Zhejiang, Peoples R China
[2] Tongji Univ, Sch Math Sci, Shanghai 200092, Peoples R China
[3] Univ New South Wales Sydney, Sch Risk & Actuarial Studies, Sydney, NSW 2052, Australia
[4] Univ New South Wales Sydney, CEPAR, Sydney, NSW 2052, Australia
[5] Fudan Univ, Sch Math Sci, Dept Finance & Control Sci, Shanghai 200433, Peoples R China
来源
APPLIED MATHEMATICS AND OPTIMIZATION | 2023年 / 87卷 / 01期
基金
美国国家科学基金会; 中国国家自然科学基金; 澳大利亚研究理事会; 国家重点研发计划;
关键词
Stochastic control; Dynamic programming; Stochastic HJB equation; Stochastic partial integral differential equation; ADAPTED SOLUTION; VISCOSITY SOLUTIONS; MAXIMUM PRINCIPLE; ASSET RETURNS; SYSTEMS; RISK;
D O I
10.1007/s00245-022-09914-8
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We study the stochastic Hamilton-Jacobi-Bellman (HJB) equation with jump, which arises from a non-Markovian optimal control problem with a recursive utility cost functional. The solution to the equation is a predictable triplet of random fields. We show that the value function of the control problem, under some regularity assumptions, is the solution to the stochastic HJB equation; and a classical solution to this equation is the value function and characterizes the optimal control. With some additional assumptions on the coefficients, an existence and uniqueness result in the sense of Sobolev space is shown by recasting the stochastic HJB equation as a backward stochastic evolution equation in Hilbert spaces with the Brownian motion and Poisson jump.
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页数:51
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