English

Viscosity Solutions of Stochastic Hamilton--Jacobi--Bellman Equations with Jumps

Optimization and Control 2026-05-21 v1 Probability

Abstract

This paper studies the stochastic optimal control of jump-diffusion processes and the associated fully nonlinear backward stochastic Hamilton--Jacobi--Bellman (BSHJB) equations. We establish the dynamic programming principle (DPP) via backward semigroups to characterize the value function. To handle non-local integro-differential operators and polynomial growth, we introduce a stochastic viscosity solution framework based on semimartingale test functions and global tangency conditions. Existence is proved using the measurable selection theorem and the generalized It\^o--Kunita formula. Finally, under a super-parabolicity condition, we establish a weak comparison principle and prove global uniqueness via localized bounding envelopes and backward induction.

Keywords

Cite

@article{arxiv.2605.20593,
  title  = {Viscosity Solutions of Stochastic Hamilton--Jacobi--Bellman Equations with Jumps},
  author = {Dunxiang Liang and Qingxin Meng},
  journal= {arXiv preprint arXiv:2605.20593},
  year   = {2026}
}