On the Well-posedness of Hamilton-Jacobi-Bellman Equations of the Equilibrium Type
Qian Lei, Chi Seng Pun

TL;DR
This paper establishes the well-posedness of a class of nonlocal Hamilton-Jacobi-Bellman equations related to time-inconsistent stochastic control, using advanced PDE techniques and providing probabilistic representations and financial applications.
Contribution
It introduces new methods to prove global and local well-posedness of nonlocal PDEs of equilibrium type with time and space nonlocality, including a probabilistic solution representation.
Findings
Proved global well-posedness using Schauder estimates and the method of continuity.
Established local well-posedness via linearization and fixed point arguments.
Provided a probabilistic representation of solutions and an example of a solvable financial time-inconsistency problem.
Abstract
This paper studies the well-posedness of a class of nonlocal parabolic partial differential equations (PDEs), or equivalently equilibrium Hamilton-Jacobi-Bellman equations, which has a strong tie with the characterization of the equilibrium strategies and the associated value functions for time-inconsistent stochastic control problems. Specifically, we consider nonlocality in both time and space, which allows for modelling of the stochastic control problems with initial-time-and-state dependent objective functionals. We leverage the method of continuity to show the global well-posedness within our proposed Banach space with our established Schauder prior estimate for the linearized nonlocal PDE. Then, we adopt a linearization method and Banach's fixed point arguments to show the local well-posedness of the nonlocal fully nonlinear case, while the global well-posedness is attainable…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
