The Maximum Principle in Time-Inconsistent LQ Optimal Control Problem for Jump Diffusions

TL;DR

This paper develops a stochastic maximum principle for a complex, time-inconsistent linear-quadratic control problem involving jump diffusions, providing a framework for constructing equilibrium controls in such settings.

Contribution

It introduces a novel maximum principle approach for time-inconsistent LQ problems with jumps, extending control theory to more general stochastic systems.

Findings

Constructed open-loop Nash equilibrium controls using stochastic maximum principle.

Extended control framework to systems with jump diffusions and non-exponential discounting.

Provided concrete examples demonstrating the application of the theoretical results.

Abstract

In this paper, we consider a general time-inconsistent optimal control problem for a non homogeneous linear system, in which its state evolves according to a stochastic differential equation with deterministic coefficients, when the noise is driven by a Brownian motion and an independent Poisson point process. The running and the terminal costs in the objective functional, are explicitly dependent on some general discounting coefficients which cover the non-exponential and the hyperbolic discounting situations. Furthermore, the presence of some quadratic terms of the conditional expectation of the state process as well as a state-dependent term in the objective functional makes the problem time-inconsistent. Open-loop Nash equilibrium controls are constructed instead of optimal controls, by using a version of the stochastic maximum principle approach. This approach involves a stochastic system that consists of a flow of forward-backward stochastic differential equations and an equilibrium condition. As an application, we study some concrete examples.