Solvability of Equilibrium Riccati Equations: A Direct Approach

TL;DR

This paper introduces a new, direct method for solving equilibrium Riccati equations in stochastic control, avoiding the traditional dynamic programming approach, and provides both theoretical and numerical insights into their solvability.

Contribution

It offers a novel, control-theory-independent proof of ERE solvability using a priori estimates and Picard iteration, applicable to smooth and non-smooth coefficients.

Findings

Established a priori estimates for ERE with smooth coefficients

Proved local and global solvability of ERE via Picard iteration

Developed a numerical algorithm for solving EREs

Abstract

The solvability of equilibrium Riccati equations (EREs) plays a central role in the study of time-inconsistent stochastic linear-quadratic optimal control problems, because it paves the way to constructing a closed-loop equilibrium strategy. Under the standard conditions, Yong [29] established its well-posedness by introducing the well-known multi-person differential game method. However, this method depends on the dynamic programming principle (DPP) of the sophisticated problems on every subinterval, and thus is essentially a control theory approach. In this paper, we shall give a new and more direct proof, in which the DPP is no longer needed. We first establish a priori estimates for the ERE in the case of smooth coefficients. Using this estimate, we then demonstrate both the local and global solvability of the ERE by constructing an appropriate Picard iteration sequence, which actually provides a numerical algorithm. Additionally, a mollification method is employed to handle the case with non-smooth coefficients.