Centralized systemic risk control in the interbank system: Weak formulation and Gamma-convergence

TL;DR

This paper develops a mathematical framework for central banks to optimally control systemic risk in interbank systems by employing weak formulations and Gamma-convergence, leading to a mean field control model.

Contribution

It introduces a novel weak formulation and Gamma-convergence approach for systemic risk control, connecting finite bank systems to mean field models.

Findings

Optimal randomized control for finite banks derived using Ekeland's principle

Proven convergence of strategies as the number of banks increases

Established uniqueness of the solution to the associated FPK equation

Abstract

This paper studies a systemic risk control problem by the central bank, which dynamically plans monetary supply to stabilize the interbank system with borrowing and lending activities. Facing both heterogeneity among banks and the common noise, the central bank aims to find an optimal strategy to minimize the average distance between log-monetary reserves of all banks and the benchmark of some target steady levels. A weak formulation is adopted, and an optimal randomized control can be obtained in the system with finite banks by applying Ekeland's variational principle. As the number of banks grows large, we prove the convergence of optimal strategies using the Gamma-convergence argument, which yields an optimal weak control in the mean field model. It is shown that this mean field optimal control is associated to the solution of a stochastic Fokker-Planck-Kolmogorov (FPK) equation, for which the uniqueness of the solution is established under some mild conditions.