Control-stopping Games for Market Microstructure and Beyond

TL;DR

This paper introduces a new class of control-stopping games modeling market microstructure, where agents deduce asset values from others' posted prices, leading to complex coupled systems with discrete controls and multiple mathematical challenges.

Contribution

It develops a novel framework for control-stopping games with discrete controls and no exogenous asset value, connecting to coupled RBSDEs and providing existence results and numerical insights.

Findings

Existence of solutions in a Markovian setting.

Numerical examples illustrating the model.

Discussion of potential applications in market microstructure.

Abstract

In this paper, we present a family of a control-stopping games which arise naturally in equilibrium-based models of market microstructure, as well as in other models with strategic buyers and sellers. A distinctive feature of this family of games is the fact that the agents do not have any exogenously given fundamental value for the asset, and they deduce the value of their position from the bid and ask prices posted by other agents (i.e. they are pure speculators). As a result, in such a game, the reward function of each agent, at the time of stopping, depends directly on the controls of other players. The equilibrium problem leads naturally to a system of coupled control-stopping problems (or, equivalently, Reflected Backward Stochastic Differential Equations (RBSDEs)), in which the individual reward functions (or, reflecting barriers) depend on the value functions (or, solution components) of other agents. The resulting system, in general, presents multiple mathematical challenges due to the non-standard form of coupling (or, reflection). In the present case, this system is also complicated by the fact that the continuous controls of the agents, describing their posted bid and ask prices, are constrained to take values in a discrete grid. The latter feature reflects the presence of a positive tick size in the market, and it creates additional discontinuities in the agents reward functions (or, reflecting barriers). Herein, we prove the existence of a solution to the associated system in a special Markovian framework, provide numerical examples, and discuss the potential applications.