Market Making and Incentives Design in the Presence of a Dark Pool: A Stackelberg Actor–Critic Approach

We consider the issue of a market maker acting at the same time in the lit and dark pools of an exchange. The exchange wishes to establish a suitable make–take fee policy to attract transactions on its venues. We first solve the stochastic control problem of the market maker without the intervention of the exchange. Then, we derive the equations defining the optimal contract to be set between the market maker and the exchange. This contract depends on the trading flows generated by the market maker’s activity on the two venues. In both cases, we show existence and uniqueness in the viscosity sense of the solutions of the Hamilton–Jacobi–Bellman equations associated to the market maker and exchange’s problems. We finally design an actor–critic algorithm inspired by deep reinforcement learning methods, enabling us to approximate efficiently the optimal controls of the market maker and the optimal incentives to be provided by the exchange.

Funding: This work benefits from the financial support of the Chaires Analytics and Models for Regulation; Financial Risk; Deep Finance, Statistics, Machine Learning and Systematic Methods in Finance; Finance and Sustainable Development. B. Baldacci and M. Rosenbaum gratefully acknowledge the financial support of the European Research Council [Grant 679836 Staqamof]. T. Mastrolia gratefully acknowledges the support of the Agence Nationale de la recherche projects PACMAN ANR-16-CE05-0027 and ReLISCoP ANR-21-CE40-0001.