The Impact of Market Informedness on Market Makers' Profitability

This paper examines the impact of market informedness on the profitability of market makers. In contrast to the existing literature, the analysis is conducted in a complex market environment featuring heterogeneous market-making agents that differ in terms of information sets and aversion to inventory risk, endogenous price formation, exogenous fundamental value dynamics, and self-exciting market order flow. The paper also establishes finite-horizon stability guarantees for the resulting state-dependent Hawkes market-taker process, including non-explosion, exponential mispricing integrability, occupation-time bounds, and a pathwise mispricing tail estimate. To address the market-making problem, the study employs a reinforcement learning framework based on the multi-agent proximal policy optimization (MAPPO) algorithm in a centralized training with decentralized execution (CTDE) setting. The study shows that informed market order flow is particularly dangerous in poorly informed markets, leading to severe adverse-selection risk. Although the complex market dynamics together with stochastic training give rise to locally non-monotonic outcomes, the results nevertheless reveal an overall upward trend in market makers' profitability as market informedness increases, suggesting that price discovery resulting from higher market informedness offsets the negative impact of adverse selection.