Strategic Learning and Trading in Broker-Mediated Markets

ArXiv ID: 2412.20847 “View on arXiv”

Authors: Unknown

Abstract

We study strategic interactions in a broker-mediated market. A broker provides liquidity to an informed trader and to noise traders while managing inventory in the lit market. The broker and the informed trader maximise their trading performance while filtering each other’s private information; the trader estimates the broker’s trading activity in the lit market while the broker estimates the informed trader’s private signal. Brokers hold a strategic advantage over traders who rely solely on prices to filter information. We find that information leakage in the client’s trading flow yields an economic value to the broker that is comparable to transaction costs; she speculates profitably and mitigates risk effectively, which, in turn, adversely impacts the informed trader’s performance. In contrast, low signal-to-noise sources, such as prices, result in the broker’s trading performance being indistinguishable from that of a naive strategy that internalises noise flow, externalises informed flow, and offloads inventory at a constant rate.

Keywords: market microstructure, broker liquidity, strategic interaction, information asymmetry, adverse selection, equities

Complexity vs Empirical Score

  • Math Complexity: 9.0/10
  • Empirical Rigor: 2.0/10
  • Quadrant: Lab Rats
  • Why: The paper employs advanced stochastic control, filtering (Kalman-Bucy, Riccati equations), and game theory, indicating high mathematical complexity. However, it relies on theoretical models and simulations without mentioning real backtests or implementation details, showing low empirical rigor.
  flowchart TD
    A["Research Goal:<br>How do strategic interactions between<br>a broker and an informed trader affect<br>market outcomes and performance?"] --> B["Model & Methodology:<br>Dynamic Microstructure Model<br>Filtering & Inventory Control"]
    B --> C["Key Mechanisms:<br>1. Broker estimates trader's signal<br>2. Trader estimates broker's lit activity<br>3. Inventory risk & info leakage"]
    C --> D{"Computational Analysis:<br>Simulation & Equilibrium Solving"}
    D --> E["Performance Comparison<br>vs. Naive Strategy"]
    E --> F["Key Findings/Outcomes:<br>• Broker's info advantage creates value<br>• Profitable speculation & risk mitigation<br>• Adverse impact on informed trader<br>• Low signal-to-noise prices =<br>indistinguishable from naive strategy"]