Performative Market Making

ArXiv ID: 2508.04344 “View on arXiv”

Authors: Charalampos Kleitsikas, Stefanos Leonardos, Carmine Ventre

Abstract

Financial models do not merely analyse markets, but actively shape them. This effect, known as performativity, describes how financial theories and the subsequent actions based on them influence market processes, by creating self-fulfilling prophecies. Although discussed in the literature on economic sociology, this deeply rooted phenomenon lacks mathematical formulation in financial markets. Our paper closes this gap by breaking down the canonical separation of diffusion processes between the description of the market environment and the financial model. We do that by embedding the model in the process itself, creating a closed feedback loop, and demonstrate how prices change towards greater conformity to the prevailing financial model used in the market. We further show, with closed-form solutions and machine learning, how a performative market maker can reverse engineer the current dominant strategies in the market and effectively arbitrage them while maintaining competitive quotes and superior P&L.

Keywords: Market Performativity, Feedback Loops, Market Making, Algorithmic Strategy, Arbitrage, General Financial Markets

Complexity vs Empirical Score

  • Math Complexity: 9.0/10
  • Empirical Rigor: 3.0/10
  • Quadrant: Lab Rats
  • Why: The paper presents a sophisticated mathematical framework with stochastic calculus, closed-form solutions, and HJB equations, yet relies on theoretical derivations and simulations rather than real-market backtests or live data.
  flowchart TD
    A["Research Goal:<br>Formulate Market Performativity<br>in Financial Models"] --> B["Core Methodology:<br>Embed Model in Market Process<br>Create Feedback Loop"]
    B --> C["Data/Inputs:<br>Market Price Dynamics &<br>Prevailing Algorithmic Strategies"]
    C --> D["Computational Process:<br>1. Closed-Form Solution<br>2. Machine Learning Implementation"]
    D --> E["Outcome 1:<br>Prices Converge<br>toward Model Conformity"]
    D --> F["Outcome 2:<br>Performative Market Maker<br>Reverse-Engineers Strategies"]
    D --> G["Outcome 3:<br>Effective Arbitrage<br>maintaining Competitive P&L"]