This paper introduces a mathematical framework for performativity in financial markets, focusing on market making. The authors model the asset mid-price as mean-reverting to a reference process representing the valuation implied by dominant trading strategies, creating a feedback loop. They derive closed-form solutions for a performativity-aware market maker who optimally responds to the endogenous price drift generated by competitors using classical strategies (e.g., Avellaneda-Stoikov). The performatively optimal strategy can reverse trading incentives compared to classical optimality, e.g., selling when the classical strategy buys. The paper also defines performative stability as a fixed point where the strategy remains optimal under the price process it induces, and shows that under linear utility the only stable strategy is quoting at the current mid-price. Simulations confirm that performativity-aware strategies consistently outperform classical baselines as the performativity parameter increases, highlighting the importance of accounting for model-induced feedback in modern markets.