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[CS.AI] Optimal Adaptive Market Making Framework for High-Yield Liquidity

Published at: 2026-07-15 22:00 Last updated: 2026-07-17 08:46
#algorithm #optimization #C++

We have developed a rigorous theoretical framework for optimal market making in perpetual futures markets with zero maker fees. The market maker's problem is modeled as a stochastic optimal control problem on a filtered probability space, with controls being adaptive bid-ask spreads and inventory hedging decisions across two exchanges.

Our contributions include:

  1. A PnL decomposition theorem that separates revenue into spread income, adverse selection loss, inventory carrying cost, hedging friction, and funding rate exposure;
  2. The Hamilton-Jacobi-Bellman equation for the joint spread-inventory-hedging control problem under CARA utility with a verification theorem;
  3. High-APY Regime Theorems characterizing profitable regions via five dimensionless parameters, culminating in a Master APY Formula;
  4. Analysis of zero-fee economics on decentralized perpetual exchanges with optimal entry-exit thresholds;
  5. Optimal cross-exchange hedging policies with funding rate dynamics and a hedge regime trichotomy;
  6. A robustness margin quantifying parameter uncertainty tolerance;
  7. Exponential drawdown probability bounds and a universal APY-VaR identity;
  8. Ergodic inventory distribution under optimal control with Bayesian adaptive estimation;
  9. Kelly-optimal leverage with ruin boundaries;
  10. Multi-pair portfolio allocation with diversification saturation results.

Numerical analysis with twenty-three figures reveals phase transitions between profitable and unprofitable regimes. Our framework unifies and extends the Avellaneda-Stoikov, Gueant-Lehalle-Fernandez-Tapia, and Glosten-Milgrom paradigms for modern decentralized venue microstructure.

Blogger's Review: This paper offers profound theoretical insights into market making in perpetual futures, especially in a zero-fee environment. By introducing complex mathematical tools and models, it enables market participants to manage liquidity more precisely while laying a solid foundation for future research.

Original Source: https://arxiv.org/abs/2607.11888

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