RL◆ AI-generated · Sourced

Optimal Adaptive Market Making: A Theoretical Framework for High-Yield Liquidity Provision in Perpetual Futures Markets

Optimal Adaptive Market Making: A Theoretical Framework for High-Yield Liquidity Provision in Perpetual Futures Markets
TL;DR

arXiv:2607.11888v1 introduces the first rigorous stochastic optimal control framework for market making in zero-maker-fee perpetual futures markets, deriving a decomposable PnL structure, the HJB equation under CARA utility with verification theorem, and a Master APY Formula characterizing profitable regimes via five dimensionless parameters.

Core Contribution: Rigor Meets Quantitative Actionability

This paper (arXiv:2607.11888v1) establishes the first rigorous optimal market making framework for zero-maker-fee perpetual futures markets, formulating the market maker’s problem as a stochastic optimal control problem on a filtered probability space, with controls being adaptive bid-ask spreads and cross-exchange inventory hedging decisions.

Key Technical Results

  • PnL Decomposition Theorem: Profit-and-loss is rigorously decomposed into five components — spread income, adverse selection loss, inventory carrying cost, hedging friction, and funding rate exposure;
  • HJB Equation & Verification Theorem: Derives the Hamilton-Jacobi-Bellman equation for the joint spread-inventory-hedging control problem under Constant Absolute Risk Aversion (CARA) utility, accompanied by a full verification theorem;
  • High-APY Regime Characterization: Introduces High-APY Regime Theorems that define profitable regions using five dimensionless parameters (e.g., relative volatility ratio, funding rate Sharpe ratio, hedging latency factor), culminating in a closed-form Master APY Formula;
  • Zero-Fee Economics Analysis: First systematic analysis of optimal entry-exit thresholds for liquidity provision on decentralized perpetual exchanges operating with zero maker fees;
  • Cross-Exchange Hedging Policies: Integrates dynamic funding rate modeling and proposes a hedge regime trichotomy—distinguishing arbitrage-dominated, risk-hedging-dominated, and liquidity-capture-dominated regimes;
  • Robustness Margin: Quantifies parameter uncertainty tolerance via a formally defined robustness margin;
  • Tail-Risk Control: Provides exponential drawdown probability bounds and a universal AP (asset pricing) approximation.
Sources (compliance trail)
https://arxiv.org/abs/2607.11888
Umi Intelligence · Enroll / Contact

Turn “understanding the frontier” into “putting it to work”

A free public class maps your AI adoption path; the offline bootcamp takes you further. Reach out anytime.

✉ hello@umi6.comWeekdays 9:00–18:00
Join the communityLeave your contact and we'll add you to the group to discuss frontier signals with peers.