考虑随机资金费率的永续合约做市
文章 arXiv papers · 作者: Nam Anh Le
总结
本文将最优做市扩展至资金费率随机变化的永续合约。由于做市商库存会同时影响价格敞口和资金现金流，作者构建了一个联合控制库存与资金费率的问题。他们使用Hamilton-Jacobi-Bellman方程的单调有限差分方法求解，再根据不同库存水平之间的价值变化推导买卖报价偏移。
研究使用Hyperliquid的ETH、BTC和SOL永续合约数据校准资金费率行为。作者以高斯Ornstein-Uhlenbeck资金费率作为便于处理的基准，并考察显示资金费率创新具有厚尾特征的跳跃诊断结果。在使用两种成交代理校准方式的留出模拟中，相较于经典Avellaneda-Stoikov方法，该方法提高了ETH和BTC的平均表现，并降低了库存RMS。SOL相较于未缩放的Avellaneda-Stoikov方法有所改善，但相较于经风险缩放的诊断方案并未实现帕累托改进。研究发现取决于模拟假设和代理成交；摘录并未证明其在实盘市场中的表现，跳跃行为仍有待未来模型扩展处理。
核心观点
- 永续合约做市库存会影响盯市风险和资金现金流。
- 控制问题将库存与随机资金费率状态联合建模。
- 研究使用有限差分HJB解推导买卖报价偏移。
- 尽管有证据表明资金费率创新具有厚尾特征，研究仍以高斯Ornstein-Uhlenbeck资金费率作为便于处理的基准。
- 留出模拟结果因资产和基准而异；相较于经风险缩放的Avellaneda-Stoikov方法，SOL未实现帕累托改进。
标签
全文
# Funding-Aware Optimal Market Making for Perpetual DEXs # Funding-Aware Optimal Market Making for Perpetual DEXs This paper studies optimal liquidity provision for perpetual contracts when the funding rate is a stochastic state variable. The core extension to classical market making is the coupling between inventory and funding payments: inventory creates both mark-to-market exposure and a state-dependent funding cash flow. A reduced inventory-funding control problem is formulated, solved with a monotone finite-difference Hamilton-Jacobi-Bellman scheme, and bid and ask quote offsets are recovered from discrete inventory value differences. Funding is calibrated on Hyperliquid ETH, BTC, and SOL perpetual data. Gaussian OU funding is retained as a tractable diffusion baseline, while OU-plus-jump diagnostics document the heavy-tailed funding innovations that should enter a future extension. In 100-seed holdout simulations under two official-fill proxy calibrations, the funding-aware HJB improves mean ETH/BTC performance while lowering inventory RMS relative to classical Avellaneda-Stoikov. SOL gains are positive versus unscaled AS but are not a Pareto improvement once a risk-scaled AS diagnostic is included.
在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0
此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。