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arXiv 2405.03496q-fin.TR
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价格感知型自动做市商:超越布朗价格与静态流动性的模型

Price-Aware Automated Market Makers: Models Beyond Brownian Prices and Static Liquidity

Philippe Bergault, Louis Bertucci, David Bouba, Olivier Guéant, Julien Guilbert

AI总结:

本文针对价格感知型自动做市平台的报价优化需求,提出融合随机波动率、跳变、Hawkes过程微观价格模型及两类需求过程的模型体系,并分析各模型最优报价计算的数值方法复杂度。

摘要:

本文提出了一套适用于希望优化报价的价格感知型自动做市平台的模型。这些模型融合了先进的价格动力学,包括随机波动率、跳变,以及基于Hawkes过程(霍克斯过程)的微观结构价格模型。此外,我们通过采用Hawkes过程或马尔可夫调制泊松过程的模型,解决了流动性 taker( taker,即流动性需求方)需求的可变性问题。我们对每个模型都进行了分析,重点关注计算最优报价所需数值方法的复杂度。

英文摘要:

In this paper, we introduce a suite of models for price-aware automated market making platforms willing to optimize their quotes. These models incorporate advanced price dynamics, including stochastic volatility, jumps, and microstructural price models based on Hawkes processes. Additionally, we address the variability in demand from liquidity takers through models that employ either Hawkes or Markov-modulated Poisson processes. Each model is analyzed with particular emphasis placed on the complexity of the numerical methods required to compute optimal quotes.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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