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

TL;DR

This paper develops advanced price-aware automated market maker models incorporating stochastic volatility, jumps, and microstructural dynamics, addressing demand variability with sophisticated stochastic processes to optimize quoting strategies.

Contribution

It introduces novel models that extend traditional frameworks by integrating complex price dynamics and demand variability, along with analysis of numerical methods for optimal quote computation.

Findings

Models include stochastic volatility, jumps, and Hawkes processes.

Analysis of numerical complexity for optimal quote calculation.

Enhanced understanding of demand variability impacts.

Abstract

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.