Statistical Arbitrage on Uniswap V3 (Full Strategy)
Statistical Arbitrage — Part 2: Strategy and Modeling
The Statistical Arbitrage Series is a collaboration between
and to present stat arb strategies and their application in a blockchain environment.Many entries in the series will be written by a single author, however the series will be available in full on both publications.
About Vertox
Vertox is a quantitative researcher from Germany who started learning about quantitative finance at the age of 14 and hasn’t stopped since.
His publication VertoxQuant covers all things quantitative finance. From simple momentum trading all the way to complex strategies involving stochastic calculus and market making.
About BowTiedDevil
BowTiedDevil is a lifelong techie who discovered the magic of computers by playing MS-DOS games on the family PC (a 286-DX). He learned how to write simple programs in BASIC, then C. He discovered the world of open source software from a Mandrake Linux CD included in a magazine.
His Ethereum bot-building experiments in 2021 were fruitful, so he began writing regularly at Degen Code where he focuses on the development of Ethereum trading bots using Python.
Foundations
This post is primarily authored by
and presents the full Uniswap V3 concentrated liquidity statistical arbitrage strategy, including full code and modeling.Table of Contents
Statistical Arbitrage with Concentrated Liquidity
Profit & Loss
Euler–Maruyama Method
Monte Carlo Simulation
Maximization with Golden-Section Search
Fitting to Historical Data
Conclusion