Decentralised Finance and Automated Market Making: Execution and Speculation

45 Pages Posted: 30 Jun 2022 Last revised: 14 Mar 2023

See all articles by Álvaro Cartea

Álvaro Cartea

University of Oxford; University of Oxford - Oxford-Man Institute of Quantitative Finance

Fayçal Drissi

University of Oxford - Oxford-Man Institute of Quantitative Finance

Marcello Monga

University of Oxford; University of Oxford - Oxford-Man Institute of Quantitative Finance

Date Written: June 23, 2022

Abstract

Automated market makers (AMMs) are a new prototype of trading venues which are revolutionising the way market participants interact. At present, the majority of AMMs are constant function market makers (CFMMs) where a deterministic trading function determines how markets are cleared. A distinctive characteristic of CFMMs is that execution costs are given by a closed-form function of price, liquidity, and transaction size. This gives rise to a new class of trading problems. We focus on constant product market makers and show how to optimally trade a large position in an asset and how to execute statistical arbitrages based on market signals. We employ stochastic optimal control tools to devise two strategies. One strategy is based on the dynamics of prices in competing venues and assumes constant liquidity in the AMM. The other strategy assumes that AMM prices are efficient and liquidity is stochastic. We use Uniswap v3 data to study price, liquidity, and trading cost dynamics, and to motivate the models. Finally, we perform consecutive runs of in-sample estimation of model parameters and out-of-sample liquidation and arbitrage strategies to showcase the performance of the strategies.

Keywords: Decentralised Finance, Automated Market Making, Algorithmic Trading, Statistical Arbitrage, Predictive Signals, Market Impact, Adaptive Strategies, Smart Contracts

Suggested Citation

Cartea, Álvaro and Drissi, Fayçal and Monga, Marcello, Decentralised Finance and Automated Market Making: Execution and Speculation (June 23, 2022). Available at SSRN: https://ssrn.com/abstract=4144743 or http://dx.doi.org/10.2139/ssrn.4144743

Álvaro Cartea (Contact Author)

University of Oxford ( email )

Mansfield Road
Oxford, Oxfordshire OX1 4AU
United Kingdom

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

Eagle House
Walton Well Road
Oxford, Oxfordshire OX2 6ED
United Kingdom

Fayçal Drissi

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

Eagle House
Walton Well Road
Oxford, Oxfordshire OX2 6ED
United Kingdom

Marcello Monga

University of Oxford ( email )

Mansfield Road
Oxford, Oxfordshire OX1 4AU
United Kingdom

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

Eagle House
Walton Well Road
Oxford, Oxfordshire OX2 6ED
United Kingdom

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
4,592
Abstract Views
9,495
Rank
3,540
PlumX Metrics