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Related papers: Impermanent loss and Loss-vs-Rebalancing II

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There are two predominant metrics to assess the performance of automated market makers and their profitability for liquidity providers: 'impermanent loss' (IL) and 'loss-versus-rebalance' (LVR). In this short paper we shed light on the…

Statistical Finance · Quantitative Finance 2025-05-16 Abe Alexander , Lars Fritz

Although modern blockchains almost universally produce blocks at fixed intervals, existing models still lack an analytical formula for the loss-versus-rebalancing (LVR) incurred by Automated Market Makers (AMMs) liquidity providers in this…

Mathematical Finance · Quantitative Finance 2025-05-16 Alex Nezlobin , Martin Tassy

Automated Market Makers (AMMs) hold assets and are constantly being rebalanced by external arbitrageurs to match external market prices. Loss-versus-rebalancing (LVR) is a pivotal metric for measuring how an AMM pool performs for its…

Trading and Market Microstructure · Quantitative Finance 2024-11-01 Matthew Willetts , Christian Harrington

We consider the market microstructure of automated market makers (AMMs) from the perspective of liquidity providers (LPs). Our central contribution is a ``Black-Scholes formula for AMMs''. We identify the main adverse selection cost…

Mathematical Finance · Quantitative Finance 2024-05-29 Jason Milionis , Ciamac C. Moallemi , Tim Roughgarden , Anthony Lee Zhang

This paper mathematically models a constant-function automated market maker (CFAMM) position as a portfolio of exotic options, known as perpetual American continuous-installment (CI) options. This model replicates an AMM position's delta at…

We derive the arbitrage gains or, equivalently, Loss Versus Rebalancing (LVR) for arbitrage between \textit{two imperfectly liquid} markets, extending prior work that assumes the existence of an infinitely liquid reference market. Our…

Mathematical Finance · Quantitative Finance 2025-12-03 Christoph Schlegel , Quintus Kilbourn

The always-available liquidity of automated market makers (AMMs) has been one of the most important catalysts in early cryptocurrency adoption. However, it has become increasingly evident that AMMs in their current form are not viable…

Computer Science and Game Theory · Computer Science 2023-08-10 Conor McMenamin , Vanesa Daza , Bruno Mazorra

AMMs are autonomous smart contracts deployed on a blockchain that make markets between different assets that live on that chain. In this paper we are examining a specific class of AMMs called Constant Function Market Makers whose trading…

Trading and Market Microstructure · Quantitative Finance 2021-11-18 Stefan Loesch , Nate Hindman , Mark B Richardson , Nicholas Welch

Passive liquidity providers (LPs) in automated market makers (AMMs) face losses due to adverse selection (LVR), which static trading fees often fail to offset in practice. We study the key determinants of LP profitability in a dynamic…

Trading and Market Microstructure · Quantitative Finance 2025-08-12 Steven Campbell , Philippe Bergault , Jason Milionis , Marcel Nutz

Decentralized exchanges (DEXs) are crucial to decentralized finance (DeFi) as they enable trading without intermediaries. However, they face challenges like impermanent loss (IL), where liquidity providers (LPs) see their assets' value…

Computer Science and Game Theory · Computer Science 2026-03-04 Irina Lebedeva , Dmitrii Umnov , Yury Yanovich , Ignat Melnikov , George Ovchinnikov

Dynamic-weight AMMs (aka Temporal Function Market Makers, TFMMs) implement algorithmic asset allocation, analogous to index or smart beta funds, by continuously updating pools' weights. A strategy updates target weights over time, and…

Trading and Market Microstructure · Quantitative Finance 2026-02-26 Matthew Willetts , Christian Harrington

We consider the impact of trading fees on the profits of arbitrageurs trading against an automated market maker (AMM) or, equivalently, on the adverse selection incurred by liquidity providers (LPs) due to arbitrage. We extend the model of…

Mathematical Finance · Quantitative Finance 2025-07-24 Jason Milionis , Ciamac C. Moallemi , Tim Roughgarden

We provide a framework for analyzing impermanent loss for general Automated Market Makers (AMMs) and show that Geometric Mean Market Makers (G3Ms) are in a rigorous sense the simplest class of AMMs from an impermanent loss viewpoint. In…

Trading and Market Microstructure · Quantitative Finance 2022-03-23 Neelesh Tiruviluamala , Alexander Port , Erik Lewis

The gloabal objective of inverse Reinforcement Learning (IRL) is to estimate the unknown cost function of some MDP base on observed trajectories generated by (approximate) optimal policies. The classical approach consists in tuning this…

Machine Learning · Computer Science 2021-05-26 Firas Jarboui , Vianney Perchet

Decentralized exchanges are widely used platforms for trading crypto assets. The most common types work with automated market makers (AMM), allowing traders to exchange assets without needing to find matching counterparties. Thereby,…

General Economics · Economics 2024-02-12 Matthias Hafner , Helmut Dietl

We study the problem of optimal liquidity withdrawal for a representative liquidity provider (LP) in an automated market maker (AMM). LPs earn fees from trading activity but are exposed to impermanent loss (IL) due to price fluctuations.…

Trading and Market Microstructure · Quantitative Finance 2025-10-21 Philippe Bergault , Sébastien Bieber , Leandro Sánchez-Betancourt

The latency of the exchanges in Market Making (MM) is inevitable due to hardware limitations, system processing times, delays in receiving data from exchanges, the time required for order transmission to reach the market, etc. Existing…

Machine Learning · Computer Science 2025-05-20 Junzhe Jiang , Chang Yang , Xinrun Wang , Zhiming Li , Xiao Huang , Bo Li

With the emergence of decentralized finance, new trading mechanisms called Automated Market Makers have appeared. The most popular Automated Market Makers are Constant Function Market Makers. They have been studied both theoretically and…

Trading and Market Microstructure · Quantitative Finance 2023-11-21 Philippe Bergault , Louis Bertucci , David Bouba , Olivier Guéant

Decentralized exchanges (DEXs) face persistent challenges in liquidity retention and user engagement due to inefficiencies in conventional automated market maker (AMM) designs. This work proposes a dual-mechanism framework to address these…

Trading and Market Microstructure · Quantitative Finance 2025-02-28 CY Yan , Steve Keol , Xo Co , Nate Leung

Liquidity providers are essential for the function of decentralized exchanges to ensure liquidity takers can be guaranteed a counterparty for their trades. However, liquidity providers investing in liquidity pools face many risks, the most…

Trading and Market Microstructure · Quantitative Finance 2023-01-18 Rohan Tangri , Peter Yatsyshin , Elisabeth A. Duijnstee , Danilo Mandic
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