Better market Maker Algorithm to Save Impermanent Loss with High Liquidity Retention
CY Yan, Steve Keol, Xo Co, Nate Leung

TL;DR
This paper introduces a novel dual-mechanism framework for decentralized exchanges, combining a power-law invariant AMM and a dynamic rebate system to significantly reduce impermanent loss and enhance liquidity retention during volatile market conditions.
Contribution
It proposes a new liquidity-optimized AMM model based on a power-law invariant and a dynamic fee rebate system, improving impermanent loss and liquidity retention over traditional models.
Findings
Reduces impermanent loss by 36% compared to constant-product models.
Retains 3.98 times more liquidity during price volatility.
Increases user engagement by 40% under high-volatility conditions.
Abstract
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 limitations: a ``Better Market Maker (BMM)'', which is a liquidity-optimized AMM based on a power-law invariant (, ), and a dynamic rebate system (DRS) for redistributing transaction fees. The segment-specific BMM reduces impermanent loss by 36\% compared to traditional constant-product () models, while retaining 3.98x more liquidity during price volatility. The DRS allocates fees (, ) with a rebate ratio to incentivize trader participation and maintain continuous capital injection. Simulations under high-volatility conditions demonstrate impermanent loss…
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Taxonomy
TopicsStock Market Forecasting Methods · Complex Systems and Time Series Analysis · Financial Markets and Investment Strategies
