A theoretical framework for dynamical fee choice in AMMs
arxiv(2024)
摘要
In the ever evolving landscape of decentralized finance automated market
makers (AMMs) play a key role: they provide a market place for trading assets
in a decentralized manner. For so-called bluechip pairs, arbitrage activity
provides a major part of the revenue generation of AMMs but also a major source
of loss due to the so-called informed orderflow. Finding ways to minimize those
losses while still keeping uninformed trading activity alive is a major problem
in the field. In this paper we will investigate the mechanics of said arbitrage
and try to understand how AMMs can maximize the revenue creation or in other
words minimize the losses. To that end, we model the dynamics of arbitrage
activity for a concrete implementation of a pool and study its sensitivity to
the choice of fee aiming to maximize the value retention. We manage to map the
ensuing dynamics to that of a random walk with a specific reward scheme that
provides a convenient starting point for further studies.
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