Abstract
In this paper we introduce a new zero-intelligence framework to analyse price formation in a cryptocurrency decentralised exchange (DEX) combining agent-based modelling and real trading history. We shuffle real Uniswap order event data and replay back into the automatic market maker (AMM) matching mechanism. We study how decomposing real markets down from bounded rationality to zero-intelligence markets in a controlled experiment affects liquidity provider’s impermanent loss, trade slippage and price efficiency.
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