We analyze the market microstructure of Automated Market Maker (AMM) with constant product function , the most prominent type of blockchain-based decentralized crypto exchange. We show that, even without information asymmetries,  the order execution mechanism of the blockchain-based exchange induces adverse selection problems for liquidity providers if token prices are volatile. AMM is more likely to be adopted for pairs of coins which are stable or of high personal use for investors. For high volatility tokens, there exists a market breakdown such that rational liquidity providers do not deposit their tokens in the first place . The adoption of AMM leads to a surge of transaction fees on the underlying blockchain if token prices are subject to high fluctuations .
We analyze the market microstructure of Automated Market Maker (AMM) , the most prominent type of blockchain-based decentralized crypto exchange. We show that, even without information asymmetries, liquidity providers lose token value if exchange rates are volatile due to the order execution mechanism of the blockchain-based exchange . AMMs are more likely to be adopted for pairs of coins which are stable or of high personal use for investors. Liquidity providers may not deposit their tokens if the exchange rate volatility is high, leading to a liquidity freeze . The adoption of AMMs leads to a surge of transaction fees on the underlying blockchain if token exchange rates fluctuate wildly. We provide empirical support for our model implications using transaction-level data of AMMs .
D
with constant product function
A
liquidity providers lose token value if exchange rates are volatile due to
R
induces adverse selection problems for liquidity providers if token prices are volatile. AMM is
. AMMs are
R
For high volatility tokens, there exists a market breakdown such that rational liquidity providers do
Liquidity providers may
R
in the first place
if the exchange rate volatility is high, leading to a liquidity freeze
R
AMM
AMMs
R
prices are subject to high fluctuations
exchange rates fluctuate wildly. We provide empirical support for our model implications using transaction-level data of AMMs