We consider an automated market maker (AMM) in which all trades are batched
and executed at a price equal to the marginal price (i.e., the price of an
arbitrarily small trade) after the batch trades. We show that such an AMM is a
function maximizing AMM (or FM-AMM): for given prices, it trades to reach the
highest possible value of a given function. Competition between arbitrageurs
guarantees that an FM-AMM always trades at a fair, equilibrium price, and
arbitrage profits (also known as LVR) are eliminated. Sandwich attacks are also
eliminated because all trades occur at the exogenously-determined equilibrium
price. We use Binance price data to simulate the lower bound to the return of
providing liquidity to an FM-AMM. We show that this bound is very close to the
empirical returns of providing liquidity on Uniswap v3 (at least for the token
pairs and the period we consider).Comment: Arbitrage profits, Loss-vs-Rebalancing (LVR), MEV, Sandwich attacks,
AMM, Mechanism design, Batch tradin