Paper: arXiv 2303.00208

Authors: Jason Milionis, Ciamac C. Moallemi, Tim Roughgarden

Abstract

In decentralized finance (“DeFi”), automated market makers (AMMs) enable traders to programmatically exchange one asset for another. Such trades are enabled by the assets deposited by liquidity providers (LPs). The goal of this paper is to characterize and interpret the optimal (i.e., profit-maximizing) strategy of a monopolist liquidity provider, as a function of that LP’s beliefs about asset prices and trader behavior. We introduce a general framework for reasoning about AMMs based on a Bayesian-like belief inference framework, where LPs maintain an asset price estimate. In this model, the market maker (i.e., LP) chooses a demand curve that specifies the quantity of a risky asset to be held at each dollar price. Traders arrive sequentially and submit a price bid that can be interpreted as their estimate of the risky asset price; the AMM responds to this submitted bid with an allocation of the risky asset to the trader, a payment that the trader must pay, and a revised internal estimate for the true asset price. We define an incentive-compatible (IC) AMM as one in which a trader’s optimal strategy is to submit its true estimate of the asset price, and characterize the IC AMMs as those with downward-sloping demand curves and payments defined by a formula familiar from Myerson’s optimal auction theory. We generalize Myerson’s virtual values, and characterize the profit-maximizing IC AMM. The optimal demand curve generally has a jump that can be interpreted as a “bid-ask spread,” which we show is caused by a combination of adverse selection risk (dominant when the degree of information asymmetry is large) and monopoly pricing (dominant when asymmetry is small). This work opens up new research directions into the study of automated exchange mechanisms from the lens of optimal auction theory and iterative belief inference, using tools of theoretical computer science in a novel way.

Complexity vs Empirical Score

  • Math Complexity: 8.5/10
  • Empirical Rigor: 2.5/10
  • Quadrant: Lab Rats — theoretically deep, empirically untested

Why this score: The paper provides a highly novel and mathematically rigorous adaptation of Myersonian mechanism design to Automated Market Makers (AMMs) in DeFi. However, as a purely theoretical framework, it lacks empirical backtesting or real-world transaction data validation.

Research Flowchart

  flowchart TD
    A["Research Goal: Characterize optimal (profit-maximizing) strategy for a monopolist LP in AMMs"] --> B["Input & Belief Model: LP maintains Bayesian price estimate; Traders submit price bids"]
    B --> C["Apply Optimal Auction Theory: Framework using Myersonian Virtual Values & IC Constraints"]
    C --> D["Derive Incentive-Compatible AMM: Enforce downward-sloping demand curves & payment rules"]
    D --> E["Optimization Process: Compute profit-maximizing demand curve with revised internal price estimates"]
    E --> F["Key Outcome: Optimal demand curve exhibits a jump (Bid-Ask Spread)"]
    F --> G["Core Finding: Spread driven by Adverse Selection (high info asymmetry) & Monopoly Pricing (low asymmetry)"]