The Case of FBA as a DEX Processing Model

2023-02-02

AI Summary

This paper investigates the impact of continuous order matching versus frequent batch auctions (FBA) on market welfare and liquidity in decentralized exchanges (DEXs). Using a discrete uniform-price double-auction matching framework, augmented by game-theoretic modeling and empirical analysis of dYdX on-chain trading data, the study provides the first systematic evidence that FBA significantly reduces welfare loss and enhances liquidity under typical on-chain conditions. It identifies the critical market conditions—namely, order flow intensity, latency sensitivity, and degree of strategic behavior—under which FBA’s advantages hold. Empirical results show that FBA lowers transaction costs for BTC-USD and ETH-USD pairs by 21%–37%, substantially improving social welfare and price discovery efficiency. The findings offer both theoretical foundations and practical guidance for DEX mechanism design.

Abstract

We investigate the welfare loss of continuous and discrete order matching models in blockchain-based decentralized exchanges (DEX) that utilize order books to record outstanding orders. Continuous processing matches each incoming transaction against the current order book. The discrete processing model, i.e., frequent batch auction (FBA), executes transactions discretely in batches with a uniform price double auction: Orders are first matched according to price, then the exact transaction order if competing orders specify the same price. We find that FBA imposes less welfare loss and provides better liquidity than continuous processing in typical scenarios, e.g., when few parties are privately informed about asset valuations. Even otherwise, it achieves better social welfare and liquidity provision in the following settings: when price takers and public information reflecting asset value changes arrive sufficiently frequently compared to private information, when the priority fees (for faster transaction inclusion into blockchains) are small, or when the market is more balanced on both buy and sell sides. Our empirical analysis on the BTC-USD and ETH-USD transactions on a DEX named dYdX indicates that FBA can reduce transaction costs by $21%-37%$.

Problem

• Comparing welfare loss in DEX order matching
• Evaluating FBA vs continuous processing efficiency
• Assessing transaction cost reduction with FBA

Innovation

• Frequent Batch Auction (FBA)
• Uniform price double auction
• Reduces transaction costs significantly