Dissertation Defense:“Essays on Decentralized Exchanges”, Nir Chemaya, University of California, Santa Barbara

Speaker

Nir Chemaya, University of California, Santa Barbara

Biography

Nir Chemaya is a PhD Candidate in Economics at the University of California, Santa Barbara. He focuses on researching Finance and Behavioral and Experimental Economics. Nir is particularly interested in exploring innovations in the Fintech markets, such as blockchain and Decentralized Finance (DeFi), and agents' interactions with those technologies. In this spirit, Nir’s job market paper estimates traders' preferences for blockchain security from a big trading data set of over 19M transactions from Decentralized Exchange (DEX) platforms. Using empirical or experimental data and applying traditional economic models and rigorous analysis, Nir examines and unpacks current hypotheses about trends in Blockchain and DeFi.

In addition to his research, Nir is actively involved in teaching and academic service. Nir was one of the lead organizers of the Economic Science Association 2022 North American conference in Santa Barbara in November 2022 and is currently one of the leaders of the UCSB-ECON DeFi Seminar, which is a graduate-student-led seminar series sponsored by Uniswap. In addition, he has been the head teaching assistant or teaching assistant for courses in microeconomics, macroeconomics, and other specialized topics at UC Santa Barbara. He holds Bachelor and Master degrees in Economics from Ben Gurion University in Israel.

Title

“Essays on Decentralized Exchanges”

Abstract

This dissertation consists of essays that study decentralized exchange markets from different perspectives, such as
security, slippage settings, and transaction ordering. The first chapter explores swapping decisions on decentralized
exchanges (DEX). With the increasing adoption of DEX platforms, new Layer 2 (L2) blockchain alternatives offer better scalability and lower fees than the Ethereum blockchain (L1), yet the relative security of L2 is uncertain. Using a structural model and a novel dataset, we estimate investor preferences for blockchain security between mainnet (L1), and two main L2 networks, Polygon and Optimism. We find that traders anticipate a 0.68\% (3.29%) chance of losing transaction value when trading on Polygon (Optimism) compared to L1, significantly higher than the transaction fees (0.01%-0.3%) charged on each trade. Our findings provide empirical evidence of the trade-off between scalability, security, and decentralization, a major challenge for blockchain networks.

The second chapter investigates slippage default settings on DEX. DEX prices update continuously after each swap, causing potential price shifts for users awaiting execution. Users set a slippage tolerance to limit acceptable price increases, but this can either expose them to sandwich attacks or cause transaction failures. We analyze the impact of slippage tolerance settings on the health of Uniswap and Sushiswap ecosystems. A recent Uniswap change replaced the static default slippage setting (0.5%) with a dynamic one based on market conditions to reduce sandwich attacks. We find that this change significantly reduces trader losses by approximately 54.7%, with an even more pronounced effect (90%) for traders following the default settings. We also propose further improvements for these settings.

The final chapter explores the impact of transaction ordering on DEX AMM markets. A critical challenge of AMM-powered trading is that transaction order has high financial value, so a policy or method to order transactions in a "good" (optimal) manner is vital. We offer economic measures of both price stability (low volatility) and inequality that inform how a "social planner" should pick an optimal ordering. We show that there is a trade-off between achieving price stability and reducing inequality, and that policymakers must choose which to prioritize. In addition, picking the optimal order can often be costly, especially when performing an exhaustive search over trade orderings (permutations). As an alternative we provide a simple algorithm, Clever Look-ahead Volatility Reduction (CLVR). This algorithm constructs an ordering which approximately minimizes price volatility with a small computation cost. We also provide insight into the strategy changes that may occur if traders are subject to this sequencing algorithm.

Keywords: Automated Market Making, Blockchain, Cryptocurrency, Decentralized Exchanges, Decentralized Finance, Defi, Default Effect, Layer 1, Layer 2, Security, Ordering and Price Stability
JEL Codes: D81, D83, G10, G19, G40

Event Details

Join us to hear Nir’s dissertation defense. He will be presenting his dissertation titled, “Essays in
Decentralized Exchanges”. To access a copy of the dissertation, you must have an active UCSB NetID and
password.