Dissertation Defense: “Essays in Fintech and Behavioral Economics”, Dingyue (Kite) Liu
Speaker
Dingyue (Kite) Liu, PhD Candidate, University of California, Santa Barbara
Biography
Dingyue is currently a PhD Candidate in the Department of Economics at UC Santa Barbara. Prior to UC Santa Barbara, Dingyue graduated from Purdue University. His main research interests lie in the fields of Fintech and Behavioral Economics. He’s interested in learning how bounded rationality influences decision making and belief formation, both in real life scenarios and through controlled experiments. His work has primarily focused on Decentralized Finance (DeFi), where he the revealed security preferences within the decentralized exchange (DEX) market, and investigates how default slippage tolerance can impact trader welfare. In his other research areas, he has conducted field experiment, lab experiments, and \ worked with large language models (LLMs).
Abstract
This dissertation consists of two essays studying decision making in FinTech, and one essay on decision making in education.
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 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 examines student decision-making, specifically the impact of a gamified leaderboard on engagement and procrastination. Procrastination is common among students, particularly with assignments. Gamification, incorporating game-like elements into education, shows promise in addressing this issue. Our results indicate that students in the treatment group complete assignments faster, suggesting the leaderboard positively influences study behaviors. While the overall class performance effect is not significant, transfer students and male students exposed to the leaderboard achieve higher course grades than their peers in the control group.
JEL Codes: D81, D83, G10, G19, G40, A22
