Research
Research Areas: Agentic AI, Dark Web, Distributed Ledgers, Stablecoins, Accounting Regulations, General Economics and Finance
Agentic Artificial Intelligence
- AI Agents and Accounting Standards Experiments (Thesis) [show abstract]
This study uses AI agents to replicatively re-run accounting experiments published on FASB accounting standards. The results show that AI agents consistently mitigate a high proportion of cognitive biases observed in human participants, regardless of expertise, across tasks in information processing, auditing, and management accounting. AI agents can also be configured to simulate specific biases, enabling controlled testing of behavioral assumptions. A comparison across old and new model generations reveals a clear shift from heuristic-driven to more consistent and rational decision-making. Additionally, AI agents can be used to identify design flaws in experiments and support cross-cultural replication at scale. Some prior experimental findings may also reflect design artifacts rather than genuine behavioral effects.
Conferences and Presentations
- Information or Institution? AI’s role in Expert Testimony [show abstract]
This paper studies whether the value of expert testimony lies primarily in its informational content or in the institutional role of the expert witness. Using federal district court Daubert rulings in copyright cases, we show that admissibility is not determined by methodology alone, but also by institutional considerations. We develop a model to ground this intuition and to show how AI can compress differences in methodological production while making institutional signals more important for judicial evaluation. Empirically, we then compare observed expert packages to AI-generated packages from neutralized case descriptions and find that AI reproduces much of the methodology and topic coverage of retained experts, while systematically proposing broader and more credentialed expert designs. AI-generated packages are closest to experts whose testimony is admitted and furthest from those whose testimony is excluded. The results show that methodology is increasingly reproducible, but institutional features of the expert still matter for admissibility.
Coauthors: Shou-Ming Chang
Conferences and Presentations
Digital Assets
- Election Prediction Markets: Evidence from Polymarket, Kalshi, and Robinhood [show abstract]
This paper provides the first empirical analysis of federally legalized U.S. election prediction markets, using transaction-level data from four major platforms: Polymarket, Kalshi, PredictIt, and Robinhood, during the 15 days preceding the 2024 presidential election. We find that within-platform arbitrage is virtually absent, while persistent cross-platform arbitrage, especially in illiquid contracts, reflects segmentation in liquidity and pricing. Liquidity emerges as the primary driver of price discovery, with Polymarket and Robinhood leading due to deeper markets. Market design also matters, as Polymarket’s limit order book facilitates faster information incorporation than Kalshi’s automated market maker. Finally, large “whale” trades significantly impact prices and order flow, with asymmetric effects.
Coauthors: Lin Peng, Dexin Zhou, Yubo Tao
Conferences and Presentations
- Finance Seminar, Baruch College, June 2025
- Finance Seminar, The Hong Kong Polytechnic University, Oct 2025
- How Wash Traders Exploit Market Conditions in Cryptocurrency Markets [show abstract]
Wash trading, the practice of simultaneously placing buy and sell orders for the same asset to inflate trading volume, has been prevalent in cryptocurrency markets. This paper investigates whether wash traders in Bitcoin act deliberately to exploit market conditions and identifies the characteristics of such manipulative behavior. Using a unique dataset of 18 million transactions from Mt. Gox, once the largest Bitcoin exchange, I find that wash trading intensifies when legitimate trading volume is low and diminishes when it is high, indicating strategic timing to maximize impact in less liquid markets. The activity also exhibits spillover effects across platforms and decreases when trading volumes in other asset classes like stocks or gold rise, suggesting sensitivity to broader market dynamics. Additionally, wash traders exploit periods of heightened media attention and online rumors to amplify their influence, causing rapid but short-lived spikes in legitimate trading volume. Using an exogenous demand shock associated with illicit online marketplaces, I find that wash trading responds to contemporaneous events affecting Bitcoin demand. These results advance the understanding of manipulative practices in digital currency markets and have significant implications for regulators aiming to detect and prevent wash trading.
Conferences and Presentations
- The Annual Baruch College/CUNY Southwestern University of Finance and Economics (SWUFE) Research Symposium, Baruch College, May 2025
ESG
- Disclosure Policy Diffusion Mechanisms [show abstract]
This paper studies why mandatory ESG disclosure rules spread unevenly across countries, focusing first on greenhouse-gas disclosure and framing adoption through the classic policy-diffusion channels of learning, competition, imitation, and coercion. Using a country-year panel and discrete-time hazard models, it finds that broad diffusion pressure and especially competitive exposure to already regulated jurisdictions are associated with adoption, while the current proxies for learning and imitation do not perform as expected in the data. The consequences of disclosure regulation depend not just on whether countries adopt, but on how they adopt, with the broader goal of linking diffusion mechanisms to later market outcomes such as liquidity and policy credibility.
Coauthors: Lauren Vollon, Svenja Dube, Cheryl Sun
General Economics
- Why is it so hard to find a job now? Enter Ghost Jobs [show abstract]
This paper investigates "ghost jobs", which are vacancies posted without intent to hire, using a novel dataset of interview reviews from Glassdoor. Using a fine-tuned BERT model, I find that approximately 21% of job postings exhibit patterns consistent with ghost jobs. These are disproportionately concentrated in larger firms and high-skill industries, where firms may benefit from resume collection, market intelligence, or signaling. I also show that incorporating ghost job prevalence helps reconcile the recent disconnect in the Beveridge Curve between vacancy and hiring rates. The results highlight how ghost hiring imposes costs on job seekers, distorts labor market indicators, and warrants closer scrutiny from policymakers.
- Beyond Words: The Differential Impact of Fed Chairs’ Facial Expressions on Financial Markets [show abstract]
This paper explores how Federal Reserve Chairs' facial expressions during FOMC press conferences influence investor behavior and financial markets. Using facial recognition technology and deepfake simulations on press conference videos from April 2011 to December 2020, I quantify changes in nonverbal signals while controlling for verbal content. My findings reveal that nonverbal cues act as independent public signals that significantly affect market outcomes. Using deepfakes, I uniquely demonstrate that identical facial expressions elicit different market reactions and this depends on the Fed Chair's identity, tenure, and experience, indicating that investor interpretations are dynamically shaped by perceptions of the Chair. Moreover, the evolving market response over time aligns with the dual-processing, bounded memory model of information processing. Lastly, I find no evidence that Fed Chairs strategically change their facial expressions to influence markets, highlighting the unintentional yet impactful nature of nonverbal communication.
- Legitimacy and the Fluid Singaporean Welfare (Published in Sociology Compass) [show abstract]
This paper develops a theory of the fluid welfare state, in which legitimacy rather than efficiency constitutes the central constraint of welfare governance. Using a dynamic model of government–citizen interaction, we show that a state that adjusts its welfare messaging across social groups enhances legitimacy when the persuasive benefit exceeds the credibility cost. The framework is inductively derived from the case of Singapore, which exemplifies how a small, open, and fiscally disciplined East Asian productivist welfare state can sustain public trust through performance and communication rather than extensive redistribution. As welfare communication increasingly takes place through digital platforms and social media, the capacity to adapt these narratives can be a powerful tool for all regimes. The concept of the fluid welfare state therefore provides a framework for understanding how contemporary governments, particularly those facing fiscal and demographic constraints, can preserve welfare legitimacy through adaptive persuasion rather than expansionary spending.
Research Essays
Dissertation Committee
- Edward Li (Baruch College)
- Lin Peng (Baruch College)
- Svenja Dube (Baruch College)
- Diana Weng (University of South Florida, Tampa)
Advisors
- Yen Tong (Nanyang Technological University)
- Kalin Kolev (Baruch College)
Peer Reviews
- 2026 Reviewer for Journal of International Financial Markets, Institutions & Money
- 2025 Reviewer for Cogent
- 2025 Reviewer for Journal of International Financial Markets, Institutions & Money
- 2023 Management Science Reproducibility Project
Conferences and Presentations
- AES Baruch Accounting Theory Summer School 2025
- Taught by Ivan Marinovic, Jon Glover, Jeremy Bertomeu
- Hawaii Doctoral Institute Summer 2025
- Taught by Hans Christensen, Brian White, Joe Schroeder, Jennifer Blouin
- Gave presentations in class on selected papers
- 2025 Baruch-SWUFE Research Symposium
- Presented paper
- Download Agenda
- 2025 Baruch PhD Research Day in Finance
- Presented Paper
- Download Agenda
- 2025 Finance Brownbag
- Presented Paper
- Download Agenda
- 2025 Baruch/JFQA Climate Finance Conference
- Participant
- 2025 Baruch-Fordham-Rutgers Trischool Conference
- Participant
- 2024 The Chinese Finance Association TCFA 30th Annual Conference
- Participant
- NYU Accounting Theory Summer School 2024
- Taught by Ilan Guttman, Judson Caskey, Jeremy Bertomeu
- Duke University Accounting Theory Summer School 2024
- Presented paper - “Cybersecurity Disclosures”.
- Taught by Itay Goldstein, Qi Chen, Chandra Kanodia, Thomas Hemmer
Awards
- Mills & Tannenbaum Award 2025
- Donald Vredenburgh Research Grant 2025