Research

Dissertation Committee

• Edward Li (Baruch College)
• Lin Peng (Baruch College)
• Svenja Dube (Baruch College)
• Diana Weng (Baruch College)

Advisors

• Yen Tong (Nanyang Technological University)
• Kalin Kolev (Baruch College)
• Mingcherng Deng (Baruch College)

Working Papers

• Election Prediction Markets: Evidence from Polymarket, Kalshi, and Robinhood
  • 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.
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• Beyond Words: The Differential Impact of Fed Chairs’ Facial Expressions on Financial Markets
  • 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.
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• How Wash Traders Exploit Market Conditions in Cryptocurrency Markets
  • 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.
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• Why is it so hard to find a job now? Enter Ghost Jobs
  • 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.
• BigBird for ESG Reports - A Sparse Attention Model For Differences Between Languages In Textual Analysis
  • Coauthored with Shuai Xu (Shanghai University of Finance and Economics, Singapore Management University)
  • This paper introduces BigBird-ESG, a domain-specific transformer architecture pre-trained on manually classified paragraphs from Chinese ESG reports between 2016 to 2020. Our results show that BigBird-ESG, with its sparse attention mechanisms, more efficiently processes Chinese ESG reports due to innate qualities of the Chinese language and its difference from the English language. We show that BigBird-ESG outperforms BERT and FinBERT under specific conditions in both sentiment and category classification tasks. The findings suggest that language specificity affects the accuracy of LLM models in parsing textual data. Our findings affect the future advancement of multi-modal LLMs and transfer learning, which should consider language-specific qualities when interpreting sources of financial information. We also use state-of-the-art OCR to coherently extract paragraphs from the ESG reports, which preserves the meaning of the textual data and we use this new methodology to show that tone in Chinese ESG reports is correlated with ESG ratings.
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• Decreasing Familial Welfare: The Fluid Welfare State in post-COVID Singapore
  • This paper examines Singapore’s post-COVID social policies and argues that its welfare state has evolved into a fluid welfare state. The fluid welfare state is defined not by fixed institutional forms but by its anchoring in legitimacy and core governance values. Rather than expanding traditional welfare provisions, Singapore reinforces its longstanding emphasis on rationality, leanness, and effectiveness through a multirole approach: acting as a wise technocrat, a responsible redistributor, and a loving family member. This shift has involved a retreat from the paradigm of familial welfare, allowing the state greater flexibility to respond to demographic, economic, and technological change. The fluid welfare state offers a distinctive model for how legitimacy, rather than generosity, can sustain public trust and policy adaptability in a rapidly changing global landscape.
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Peer Reviews

• 2025 Reviewer for Journal of International Financial Markets, Institutions & Money
• 2023 Management Science Reproducibility Project

Conferences and Presentations

• Hawaii Doctoral Institute Summer 2025
  • Taught by Hans Christensen, Brian White, Joe Schroeder, Jennifer Blouin
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  • Download WhiteClass_PPT
  • Download ChristensenClass_PPT
• 2025 Baruch-SWUFE Research Symposium
  • Presented paper
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• 2025 Baruch PhD Research Day in Finance
  • Presented Paper
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• 2025 Finance Brownbag
  • Presented Paper
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• 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