• When Automation Meets Accountability: International Evidence from Robotics Adoption and ESG Incidents, with Sadok El Ghoul, Omrane Guedhami, and Siqi Wei. (Link)

Presentations: FMA 2025, 19th International Behavioural Finance Conference, University of Richmond, SWFA 2026, FMA Europe 2026 (scheduled), CICF 2026 (scheduled), AAA 2026 (scheduled).​

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• Using global industrial robotics data as a proxy for automation, and ESG incident measures as a proxy for ESG risk, we find that robotics stock and flow are positively associated with higher firm-level ESG risk, including the frequency of ESG incidents, the overall ESG risk index, and the severity, reach, and novelty of these incidents.

• The impact is more pronounced for environmental- and social-related incidents.

• Using internet fixed broadband subscriptions and population aging measures as instruments, we show that these results are causal.

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• Endogenous Preference and Green Bond Pricing, with Ming Li, Nancy Tran, and Matthew Wilson. (SSRN link).

Presentations: University of Richmond Research Symposium, Robins School Research Lunch, FMA 2024, CEMA 2025, EFMA 2025, CICF 2025, AAA 2025 Global Emerging Scholar Research Workshop.​

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• Using a macro model based on endogenous preference theory, our paper explores how climate change concern captured by news media influences green bond premiums.

• Empirical analysis of U.S. municipal bonds shows that green bonds are traded at 7 basis points lower than non-green bonds during the periods of increased climate change concerns.

• Investors' non-financial motives rather than their desire to hedge against climate risk are the primary mechanisms driving our results.

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• Do Corporate Insiders Take Advantage of Their Political Connections? Evidence from Insider Trading, with Haoyang Xiong (SSRN link).

Presentations: University of Oklahoma, AFFI Conference PhD Workshop 2021, EFMA 2021, SWFA 2022, EFA 2022, FMCG 2022, FMA 2022, University of Richmond Research Symposium, City University of Macau.​​

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• Purchases (sales) by politically connected corporate insiders are associated with lower (higher) abnormal returns compared with non-politically connected insiders, indicating that politically connected insiders in general are sophisticated and cautious about potential legal risk.

• Politically connected insiders are more likely to have longer trading horizons, and more likely to make routine trades.

• The STOCK Act passed in April 2012 effectively decreases (increases) the abnormal returns associated with insider purchases (sales) made by Congress members and staff in short horizons.

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• ​Expropriation Through Regulatory Fiat: China’s Blockholder Share Sale Ban, with Yong Li and William Meggingson.

• Attempting to arrest a sharp drop in stock prices in July 2015, Chinese government adopted sale bans of shares held by any 5%+ blockholder in a listed company.

• We examine the short and long-term effects of these bans—focusing on the first shock in July 2015—and document significant destruction of corporate value and blockholder wealth.

• Over the short term, companies with higher treatment intensity, measured by blockholder concentration and ownership percentage, experience higher abnormal returns, lower volatility, lower trading volume, and lower downside risk than companies with lower treatment intensity. However, over the long term, firms with higher treatment intensity experience significant drops in firm values and shareholder wealth.

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• Unlocking Dormant Accounts: A Catalyst for Sustainable Development, with Romora Sitorus and Agustinus Prasetyantoko.

  • Policy Brief prepared for Think 20 (T20) South Africa.​

 

• Converting NPV and IRR Cash Flows into a Financial Calculator Using an Excel Template, with Tom Arnold and Cassandra Marshall.

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• Creating Private Equity Waterfall Functions in Excel, with Tom Arnold and Cassandra Marshall.

 

• Bond Pricing Mechanics Beyond Yield-to-Maturity Based Calculations, with Maura Alexander and Tom Arnold.

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• Monte Carlo Analysis for a Private Equity Transaction in Excel, with Tom Arnold and Cassandra Marshall.
   

• Multiple Application Models for Monte Carlo Analysis in Excel, with Tom Arnold, Deniz Besik, and Nancy Tran.