Working papers

Disagreement and Macro Announcement Returns. 2025. Joint with Xiaowen Lei.

This paper investigates disagreement as a key driver of macro-announcement returns. Using signed SPX option volumes, we separate investor disagreement from uncertainty of expected returns. We show that announcements that more effectively resolve disagreement have higher announcement-day returns. We further decompose the overall disagreement into pre-announcement uncertainty-induced disagreement and post-announcement differential interpretation. We find that the former positively predicts immediate announcement returns, while the latter is significantly negatively associated with post-announcement returns. A two-period asset pricing model with heterogeneous beliefs supports our findings, highlighting disagreement’s critical role in shaping announcement returns.

Expected Return or Mispricing? Evidence from the Term Structure of Option-implied Disagreement. 2025. Joint with Bing Han, and Lei Lu.

We study the term structure of option-implied investor disagreement about future market returns. We document two key patterns: (1) in the cross-section, the term structure of disagreement is generally downward sloping, and (2) in the time series, disagreement does not uniformly decline across all horizons as new information arrives. While aggregate disagreement shows limited predictive power for future market returns, the term structure factors-particularly level and curvature-significantly predict returns from one to 24 months. Moreover, these factors predict returns through distinct channels: the level factor serves as a predictor of mispricing, while the curvature factor captures risk-based variations in returns. Our findings shed light on the dynamics of investor disagreement across varying horizons. 

Risk and Return of Cryptocurrency Carry Trade. 2024. Joint with Feng Jiao, Lei Lu, and Xing Tong.

This paper comprehensively examines the risk-return relation of cryptocurrency carry trade using realistic borrowing and lending interest rates. We find significant violations of the uncovered interest rate parity in the cryptocurrency market. The cross-sectional carry trade strategy yields an annualized return of 46.71% and a Sharpe ratio of 0.77. Unlike fiat-currency carry trade which is vulnerable to crash risk, the cryptocurrency carry trade is resistant to the cryptocurrency market crashes in 2018 and 2021. We show that the crypto-carry trade returns cannot be explained by established risk factors from fiat currencies or cryptocurrencies. We find that geopolitical risk explains a substantial amount of the carry returns. 

Can AI Read the Minds of Corporate Executives? 2023. Joint with Nicolas Chapados, Ruslan Goyenko, Issam Hadj Laradji, Fred Liu, and Chengyu Zhang. 

It can. Using textual information from a complete history of regular quarterly and annual filings by U.S. corporations, we train classic machine learning algorithms and large language models, LLMs, to predict future earnings surprises. We first find that the length of MD&A section on its own is negatively associated with future earnings surprises and firm returns in the cross-section. Second, neither sentiment-based nor bag-of-words classic machine learning regression-based approaches are able to learn from the past managerial discussions to forecast future earnings. Third, only finance-objective trained LLMs have the capacity to understand the contexts of previous 10-Q (10-K) releases to predict both positive and negative earnings surprises, and future firm returns. We find significant, and often hidden in the complexity of presentations, positive and negative informational content of publicly disclosed corporate filings, and superior (to human and classic NLP approaches) abilities of more recent AI models to identify it. 

Publications

Equity Tail Risk and Currency Risk Premium​, with J. M. Londono and X. Xiao, Journal of Financial Economics 143, no. 1 (2022): 484-503

This project is funded by Canadian Derivatives Institute.

We find that a US equity tail risk factor constructed from OTM S&P 500 put option prices explains the cross-sectional variation of currency excess returns. Currencies highly exposed to this factor offer a low currency risk premium because they appreciate when US tail risk increases. 

Moment Risk Premia and Stock Return Predictability, with X. Xiao, H. Zhou, Journal of Financial and Quantitative Analysis 57, no. 1 (2022): 67-93

We find that the moment risk premia implied from equity index options predict stock market returns. Combining the higher moment risk premia with the variance risk premium improves the stock return predictability over multiple horizons, both in-sample and out-of-sample. 

Currency carry trade: The decline in performance after the 2008 Global Financial Crisis, with Alexander Paseka, Zhen Qi, and Qi Zhang, Journal of International Financial markets, Institutions and Money 76 (2022): 101460

We document that the carry trade performance has deteriorated dramatically after the 2008 financial crisis. We attribute the decline in carry performance to the disappearance of the downside risk in the post-crisis carry trade portfolio, rather than under-diversification, changing exposure to known risk factors, or decreased crash risks in currencies.