Research

My research lies at the intersection of finance, business analytics, and financial technology (fintech). I develop data-driven and machine learning-based methods to study financial markets, macroeconomic and financial uncertainty, ESG and climate risk, as well as energy and commodity markets. My work integrates high-frequency financial data, textual analysis, and econometric modeling to improve forecasting accuracy and to better understand risk transmission across financial and real sectors.

Publications

1. "Macroeconomic and Financial Mixed Frequency Factors in a Big Data Environment", with Norman Swanson, Xiye Yang, and Chun Yao, Journal of the Royal Statistical Society, Series C (Applied Statistics), 2024, 73(3), 682–714. (ABS3, ABDC:A)

2. "Assessing the Volatility of Green Firms", with Lorán Chollete, Keener Hughen, and Ching-Chil Lu, Finance Research Letters, 2024, 64, 105372. (ABS2, ABDC:A)

3. "Sector-level Equity Returns Predictability with Machine Learning and Market Contagion Measure", with Chun Yao, Empirical Economics, 2023, 65, 1761–1798. (ABS2, ABDC: A)

4. "Co-jumps, Co-jump Tests and Sector Level S&P 500 Volatility Prediction: Monte Carlo and Empirical Evidence", with Chun Yao, Journal of Risk
and Financial Management, 2022, 15(8), 334. (ABDC: B). Best Doctoral Student Paper Award in Financial Markets, Southwestern Finance Association conference, 2018.

5. "Does Introducing Futures Markets Affect Currency Variance Forecasts? Evidence from Asian Markets", with Lorán Chollete, W. Keener Hughen and Teresa Starzecki, Eastern Economic Journal, 2025, 51, 627–654. (ABS1, ABDC: B)

6. “Financial Econometrics and Big Data: A Survey of Volatility Estimators and Tests for the Presence of Jumps and Co-jumps”, with Arpita Mukherjee, Norman R. Swanson and Xiye Yang, Handbook of Statistics, 2020, 42, 3-59, edited by C.R. Rao and H.D. Vinod, Elsevier.

7. "The Analysis of Tax Evasion of Private Companies Based on Static Game Theory Model", 2013, 当代经济, 22, 160-161. (in Chinese)

Selected Working Papers

8. "Forecasting Realized Volatility of Shanghai Oil Futures with Mix-Frequency Uncertainty Factors", with Bo Yu, Chun Yao and Wei Lan, 2025. 2nd round R&R at Pacific-Basin Finance Journal. (ABS2, ABDC: A)

9. "Forecasting Volatility of Currencies and Oil with Brown Firms: A Mixed-Frequency Approach", with Lorán Chollete, Keener Hughen, and Ching-Chil Lu, 2025.

10. "Forecasting Realized Volatility with Idiosyncratic and Systemic Jump Risk: A Machine Learning Approach with Market Regimes", with Eman Abdelfattah, 2025.

11. "Biodiversity Risks and Foreign Direct Investment", with Sunnie Wu, Loran Chollate, Mahfuja Malik and Bo Yu, 2025.

12. "Forecasting Oil Market Volatility with Signed Marked Jump Intensity, Regime Switching, and Machine Learning", with Bo Yu and Dayong Zhang, 2025.

13. ”Temporal Window Flattening with Autoencoder Compression: A New Framework for Cross-Frequency Equity Return Forecasting”, with Chun Yao and Norman Swanson, 2025. (work in progress)

14. “Estimating Strategic Spillover Effects in Environmental Regulation: A Spatial GMM Approach,” with Loran Lorán and Mahfuja Malik. (work in progress)

15. “From Climate Beta to Systemic Transition Risk: Spillovers between Green and Brown Firms under Policy Uncertainty,” with Yan (Wendy) Wu and Jinghua (Carolyn) Wang. (work in progress)

16. “A Hybrid Spatial-Temporal Graph Attention Network for Forecasting Multivariate Realized Volatility”, with Bo Yu. (work in progress)