معرفی
Dacheng Xiu is the Joseph Sondheimer Professor of Econometrics and Statistics at the University of Chicago's Booth School of Business, with additional affiliation to the Department of Statistics. He serves as a Research Associate at the National Bureau of Economic Research.
His research focuses on developing statistical methodologies and their applications to financial data, with current emphasis on machine learning solutions for big-data problems in empirical asset pricing. His earlier work involved risk measurement and portfolio management with high-frequency data and econometric modeling of derivatives.
Xiu's research interests span Financial Econometrics, Statistics, Empirical Asset Pricing, and Quantitative Finance, with increasing integration of Machine Learning and AI techniques. His work demonstrates how statistical methods can extract meaningful economic signals from complex financial datasets, particularly through the application of machine learning to asset pricing problems.
His publications reveal a strong trend toward integrating machine learning with traditional financial econometrics, with recent papers focusing on text data analysis, image recognition applications to financial markets, and sophisticated factor modeling approaches. The research shows progression from traditional volatility modeling to cutting-edge applications of deep learning and natural language processing in finance.
- Fellow of the Society for Financial Econometrics
- Fellow of the Journal of Econometrics
- Swiss Finance Institute Outstanding Paper Award
- AQR Insight Award
- Dimensional Fund Advisors Prize
- Bates-White Prize
- Best Conference Paper Prize at the 44th EFA
- Poets & Quants' Best 40-under-40 Business School Professors
Xiu serves as Co-Editor of Journal of Business & Economic Statistics and Journal of Financial Econometrics, and as Associate Editor for prestigious journals including Journal of Finance, Review of Financial Studies, Journal of the American Statistical Association, Management Science, and Journal of Econometrics. His Risk Lab provides up-to-date daily annualized realized volatilities for individual stocks, ETFs, and future contracts, estimated from high-frequency data, demonstrating practical applications of his methodological research.
