Lan Zhang, PhD
Professor
Department of Finance
Contact
Building & Room:
UH 2112
Address:
601 S. Morgan St., Chicago, IL 60607
Email:
CV Link:
Related Sites:
About
Lan Zhang is Professor of Finance at the University of Illinois at Chicago. Her research focuses on big data in finance and high frequency financial econometrics. Lan Zhang has developed a number of inferential methods for high dimensional and high frequency financial data, including the two-scale and multi-scale realized volatility estimators (TSRV, MSRV) under market microstructure, as well as high frequency PCA.
Professor Zhang has published widely in leading journals including Econometrica, Review of Financial Studies, Journal of Econometrics, Journal of the American Statistical Association, Bernoulli, and Annals of Statistics. She is the co-editor for the Special Issue on "Big Data in Predictive Dynamic Econometric Modeling", Journal of Econometrics. She has also served as Associate Editor for the academic journals Statistics and Its Interface, Annals of Applied Statistics, and Econometric Theory. Her work on the interface between statistics and finance has received grants from the National Science Foundation (2002-2005, 2014-2017, 2017-2020), National Institute of Health (2003-2006), and Morgan Stanley Research Fund on Market Microstructure (2004-2005). Before joining UIC, Lan Zhang was an Assistant Professor (2001-2005) and Associate Professor (effective 2006) at Carnegie Mellon University. At UIC, She became a tenured Associate Professor in 2008 and Professor in 2010. She was Reader (2009-2010) at the University of Oxford, UK (Said School of Business, and Oxford Man Institute of Quantitative Finance), as well as fellow of St. Edmund Hall College. She was Visiting Professor at the University of Oslo (2016-2017).
Selected Grants
National Science Foundation, National Science Foundation grant DMS 20-15530 (2020-2023), "Statistical Inference for High Dimensional and High Frequency Data", Principal Investigator
National Science Foundation, National Science Foundation grant DMS 17-13118 (2017-2020), "Statistical Inference for High-Frequency Data", Principal Investigator
National Science Foundation, National Science Foundation grant DMS 14-07820 (2014-2017), "Better efficiency, better forecasting, better accuracy: A new light on the dependence structure in high frequency data", Principal Investigator
Selected Publications
Chen, D., Feng, L., Mykland, P.A., and Zhang, L. “High Dimensional Regression Coefficient Test with High Frequency Data.” Journal of Econometrics, vol. 254, Part A, 2026, p. 105812.
Chen, D., Mykland, P.A., and Zhang, L. “Realized Regression with Asynchronous and Noisy High Frequency Data.” Journal of Econometrics, vol. 239, no. 2, 2024, p. 105446.
Stoltenberg, E., Mykland, P.A., and Zhang, L. “A CLT for second difference estimators with an application to volatility and intensity.” Annals of Statistics, vol. 50, no. 4, 2022, pp. 2072-2095.
Chen, D., Mykland, P.A., and Zhang, L. “The Five Trolls Under the Bridge: Principal component analysis with asynchronous and noisy high frequency data.” Journal of the American Statistical Association, vol. 115, no. 532, 2020, pp. 1960-1977.
Mykland, P.A., Zhang, L., and Chen, D. “The Algebra of Two Scales Estimation, and the S-TSRV: High Frequency Estimation that is Robust to Sampling Times.” Journal of Econometrics, vol. 208, no. 1, 2019, pp. 101-119.
Mykland, P.A. and Zhang, L. “Assessment of uncertainty in high frequency data: The observed asymptotic variance.” Econometrica, vol. 85, no. 1, 2017, pp. 197-231.
Professional Leadership
Council Memeber (2019), Society for Financial Econometrics
Program Chair (July 2018 - June 2019), 12th Annual Conference of the Society for Financial Econometrics
Co-Organizer, Conference on Market Microstructure and High Frequency Data, Chicago (University of Chicago)
Notable Honors
2016, Fellow, Society for Financial Econometric
Education
PhD in Statistics- University of Chicago
Exchange Scholar Finance and Financial engineering- Princeton University
MA Psychology- University of Chicago
BS Psychology- Peking University
Professional Memberships
Institute of Mathematical Statistics (IMS) — Fellow
Society for Financial Econometrics (SoFiE) — Fellow; Council Member
Econometric Society
American Statistical Association (ASA)