Department of Finance
Building & Room:
University Hall 2112
601 S. Morgan St., Chicago, IL 60607
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).
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
“The Observed Asymptotic Variance: Hard edges, and a regression approach”. Mykland, P.A., and Zhang, L. Journal of Econometrics, 222 (1), Part B, 411-428, May 2021.
“The Five Trolls Under the Bridge: Principal component analysis with asynchronous and noisy high frequency data.” Chen, D., Mykland, P.A. and Zhang, L. Journal of The American Statistical Association, 115(532), 1960-1977, 2020.
“The Algebra of Two Scales Estimation, and the S-TSRV: High Frequency Estimation that is Robust to Sampling Times.” Mykland, P.A., Zhang, L. and Chen, D. Journal of Econometrics, 208 (1), 101-119, 2019
“Assessment of uncertainty in high frequency data: The observed asymptotic variance.” Mykland, P.A. and Zhang, L. , Econometrica, 85 (1), 197-231, 2017.
Supplement to “Assessment of Uncertainty in High Frequency Data: The Observed Asymptotic Variance”. Mykland, P.A. and Zhang, L., Econometrica website, 2017.
“Between data cleaning and Inference: Pre-Averaging and other robust estimators of the efficient price.” Mykland, P.A. and Zhang, L., Journal of Econometrics, 194 (2), 242-262, 2016.
“Realized volatility when sampling times can be endogenous.” Li, Y., Mykland, P.A., Renault, E., Zhang, L. and Zheng, X., Econometric Theory, 30, 580-605, June 2014.
“Implied and realized volatility: Empirical model selection.” Zhang, L., Annals of Finance, 8 (2), 259-275, 2012.
“The econometrics of high frequency data.’ Mykland, P.A. and Zhang, L., Statistical Methods for Stochastic Differential Equations, M. Kessler, A. Lindner, and M. Sorensen, eds. Chapman & Hall/CRC Press, 109- 190, June 2012.
“The Double Gaussian Approximation for High Frequency Data.” Mykland, P.A., and Zhang, L., Scandinavian Journal of Statistics, 38 (2), 215-236, June 2011.
“Estimating covariation: Epps effect, microstructure noise.” Zhang, L., Journal of Econometrics, 160, 33-47, 2011
“Edgeworth expansions for realized volatility and related estimators.” Zhang, L., Mykland, P.A., and Ait-Sahalia, Y., Journal of Econometrics, 160, 190-203, 2011.
“Ultra high frequency volatility estimation with dependent microstructure noise.” Ait-Sahalia, Y., Mykland, P.A. and Zhang, L., Journal of Econometrics, 160, 160-175, 2011.
“Forecasting return volatility in the presence of microstructure noise.” Kang, Z.X., Zhang, L., and Chen, R., Statistics and Its Interface, 3 (2), 145-158, 2010.
“Inference for continuous semimartingales observed at high frequency.” Mykland, P.A. and Zhang, L., Econometrica, 77 (5), 1403-1445, 2009.
“Inference for Volatility-Type Objects and Implications for Hedging.” Mykland, P.A. and Zhang, L., Statistics and Its Interface, 1, 255-278, 2008.
“Efficient Estimation of Stochastic Volatility Using Noisy Observations: A Multi-Scale Approach.” Zhang, L, Bernoulli, 12 (6), 1019-1043, 2006.
“ANOVA for diffusions and Ito processes.” Mykland, P.A. and Zhang, L., Annals of Statistics, 34 (4), 1931-1963, 2006.
Comment on “Realized Variance and Market Microstructure Noise” by P.R. Hansen and A. Lunde. Ait-Sahalia, Y., Mykland, P.A. and Zhang, L. Journal of Business and Economic Statistics, 24 (2), 162-167, April 2006.
“A tale of two time scales: Determining integrated volatility with noisy high frequency data.” Zhang, L., Mykland, P.A. and Ait-Sahalia, Y. Journal of The American Statistical Association, 100 (472), 1394-1411, December 2005.
“Comment: A selective overview of nonparametric methods in financial econometrics.” Mykland, P.A. and Zhang, L. Statistical Science, 20 (4), 347-350, December 2005.
“How often to sample a continuous-time process in the presence of market microstructure noise.” Ait-Sahalia, Y., Mykland, P.A. and Zhang, L. Review of Financial Studies, 18, 351-416, April 2005.
“From Martingales to ANOVA: Implied and Realized Volatility,” Zhang, L. PhD dissertation, University of Chicago, June 2001.
“Trends in the vertical distribution of ozone: A comparison of two analyses of ozonesonde data.” Logan, JA, Megretskaia, IA, Miller, AJ, Tiao, GC, Choi, D, Zhang, L, Stolarski, RS, Labow, GJ, Hollandsworth, SM, Bodeker, GE, Claude, H, De Muer, D, Kerr, JB, Tarasick, DW, Oltmans, SJ, Johnson, B, Schmidlin, F, Staehelin, J, Viatte, P, Uchino, O, Journal of Geophysical Research – Atmospheres,104 (D21), 26373-26399, Nov 1999.
“Update of Umkehr ozone profile data trend analysis through 1997.” Reinsel, GC, Tiao, GC, Miller, AJ, Nagatani, RM, Wuebbles, DJ, Weatherhead, EC, Cheang, WK, Zhang L, Flynn, LE, Kerr, JB, Journal of Geophysical Research – Atmospheres, 104 (D19), 23881-23898, Oct 1999.
“Delay or probability discounting in a model of impulsive behavior: Effect of alcohol.” Richards, J, Zhang, L, Mitchell, S, and de Wit, H, Journal of the Experimental Analysis of Behavior, 71, 121-143, 1999.
“Requests and Subsequent Compliance in Infant-parent Interaction,” Zhang, L. Master thesis, Department of Psychology, University of Chicago, June 1995.
“Ability and development of facial expression recognition in infancy.” Wang L, Zhang L, Li L, Beijing Psychological Bulletin, 2 (2), 169-175, 1994.
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)
2016, Fellow, Society for Financial Econometric
University of Chicago, Ph.D. in Statistics, June 2001
Princeton University, Exchange Scholar Program, Bendheim Center for Finance (Department of Economics, Department of Operations Research & Financial Engineering, September 2000 - May 2001
University of Chicago, M.A. in Psychology, June 1995
Peking University, China, B.S. in Psychology, July 1992