Name: Liu Qiang
Title: Assistant Professor
Research Direction: High-frequency high-dimensional financial econometrics, statistical machine learning, and its applications in financial economics
Courses Taught:
E - mail：liuqiang@mail.shufe.edu.cn
Phone: 65906889
Research Project
Serial Number | Project Name | Start and End Time |
1 | Regarding the Statistical Inference Problem of Instantaneous Volatility of High-Frequency Data | 2021.07.01 -2024.07.01 |
2 | Statistical Machine Learning in the Application of Financial High-Frequency Data | 2022.10.1 -2025.9.30 |
3 | Statistical Inference of Instantaneous Volatility Matrix of High-Frequency Data and Its Application Research | 2026.1.1 -2029.1.1 |
Research Field
Financial Econometrics, Statistical Machine Learning
Education Background
2015.8—2018.6 University of Macau, Department of Mathematics, PhD
2013.8—2015.6 University of Macau, Department of Mathematics, Master's Degree
2009.9—2013.7 Lanzhou University, School of Mathematics and Statistics, Bachelor’s Degree
Work Experience
2021.7—Present Shanghai University of Finance and Economics, School of Statistics and Management, Assistant Professor
2018.7—2021.6 National University of Singapore, Department of Mathematics, Postdoctoral Researcher
Publication:
1.Hong, S., Li, W.*, Liu, Q. and Zhang, Y. (in alphabetical order) “An adaptive adjustment to the R2 statistic in high-dimensional elliptical models”, Journal of the American Statistical Association，2024+.
2.Liu, Q., and Liu, Z.* “Estimating spot volatility under infinite variation jumps with dependent market structure noise”, Econometrics Journal, 27:278-298, 2024.
3.He, L.*, Liu, Q., Liu, Z. and Bucci, A. “Correcting spot power variation estimator via Edgeworth expansion”, Metrika, 87:921-945, 2023.
4.Liu, Q., and Liu, Z.* “Statistical inference of spot correlation and spot market beta under infinite variation jumps”, Journal of Financial Econometrics, 20:612-654, 2022.
5.Chen, X., Liu, Q., and Tong X. (in alphabetical order)“Dimension independent excess risk by stochastic gradient descent”, Electronic Journal of Statistics, 16:4547-4603, 2022.
6.Liu, Q., Liu, Z.* and Zhang C. “Heteroscedasticity test of high-frequency data with jumps and microstructure noise”, Applied Stochastic Models in Business and Industry, 38:441-457, 2022.
7.Zhang C.*, Liu, Z., and Liu, Q. “Jumps at ultra-high frequency: Evidence from the Chinese stock market”, Pacific-Basin Finance Journal, 68:101420, 2021.
8.Liu, Q.*, and Tong, X. “Accelerating Metropolis-within-Gibbs sampler with localized computations of differential equations”, Statistics and Computing, 30:1037-1056, 2020.
9.He, L., Liu, Q.*, and Liu, Z. “Edgeworth corrections for spot volatility estimator”, Statistics and Probability Letters, 164: 108809, 2020.
10.Liu, Q., Liu, Y., and Liu, Z.* “Estimating spot volatility in the presence of infinite variation jumps”, Stochastic Processes and their Applications, 128:1958-1987, 2018.
11.Liu, Q., Liu, Y.*, Liu, Z., and Wang, L. “Estimation of spot volatility with superposed noisy data”, The North American Journal of Economics and Finance, 44:61-79, 2018.
12.Liu, Y., Liu, Q.*, Liu, Z., and Ding, D. “Determining the integrated volatility via limit order books with multiple records”, Quantitative Finance, 17(11):1697-1714, 2017.
