Name: Xia Ningning
Title: Associate Professor
Research Areas: High-dimensional random matrix analysis, high-frequency financial data analysis
Courses Taught: Mathematical Analysis, Functional Analysis, Multivariate Statistical Analysis, Financial Time Series, Advanced Probability Theory, Stochastic Processes, Data Analysis and Statistical Modeling
E - mail: xia.ningning@mail.shufe.edu.cn; Phone: 65904185
Research Project
研究项目
Serial Number | Project Name | Project Number | Project Source | Start and End Time | Project Funding |
1 | Theoretical Research and Application of High-Dimensional Random Matrices in Factor Models | 11871322 | National Surface Projects | 2019-2022 Years | 520,000 |
2 | Statistical Analysis of Financial Asset Integral Volatility Matrix under High-Dimensional High-Frequency Data | 11501348 | National Natural Science Foundation | 2016-2018 Years | 180,000 |
3 | Limit Analysis of Eigenvectors of High-Dimensional Random Matrices | 15PJ1402300 | Shanghai Pujiang Talent Program | 2015-2017 Year | 200,000 |
Research Field
Random Matrix Theory and Its Applications, High-Dimensional Data Statistical Analysis, High-Frequency Financial Data Analysis, etc.
Education Experience
2009-2013 Year National University of Singapore, PhD
Work Experience
2013-2014, Hong Kong University of Science and Technology, Postdoctoral.
2014 - Present, School of Statistics and Data Science, Shanghai University of Finance and Economics.
·Fan, Jianqing, Li, Yingying, Xia, Ningning, Zheng, Xinghua (2025). Tests for principal eigenvalues and eigenvectors. Submitted.
·Xia, Ningning, Yu, Wenxin, Zheng, Shurong (2025). Testing high-dimensional spatial sign covariance matrices based on the eigenvector empirical spectral distribution. Submitted.
·Xia, Ningning, Xu, Yangchang, Yao, Jianfeng, Yu, Wenxin, Zheng, Shurong (2025). Two-sample hypothesis testing under generalized elliptical distributions: applications in high-frequency financial data. Submitted.
·Deng, Yibo, Xia, Ningning, Yu, Wenxin, Zheng, Shurong (2025). High-dimensional eigenvector spectral analysis on sample covariance matrices: a joint CLT framework, asymptotic independence from eigenvalues, and applications. Submitted.
·Wang, Moming, Xia, Ningning, Yu, Wenxin (2025). Nonlinear shrinkage estimation of high-dimensional covariance matrix under the elliptical distribution. Submitted.
·Wang, Moming, Xia, Ningning, Zhou, Yong (2025). Limiting spectral distribution of high-dimensional integrated covariance matrices based on high-frequency data with multiple transactions. Journal of Multivariate Analysis (Accepted).
·Wang, Moming, Hu, Jianhua, Xia, Ningning, Zhou, Yong (2025). On the estimation of high-dimensional integrated covariance matrix based on high-frequency data with multiple transactions. Statistica Sinica 35 (2025), 1737-1757.
·Xu, Yangchang, Xia, Ningning (2023). On the eigenvectors of large-dimensional sample spatial sign covariance matrices. Journal of Multivariate Analysis 193(2023) 105119.
·Liu, Cheng, Wang, Moming, Xia, Ningning (2022). Design-free estimation of integrated covariance matrices for high-frequency data. Journal of Multivariate Analysis 189 (2022) 104910.
·Hu, Jianhua, Liu, Xiaoqian, Liu, Xu, Xia, Ningning (2022). Some aspects of response variable selection and estimation in multivariate linear regression. Journal of Multivariate Analysis 188 (2022) 104821.
·Wang, Moming, Xia, Ningning (2021). Estimation of high-dimensional integrated covariance matrix based on high-frequency data with multiple observations. Statistics and Probability Letters 170 (2021) 108996.
·Xia, Ningning, Bai, Zhidong (2019). Convergence rate of eigenvector empirical spectral distribution of large Wigner matrices. Statistical Papers (2019) 60: 983-1015.
·Xia, Ningning, Zheng, Xinghua (2018). On the inference about the spectral distribution of high-dimensional covariance matrix based on high-frequency noisy observations. The Annals of Statistics, 2018, 46(2), 500-525.
·Xia, Ningning, Bai, Zhidong (2015). Functional CLT of eigenvectors for large sample covariance matrices. Statistical Papers (2015) 56:23-60.
·Xia, Ningning, Qin, Yingli, Bai, Zhidong (2013). Convergence rates of eigenvector empirical spectral distribution of large dimensional sample covariance matrix. The Annals of Statistics, 2013, 41(5), 2572-2607.
Rewards, Honors
· Shanghai Pujiang Talent (2015-2017)
· Third prize in the first Young Teacher Teaching Competition at Shanghai University of Finance and Economics in the Science and Engineering group.
Social Work
·Advances in Decision Sciences (ADS) Editorial Board
· Director of the Big Data Statistics Branch of the China Society for Statistics
· Council member of the Random Matrix Theory and Applications Branch of the Chinese Statistical Research Association
· National Expert for Graduate Education Evaluation and Monitoring
Academic Reports (Since 2008)
The Society for Financial Econometrics (SoFiE), NYU, June 20-23, 2017, New York University (USA).
1st International Conference on Econometrics and Statistics (EcoSta 2017), HKUST, June 15-17, 2017, Hong Kong University of Science and Technology.
The 2017 China Meeting of the Econometric Society in Wuhan. June 9-11, 2017, Wuhan.
The 10th ICSA International Conference on Global Growth of Modern Statistics in the 21st Century. December 19-22, 2016, Shanghai Jiao Tong University.
2016 "Big Data Financial Measurement and Statistical Learning Theory and Methods" Seminar, August 23-25, 2016, Beihai, Guangxi.
Guangzhou 2016 Symposium on Financial Engineering and Risk Management (FERM), June 12-13, 2016, Sun Yat-sen University, Guangzhou.
Workshop on high frequency data, network data and related fields, June 3-5, 2016, Nanjing Audit University.
Workshop of Math Finance and Financial Data Processing, April 29-30, 2016, Suzhou University.
Central China Normal University Youth Statistics Forum, April 9-10, 2016, Central China Normal University (Wuhan).
2015 Symposia on Methodologies for Analyzing Big Data and their Applications (2015 Big Data Analysis Methods and Applications Symposium) September 19-20, 2015, Xi'an Jiaotong University.
