Publications:
- Jiang Binyan, Liu, Cheng*, and Tang Cheng Yong (2022), Dynamic covariance matrix estimation and portfolio analysis with high-frequency data. Journal of Financial Econometrics, forthcoming. DOI:https://doi.org/10.1093/jjfinec/nbad003
- Chang Jinyuan*, Hu Qiao, Liu Cheng and Tang Cheng Yong (2022), Optimal covariance matrix estimation for high-dimensional noise in high frequency data. Journal of Econometrics,DOI: https://doi.org/10.1016/j.jeconom.2022.06.010.
- Kong Xin-Bing, Lin Jin-Guan, Liu Cheng* and Liu Guang-Ying (2021), Discrepancy between global and local principal component analysis on large-panel high-frequency data. Journal of the American Statistical Association, DOI: https://doi.org/10.1080/01621459.2021.1996376
- Liu, Cheng, Wang Moming, and Xia Ningning (2022), Design-free estimation of integrated covariance matrices for high-frequency data. Journal of Multivariate Analysis, Volume 189, 1-14.
DOI: https://doi.org/10.1016/j.jmva.2021.104910 - Liu, Cheng and Sun, Yixiao. A Simple and Trustworthy Asymptotic t Test in Difference-in-Differences Regressions. Journal of Econometrics,2019, 210: 327-362.
- Kong Xin-Bing and Liu, Cheng*, Test against constant factor loading matrix with large panel high-frequency data, Journal of Econometrics, 2018, 204: 301-319.
- Liu, Cheng and Tang, Cheng Yong, A quasi-maximum likelihood approach for integrated covariance matrix estimation with high frequency data, Journal of Econometrics, 2014, 180: 217-232.
- Liu, Cheng and Tang, Cheng Yong, A state space model approach to integrated covariance matrix estimation with high frequency data, Statistics and Its Interface (SCI), 2013, 6: 463-475.
- 刘成,罗金斗,罗知 (2022),高频数据下积分波动率矩阵的伪似然估计、预测及应用,《数量经济技术经济研究》,第3期。