Academic Report of School of Mathematical Sciences [2026] No. 083

(Series Report for High-Level University Construction No. 1342)

Title：When Asynchronicity Meets Price Staleness: Robust Estimation of High-Frequency Covariance

Speaker：Assistant Professor Zhu Haibin (Jinan University)

Time：15:30-16:30, Sept. 12, 2026

Location：Conference Room 305, Alumni Plaza

Abstract: The existing literature has demonstrated that both asynchronicity and price staleness yield a downward bias in covariance estimation, a phenomenon known as the Epps effect. In this study, we propose a novel estimator of high-frequency covariance resilient to the concurrent presence of asynchronicity and price staleness. We establish the asymptotic properties of the proposed estimator and present a feasible central limit theorem that accounts for time-varying staleness probabilities. The proposed robust covariance estimator also yields consistent estimators for beta and correlation in the presence of these anomalies. Additionally, we adopt a preaveraging method to address microstructure noise. Through theoretical analysis and Monte Carlo simulations, we demonstrate that our estimator significantly outperforms existing alternatives. Empirically, using tick data, we evaluate the performance of ETF tracking across various covariance estimators. The results highlight the superiority and robustness of our proposed estimator.
Speaker Profile：Zhu Haibin is an assistant professor in the Department of Statistics and Data Science at Jinan University. He earned his Ph.D. from the Department of Mathematics at the University of Macau. His research focuses on high-frequency financial econometrics, financial machine learning, statistical inference for stochastic processes, and bioinformatics. His research findings have been published in statistical and financial journals such as the Journal of Business & Economic Statistics and the Journal of Empirical Finance, as well as in bioinformatics journals including BMC Bioinformatics and PLoS Computational Biology. He is the principal investigator of a National Natural Science Foundation of China (NSFC) Young Scientist Program grant. He currently serves as a council member of the Big Data Statistics Branch, the Random Matrix Theory and Applications Branch, and the Tourism Big Data Branch of the Chinese Society of Field Statistics, as well as Deputy Secretary-General of the Tourism Big Data Branch.

Faculty and students are welcome to attend!

Invited by: Wang Jiangzhou

School of Mathematical Sciences

September 7, 2026