Associate Professor Chuanhai Zhang, a researcher of the Base, has published a collaborative paper titled "Identifying latent factors based on high-frequency data" in Journal of Econometrics

Abstract:

This paper tests whether the continuous component of an observable candidate factor is in the space spanned by the counterparts of latent common factors with high-frequency financial data. We introduce two identification strategies corresponding to two types of regressions: the regressions of intraday asset returns on the estimated factors and the candidate, and the regression of the candidate factor on the estimated ones. We construct the test statistics by adding randomness to the statistics obtained from residuals of the regressions, and demonstrate the consistency of the novel randomized tests. Simulations are conducted to evaluate the performance of the tests in finite samples. We also perform empirical applications to identify the relationships between some candidate factors and the latent ones, and further use the factors selected by the tests for portfolio allocation.

Key Words: Factor model, High-dimensional data, High-frequency data, Randomized test, Jump

Link: Identifying latent factors based on high-frequency data - ScienceDirect

Teacher Profile

Chuanhai Zhang is a lecturer at the School of Finance, Zhongnan University of Economics and Law. His research interests include Financial Markets, Financial Measurement, Financial Risk Management, Fintech and Big Data. He has published nearly 10 articles in Economic Research Journal, Systems Engineering Theory and Practice, Journal of Econometrics, Quantitative Finance and Pacific-Basin Finance Journal. He has led and participated in many research projects of National Natural Science Foundation of China, National Social Science Foundation of China and Humanities and Social Science Research Foundation of Ministry of Education.