基地研究员张传海博士与首都经济贸易大学国际经济管理学院孙宇澄副教授、许文副教授合作的题为《Identifying latent factors based on high-frequency data》的论文在计量经济学权威刊物《Journal of Econometrics》上在线发表。

《Journal of Econometrics》是学界公认的计量经济学国际顶级期刊，近5年的期刊影响因子为3.513，JCR类别Q2分区，ABS四星期刊。

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.

论文链接：Identifying latent factors based on high-frequency data - ScienceDirect

教师简介

张传海，现任中南财经政法大学金融学院讲师。研究兴趣主要包括金融市场，金融计量，金融风险管理，金融科技和大数据等。在《经济研究》，《系统工程理论与实践》，《Journal of Econometrics》，《Quantitative Finance》以及《Pacific-Basin Finance Journal》等国内外期刊上发表文章近10篇。主持并参与多项国家自然科学基金、国家社会科学基金以及教育部人文社会科学研究基金等研究项目。