@article{d67e788426ef4d93a9b77f594f698260,
title = "Consistently determining the number of factors in multivariate volatility modelling",
abstract = "Consistently determining the number of factors plays an important role in factor modelling for volatility of multivariate time series. In this paper, the modelling is extended to handle the nonstationary time series scenario with conditional heteroscedasticity. Then a ridge-type ratio estimate and a BIC-type estimate are proposed and proved to be consistent. Their finite sample performance is examined through simulations and the analysis of two data sets. An observation from the numerical studies is, that unlike the cases with stationary and homoscedastic sequences in the literature, the dimensionality blessing no longer holds for the ratio-based estimates, but still does for the BIC-type estimate.",
keywords = "BIC-type criterion, Dimension reduction, Eigenanalysis, Factor modelling, Multivariate volatility, Nonstationarity, Ratio estimate",
author = "Qiang Xia and Wangli Xu and Lixing ZHU",
note = "Funding Information: The authors thank the editor, associate editor, and a referee for their constructive suggestions and comments that led to a significant improvement of an early version of the manuscript. Qiang Xia gratefully acknowledges the support of K.C.Wong Education Foundation, Hong Kong. He worked at College of Science, South China Agricultural University, he was also supported by the National Social Science Foundation of China (No:12CTJ019) and a Project of Humanities and Social Sciences (Project No.11YJCZH195) funded by Ministry of Education of China. Wangli Xu's research was supported by the National Natural Science Foundation of China (No. 11071253) and Beijing Nova Programme (2010B066). Lixing Zhu's research was supported by a grant from the University Grants Council of Hong Kong, China.",
year = "2015",
month = jul,
doi = "10.5705/ss.2013.252",
language = "English",
volume = "25",
pages = "1025--1044",
journal = "Statistica Sinica",
issn = "1017-0405",
publisher = "Institute of Statistical Science",
number = "3",
}