Document Type
Journal Article
Department/Unit
Department of Mathematics
Title
Consistently determining the number of factors in multivariate volatility modelling
Language
English
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
Publication Date
2015
Source Publication Title
Statistica Sinica
Volume
25
Issue
3
Start Page
1025
End Page
1044
Publisher
Academia Sinica, Institute of Statistical Science
DOI
10.5705/ss.2013.252
Link to Publisher's Edition
http://dx.doi.org/10.5705/ss.2013.252
ISSN (print)
10170405
ISSN (electronic)
19968507
APA Citation
Xia, Q., Xu, W., & Zhu, L. (2015). Consistently determining the number of factors in multivariate volatility modelling. Statistica Sinica, 25 (3), 1025-1044. https://doi.org/10.5705/ss.2013.252