Modelling multiple time series via common factors

Pan, Jiazhu and Yao, Qiwei ORCID: 0000-0003-2065-8486 (2008) Modelling multiple time series via common factors. Biometrika, 95 (2). pp. 365-379. ISSN 0006-3444

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Abstract

We propose a new method for estimating common factors of multiple time series. One distinctive feature of the new approach is that it is applicable to some nonstationary time series. The unobservable, nonstationary factors are identified by expanding the white noise space step by step, thereby solving a high-dimensional optimization problem by several low-dimensional sub-problems. Asymptotic properties of the estimation are investigated. The proposed methodology is illustrated with both simulated and real datasets.

Item Type:	Article
Official URL:	http://biomet.oxfordjournals.org/
Additional Information:	© 2008 The Biometrika Trust
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics
Date Deposited:	18 Feb 2009 16:53
Last Modified:	20 Oct 2021 01:45
Funders:	U.K. Engineering and Physical Science Research Council, National Natural Science Foundation of China, NationalBasic Research Program of China
URI:	http://eprints.lse.ac.uk/id/eprint/22876

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