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Modelling multiple time series via common factors

Pan, Jiazhu and Yao, Qiwei (2008) Modelling multiple time series via common factors. Biometrika, 95 (2). pp. 365-379. ISSN 1464-3510

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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 via expanding the white noise space step by step; therefore solving a high-dimensional optimization problem by several low-dimensional subproblems. Asymptotic properties of the estimation were investigated. The proposed methodology was illustrated with both simulated and real data sets.

    Item type: Article
    ID code: 13677
    Keywords: factor models, cross-correlation functions, dimension reduction, multivariate time series, non stationarity, portmanteau tests, white noise, Mathematics
    Subjects: Science > Mathematics
    Department: Faculty of Science > Mathematics and Statistics
    Related URLs:
      Depositing user: Mrs Carolynne Westwood
      Date Deposited: 12 Jan 2010 15:22
      Last modified: 11 Oct 2012 22:55
      URI: http://strathprints.strath.ac.uk/id/eprint/13677

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