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Variance Changes Detection In Multivariate Time Series

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  • Pedro Galeano

    ()

  • Daniel Peña

    ()

Abstract

This paper studies the detection of step changes in the variances and in the correlation structure of the components of a vector of time series. Two procedures are considered. The first is based on the likelihood ratio test and the second on cusum statistics. These two procedures are compared in a simulation study and we conclude that the cusum procedure is more powerful. The procedures are illustrated in two examples.R

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Paper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws041305.

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Date of creation: Feb 2004
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Handle: RePEc:cte:wsrepe:ws041305

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  1. B. Abraham & W. Wei, 1984. "Inferences about the parameters of a time series model with changing variance," Metrika, Springer, vol. 31(1), pages 183-194, December.
  2. D.S. Poskitt, . "Specification of echelon form VARMA models," Statistic und Oekonometrie 9305, Humboldt Universitaet Berlin.
  3. Booth, N.B. & Smith, A.F.M., 1982. "A Bayesian approach to retrospective identification of change-points," Journal of Econometrics, Elsevier, vol. 19(1), pages 7-22, May.
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Cited by:
  1. Ke-Li Xu & Peter C.B. Phillips, 2006. "Adaptive Estimation of Autoregressive Models with Time-Varying Variances," Cowles Foundation Discussion Papers 1585R, Cowles Foundation for Research in Economics, Yale University, revised Nov 2006.
  2. Dominik Wied & Matthias Arnold & Nicolai Bissantz & Daniel Ziggel, 2012. "A new fluctuation test for constant variances with applications to finance," Metrika, Springer, vol. 75(8), pages 1111-1127, November.

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