Variance Changes Detection In Multivariate Time Series
AbstractThis 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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Bibliographic InfoPaper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws041305.
Date of creation: Feb 2004
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-03-07 (All new papers)
- NEP-ECM-2004-03-07 (Econometrics)
- NEP-ETS-2004-03-07 (Econometric Time Series)
- NEP-RMG-2004-03-07 (Risk Management)
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