Break detection in the covariance structure of multivariate time series models

Alexander Aue, Siegfried Hörmann, Lajos Horvath, Matthew Reimherr

Publikation: Beitrag in einer FachzeitschriftArtikel

Abstract

In this paper, we introduce an asymptotic test procedure to assess the stability of volatilities and cross-volatilites of linear and nonlinear multivariate time series models. The test is very flexible as it can be applied, for example, to many of the multivariate GARCH models established in the literature, and also works well in the case of high dimensionality of the underlying data. Since it is nonparametric, the procedure avoids the difficulties associated with parametric model selection, model fitting and parameter estimation. We provide the theoretical foundation for the test and demonstrate its applicability via a simulation study and an analysis of financial data. Extensions to multiple changes and the case of infinite fourth moments are also discussed.
Originalspracheenglisch
Seiten (von - bis)4046-4087
Seitenumfang42
FachzeitschriftThe annals of statistics
Jahrgang37
Ausgabenummer6B
PublikationsstatusVeröffentlicht - 2009

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