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Titel
Testing semiparametric hypotheses in locally stationary processes / Philip Preuß, Mathias Vetter, Holger Dette
VerfasserPreuß, Philip ; Vetter, Mathias ; Dette, Holger
Erschienen[Dortmund] : SFB 823, 2011
Ausgabe
Elektronische Ressource
Umfang1 Online-Ressource (25 Seiten) : Diagramme
SerieDiscussion paper ; Nr. 13 (2011)
SchlagwörterStationärer Prozess / Semiparametrisches Modell / Bootstrap-Statistik
URNurn:nbn:de:hbz:6:2-1311727 
DOI10.17877/DE290R-13401 
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Testing semiparametric hypotheses in locally stationary processes [0.43 mb]
Zusammenfassung

In this paper we investigate the problem of testing semi parametric hypotheses in locally stationary processes. The proposed method is based on an empirical version of the L2-distance between the true time varying spectral density and its best approximation under the null hypothesis. As this approach only requires estimation of integrals of the time varying spectral density and its square, we do not have to choose a smoothing bandwidth for the local estimation of the spectral density - in contrast to most other procedures discussed in the literature. Asymptotic normality of the test statistic is derived both under the null hypothesis and the alternative. We also propose a bootstrap procedure to obtain critical values in the case of small sample sizes. Additionally, we investigate the finite sample properties of the new method and compare it with the currently available procedures by means of a simulation study. Finally, we illustrate the performance of the new test in a data example investigating log returns of the S&P 500.

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