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Monitoring procedures for strict stationarity based on the multivariate characteristic function. (English) Zbl 1520.62110

Summary: We consider model-free monitoring procedures for strict stationarity of a given time series. The new criteria are formulated as L2-type statistics incorporating the multivariate empirical characteristic function. Asymptotic results are obtained for the closed-end scenario and Monte Carlo results are presented. The new methods are also employed in order to test for possible stationarity breaks in time-series data from the financial sector.

MSC:

62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62G10 Nonparametric hypothesis testing
62G20 Asymptotic properties of nonparametric inference
62H15 Hypothesis testing in multivariate analysis
62M07 Non-Markovian processes: hypothesis testing
62G09 Nonparametric statistical resampling methods
62P05 Applications of statistics to actuarial sciences and financial mathematics

Software:

fda (R); CAViaR
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Full Text: DOI

References:

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