Monitoring procedures for strict stationarity based on the multivariate characteristic function

Abstract

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. (C) 2021 Elsevier Inc.

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Keywords

• Block bootstrap
• Change-point
• Empirical characteristic function
• Strict stationarity