Robust Test for Detecting Changes in the Autocovariance Function of a Time Series

  • Alexander Dürre Université libre de Bruxelles
  • Roland Fried Technische Universität Dortmund

Abstract

We propose a new robust test to detect changes in the autocovariance function of a time series. The test is based on empirical autocovariances of a robust transformation of the original time series. Because of the transformation, we do not require any finite moments of the original time series, making the test especially suitable for heavy tailed time series. We furthermore propose a lag weighting scheme, which puts emphasis on changes of the autocovariance at smaller lags. Our approach is compared to existing ones in some simulations.

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Published
2020-04-13
How to Cite
Dürre, A., & Fried, R. (2020). Robust Test for Detecting Changes in the Autocovariance Function of a Time Series. Austrian Journal of Statistics, 49(4), 35-45. https://doi.org/10.17713/ajs.v49i4.1123
Section
Special Issue CDAM conference