Detecting changes in the dependence structure of a time series

Abstract

We propose a new robust test to detect changes in the dependence structure 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 autocorrelation at smaller lags. Our approach is compared to existing ones in some simulations.