Optimized Segmentation-Adaptive-Based Testing of the Wavelet Co-movement Analysis: the Case of US and G8 Countries

The paper deals with the identification and the description of the co-movement between the US and G8 countries with regard to the impact of the structural change, i.e. the financial crisis in 2008. For the identification of the co-movement, we use an optimized segmentation-adaptive-based approach (SAB) of significance testing of the power wavelet cross-spectrum. The SAB testing is based on the standard testing for the power wavelet cross-spectrum adapted for the case if the data have several levels of volatility during the time evolution, i.e. the data can be split into several segments with different volatility. The number of segments is set by the heteroscedasticity test and the test for comparing variances in the segments of the time series. The SAB testing allows us to identify significant co-movement with respect to the local variance, which can reveal additional significant co-movement areas. We apply this approach to the monthly data of industrial production index for G8 countries in 1993-2017.