ITM Web Conf.
Volume 24, 2019AMCSE 2018 - International Conference on Applied Mathematics, Computational Science and Systems Engineering
|Number of page(s)||7|
|Published online||01 February 2019|
Optimized Segmentation-Adaptive-Based Testing of the Wavelet Co-movement Analysis: the Case of US and G8 Countries
Brno University of Technology, Faculty of Electrical Engineering and Communication, Technická 12, 616 00 Brno, Czech Republic
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.
© The Authors, published by EDP Sciences, 2019
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