ITM Web Conf.
Volume 16, 2018AMCSE 2017 - International Conference on Applied Mathematics, Computational Science and Systems Engineering
|Number of page(s)||5|
|Published online||09 January 2018|
Wavelet Co-movement Significance Testing with Respect to Gaussian White Noise Background
Brno University of Technology, Faculty of Electrical Engineering and Communication, Technická 12, 616 00 Brno, Czech Republic
* Corresponding author: email@example.com
The paper deals with significance testing of time series co-movement measured via wavelet analysis, namely via the wavelet cross-spectra. This technique is very popular for its better time resolution compare to other techniques. Such approach put in evidence the existence of both long-run and short-run co-movement. In order to have better predictive power it is suitable to support and validate obtained results via some testing approach. We investigate the test of wavelet power cross-spectrum with respect to the Gaussian white noise background with the use of the Bessel function. Our experiment is performed on real data, i.e. seasonally adjusted quarterly data of gross domestic product of the United Kingdom, Korea and G7 countries. To validate the test results we perform Monte Carlo simulation. We describe the advantages and disadvantages of both approaches and formulate recommendations for its using.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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