Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis
AbstractIn this paper, we contribute to the literature on energy market co-movement by studying its dynamics in the time-frequency domain. The novelty of our approach lies in the application of wavelet tools to commodity market data. A major part of economic time series analysis is done in the time or frequency domain separately. Wavelet analysis combines these two fundamental approaches allowing study of the time series in the time-frequency domain. Using this framework, we propose a new, model-free way of estimating time-varying correlations. In the empirical analysis, we connect our approach to the dynamic conditional correlation approach of Engle (2002) on the main components of the energy sector. Namely, we use crude oil, gasoline, heating oil, and natural gas on a nearest-future basis over a period of approximately 16 and 1/2years beginning on November 1, 1993 and ending on July 21, 2010. Using wavelet coherence, we uncover interesting dynamics of correlations between energy commodities in the time-frequency space.
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Bibliographic InfoArticle provided by Elsevier in its journal Energy Economics.
Volume (Year): 34 (2012)
Issue (Month): 1 ()
Contact details of provider:
Web page: http://www.elsevier.com/locate/eneco
Correlation; Co-movement; Wavelet analysis; Wavelet coherence;
Other versions of this item:
- Lukas Vacha & Jozef Barunik, 2012. "Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis," Papers 1201.4776, arXiv.org.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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2004.72, Fondazione Eni Enrico Mattei.
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