Dynamic interdependence of industrial metal price returns: Evidence from wavelet multiple correlations

George Tweneboah

Physica A: Statistical Mechanics and its Applications, 2019, vol. 527, issue C

Abstract: This study employs the recently developed wavelet multiple correlations and cross-correlations based on the maximal overlap discrete transform estimator popularized by Fernandez-Macho (2012) to investigate the interdependence and spill-over linkages among six industrial metals for the period January 2000 to June 2018. We establish that the structure of interdependence in industrial metals markets has been non-homogeneous across timescales. From the wavelet multiple cross-correlations analysis, there is evidence of intense and positive degree of integration at all frequencies in the period up to the 2008 global financial crisis and the period after. It was further revealed that, in the period up to December 2010, copper assumes the potential to act as market leader in all wavelet scales except one, which is led by aluminium. In the post-crisis era, zinc emerges as the potential market leader in all wavelet scales except at the lowest scale, led by copper. By considering the pattern of correlation among industrial metals at different timescales and investment horizons, our results highlight important implications for policy, portfolio diversification, and risk management strategies.

Keywords: Market integration; Metals; Portfolio diversification; Spill-over linkages; Volatility transmission; Wavelet multiple correlations (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:527:y:2019:i:c:s0378437119306971

DOI: 10.1016/j.physa.2019.121153

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