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Commodity futures and a wavelet-based risk assessment

Theo Berger and Robert Czudaj ()

Physica A: Statistical Mechanics and its Applications, 2020, vol. 554, issue C

Abstract: This paper provides an in-depth assessment of commodity futures on applied risk measurement. We provide a thorough empirical study on deconstructed commodity futures returns and present a novel wavelet-based portfolio strategy. First, we examine the dependence structure between commodity futures and show that it is described by different dependence regimes in the short-run, medium-run and long-run. Then, the out-of-sample portfolio study unveils that daily portfolio management is mostly driven by medium-run and long-run information. Furthermore, we also find that information inherent in long-run trends outperform the information included in short-run trends and this underlines the usefulness of the wavelet approach for portfolio management.

Keywords: Commodity futures; Portfolio management; Risk measurement; Minimum variance; Wavelet decomposition (search for similar items in EconPapers)
JEL-codes: C58 G17 Q47 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:554:y:2020:i:c:s037843712030114x

DOI: 10.1016/j.physa.2020.124339

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Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

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