Time-frequency co-movements between commodities and global economic policy uncertainty across different crises.

M Bel��n Arouxet, Aurelio F Bariviera, Ver��nica E Pastor, Victoria Vampa
Author Information
  1. M Bel��n Arouxet: Universidad Nacional de La Plata, Facultad de Ciencias Exactas, Centro de Matem��tica de La Plata, Argentina.
  2. Aurelio F Bariviera: Universitat Rovira i Virgili, Department of Business, ECO-SOS, Av. Universitat 1, 43204 Reus, Spain.
  3. Ver��nica E Pastor: Universidad de Buenos Aires, Facultad de Ingenier��a, Departamento de Matem��ticas, Argentina.
  4. Victoria Vampa: Universidad Nacional de La Plata, Facultad de Ingenier��a, Departamento de Ciencias B��sicas, Argentina.

Abstract

Commodity futures constitute an attractive asset class for portfolio managers. Propelled by their low correlation with other assets, commodities begin gaining popularity among investors, as they allow to capture diversification benefits. This comprehensive study examines the time and frequency spillovers between the Economic Policy Uncertainty [1] and a broad set of commodities encompassing ferrous, non-ferrous, and precious metals, food, and energy commodities over a period from December 1997 to April 2022, which includes various political, economic and health crises. The novelty of this research lies in its extensive temporal and categorical coverage, providing an understanding of how different types of commodities respond to various crises. Furthermore, our study breaks new ground by employing wavelet analysis to gain detailed insights in both time and frequency domains in the financial time series of interest, providing a deeper understanding of the co-movements and lead-lag relationships. Specifically, we introduce the Cross Wavelet Transform (XWT) and Wavelet Coherence (WTC) analysis. Our findings demonstrate that not all crises uniformly impact commodities. Notably, during the global financial crisis and the COVID-19 pandemic, co-movements between commodities became significantly stronger. These results highlight the heterogeneity within the commodity asset class, where individual commodities exhibit diverse underlying dynamics. Importantly, the proposed methodology facilitates the extraction of robust results even when dealing with nonlinearities and nonstationary time series data. Consequently, our work offers valuable insights for policymakers (including regulatory bodies), investors, and fund managers.

Keywords

References

  1. Financ Res Lett. 2020 Nov;37:101783 [PMID: 33013239]
  2. Resour Policy. 2021 Mar;70:101898 [PMID: 34173426]
  3. Environ Sci Pollut Res Int. 2023 Mar;30(13):37157-37173 [PMID: 36571690]
  4. Int Rev Financ Anal. 2020 Jul;70:101496 [PMID: 38620230]

Word Cloud

Created with Highcharts 10.0.0commoditiestimecrisesanalysisco-movementsWaveletassetclassmanagersinvestorsstudyfrequencyEconomicvariouseconomicprovidingunderstandingdifferentinsightsfinancialseriesglobalresultspolicyuncertaintyCommodityfuturesconstituteattractiveportfolioPropelledlowcorrelationassetsbegingainingpopularityamongallowcapturediversificationbenefitscomprehensiveexaminesspilloversPolicyUncertainty[1]broadsetencompassingferrousnon-ferrouspreciousmetalsfoodenergyperiodDecember1997April2022includespoliticalhealthnoveltyresearchliesextensivetemporalcategoricalcoveragetypesrespondFurthermorebreaksnewgroundemployingwaveletgaindetaileddomainsinterestdeeperlead-lagrelationshipsSpecificallyintroduceCrossTransformXWTCoherenceWTCfindingsdemonstrateuniformlyimpactNotablycrisisCOVID-19pandemicbecamesignificantlystrongerhighlightheterogeneitywithincommodityindividualexhibitdiverseunderlyingdynamicsImportantlyproposedmethodologyfacilitatesextractionrobustevendealingnonlinearitiesnonstationarydataConsequentlyworkoffersvaluablepolicymakersincludingregulatorybodiesfundTime-frequencyacrossCommoditiesConnectedness

Similar Articles

Cited By

No available data.