Do commodity markets catch a cold from stock markets? Modelling uncertainty spillovers using Google search trends and wavelet coherence

dc.contributor.authorSzczygielski, Jan Jakub
dc.contributor.authorCharteris, Ailie
dc.contributor.authorObojska, Lidia
dc.date.accessioned2024-03-26T09:06:34Z
dc.date.available2024-03-26T09:06:34Z
dc.date.issued2023-05
dc.descriptionDATA AVAILABILITY : Data will be made available on request.en_US
dc.description.abstractWe investigate stock market uncertainty spillovers to commodity markets using wavelet coherence and a general stock market-related Google search trends (GST)-based index to proxy for uncertainty. GST reflect stock market uncertainty over short-, medium- and long-term horizons. Periods of association between GST and the VIX, a widely used proxy for stock market uncertainty, coincide with economic, financial, and geopolitical events. The association between the VIX and GST has grown over time. In line with economic psychology, this implies that during times of heightened uncertainty investors increasingly search for stock market-related information. Our analysis further reveals that some commodities are more susceptible to uncertainty spillovers from stock markets, notably energy commodities. We demonstrate how GST may be used to isolate the impact of specific events and show that COVID-19 had a disproportionate impact on commodity price volatility. We also find that energy, livestock and precious metals are increasingly integrated with stock markets. Spillover analysis repeated using the VIX produces similar results and reflects information that is also reflected in GST, confirming an uncertainty narrative. The use of wavelet analysis and GST to proxy for general and event specific uncertainty offers an alternative perspective to traditional econometric approaches and may be of interest to econometricians, analysts, investors and researchers.en_US
dc.description.departmentFinancial Managementen_US
dc.description.librarianhj2024en_US
dc.description.sdgSDG-08:Decent work and economic growthen_US
dc.description.urihttps://www.elsevier.com/locate/irfaen_US
dc.identifier.citationSzczygielski, J.J., Charteris, A. & Obojska, L. 2023, 'Do commodity markets catch a cold from stock markets? Modelling uncertainty spillovers using Google search trends and wavelet coherence', International Review of Financial Analysis, vol. 87, art. 102304, pp. 1-19, doi : 10.1016/j.irfa.2022.102304.en_US
dc.identifier.issn1057-5219 (print)
dc.identifier.issn1873-8079 (online)
dc.identifier.other10.1016/j.irfa.2022.102304
dc.identifier.urihttp://hdl.handle.net/2263/95352
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2022 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license.en_US
dc.subjectGoogle search trends (GST)en_US
dc.subjectSpilloversen_US
dc.subjectRealised volatilityen_US
dc.subjectUncertaintyen_US
dc.subjectCommoditiesen_US
dc.subjectWavelet coherenceen_US
dc.subjectSDG-08: Decent work and economic growthen_US
dc.titleDo commodity markets catch a cold from stock markets? Modelling uncertainty spillovers using Google search trends and wavelet coherenceen_US
dc.typeArticleen_US

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