Multi-task forecasting of the realized volatilities of agricultural commodity prices

dc.contributor.authorGupta, Rangan
dc.contributor.authorPierdzioch, Christian
dc.contributor.emailrangan.gupta@up.ac.zaen_US
dc.date.accessioned2025-02-12T04:48:02Z
dc.date.available2025-02-12T04:48:02Z
dc.date.issued2024-09-23
dc.descriptionDATA AVAILABILITY : The data used to derive the results documented in this research are available from the authors upon reasonable request.en_US
dc.description.abstractMotivated by the comovement of realized volatilities (RVs) of agricultural commodity prices, we study whether multi-task forecasting algorithms improve the accuracy of out-of-sample forecasts of 15 agricultural commodities during the sample period from July 2015 to April 2023. We consider alternative multi-task stacking algorithms and variants of the multivariate Lasso estimator. We find evidence of in-sample predictability but scarce evidence that multi-task forecasting improves out-of-sample forecasts relative to a classic univariate heterogeneous autoregressive (HAR)-RV model. This lack of systematic evidence of out-of-sample forecasting gains is corroborated by extensive robustness checks, including an in-depth study of the quantiles of the distributions of the RVs and subsample periods that account for increases in the total spillovers among the RVs. We also study an extended model that features the RVs of energy commodities and precious metals, but our conclusions remain unaffected. Besides offering important lessons for future research, our results are interesting for financial market participants, who rely on accurate forecasts of RVs when solving portfolio optimization and derivatives pricing problems, and policymakers, who need accurate forecasts of RVs when designing policies to mitigate the potential adverse effects of a rise in the RVs of agricultural commodity prices and the concomitant economic and political uncertainty.en_US
dc.description.departmentEconomicsen_US
dc.description.librarianam2024en_US
dc.description.sdgSDG-02:Zero Hungeren_US
dc.description.sdgSDG-08:Decent work and economic growthen_US
dc.description.urihttps://www.mdpi.com/journal/mathematicsen_US
dc.identifier.citationGupta, R.; Pierdzioch, C. Multi-Task Forecasting of the Realized Volatilities of Agricultural Commodity Prices. Mathematics 2024, 12, 2952. https://DOI.org/10.3390/math12182952.en_US
dc.identifier.issn2227-7390
dc.identifier.other10.3390/math12182952
dc.identifier.urihttp://hdl.handle.net/2263/100748
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.rights© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.en_US
dc.subjectAgricultural commoditiesen_US
dc.subjectRealized volatilityen_US
dc.subjectMulti-task forecastingen_US
dc.subjectSDG-02: Zero hungeren_US
dc.subjectSDG-08: Decent work and economic growthen_US
dc.titleMulti-task forecasting of the realized volatilities of agricultural commodity pricesen_US
dc.typeArticleen_US

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