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

Gupta, Rangan; Pierdzioch, Christian

doi:10.3390/math12182952

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

Publication date

2024-09-23

Document type

Forschungsartikel

Author

Gupta, Rangan

Pierdzioch, Christian

Organisational unit

VWL, insb. Monetäre Ökonomik

DOI

10.3390/math12182952

URI

https://openhsu.ub.hsu-hh.de/handle/10.24405/22176

Scopus ID

2-s2.0-85205049693

Publisher

MDPI

Series or journal

Mathematics

ISSN

2227-7390

Periodical volume

12

Periodical issue

18

Article ID

2952

Is a version of

https://openhsu.ub.hsu-hh.de/handle/10.24405/19402

Peer-reviewed

✅

Part of the university bibliography

✅

Language

English

Keyword

agricultural commodities

multi-task forecasting

realized volatility

Abstract

Motivated 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.

Description

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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Published version

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