Multi-Task Forecasting of the Realized Volatilities of Agricultural Commodity Prices

Rangan Gupta and Christian Pierdzioch

No 202423, Working Papers from University of Pretoria, Department of Economics

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 pe- riod 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 hardly evidence that multi-task forecasting improves out-of-sample forecasts relative to a classic univariate heterogeneous autoregres- sive (HAR) RV model. We also study an extended model that features the RVs of energy commodities and precious metals.

Keywords: Agricultural commodities; Realized volatility; Multi-task forecasting (search for similar items in EconPapers)
JEL-codes: C22 C32 C53 Q11 (search for similar items in EconPapers)
Pages: 49 pages
Date: 2024-06
New Economics Papers: this item is included in nep-agr, nep-for and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Journal Article: Multi-Task Forecasting of the Realized Volatilities of Agricultural Commodity Prices (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:202423

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