Modeling and forecasting commodity market volatility with long‐term economic and financial variables

Journal of Forecasting - Tập 39 Số 2 - Trang 126-142 - 2020
Duc Khuong Nguyen1,2, Thomas Walther3,4
1IPAG Lab, IPAG Business School, 184 Boulevard Saint-Germain, 75006 Paris, France
2School of Public and Environmental Affairs, Indiana University, 107 S Indiana Ave, Bloomington, IN 47405 USA
3Faculty of Business and Economics echnische Universität Dresden Dresden 01062 Germany
4Institute for Operations Research and Computational Finance, University of St. Gallen, St. Gallen, 9000 Switzerland

Tóm tắt

AbstractThis paper investigates the time‐varying volatility patterns of some major commodities as well as the potential factors that drive their long‐term volatility component. For this purpose, we make use of a recently proposed generalized autoregressive conditional heteroskedasticity–mixed data sampling approach, which typically allows us to examine the role of economic and financial variables of different frequencies. Using commodity futures for Crude Oil (WTI and Brent), Gold, Silver and Platinum, as well as a commodity index, our results show the necessity for disentangling the short‐term and long‐term components in modeling and forecasting commodity volatility. They also indicate that the long‐term volatility of most commodity futures is significantly driven by the level of global real economic activity as well as changes in consumer sentiment, industrial production, and economic policy uncertainty. However, the forecasting results are not alike across commodity futures as no single model fits all commodities.

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Journal of Forecasting

Tập 39 Số 2

126-142

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