Modeling and Forecasting Commodity Market Volatility with Long-term Economic and Financial Variables

Item Type Journal paper
Abstract This 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 GARCH-MIDAS 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 of 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 the global real economic activity as well as the 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.
Authors Nguyen, Duc Khuong & Walther, Thomas
Journal or Publication Title Journal of Forecasting
Language English
Subjects economics
finance
HSG Classification contribution to scientific community
HSG Profile Area SOF - System-wide Risk in the Financial System
Refereed Yes
Date 2020
Publisher Wiley
Volume 39
Number 2
Page Range 126-142
ISSN 0277-6693
Publisher DOI https://doi.org/10.1002/for.2617
Depositing User Prof. Dr. Thomas Walther
Date Deposited 12 Jun 2019 19:48
Last Modified 08 Dec 2022 01:25
URI: https://www.alexandria.unisg.ch/publications/257164

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Nguyen, Duc Khuong & Walther, Thomas (2020) Modeling and Forecasting Commodity Market Volatility with Long-term Economic and Financial Variables. Journal of Forecasting, 39 (2). 126-142. ISSN 0277-6693

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https://www.alexandria.unisg.ch/id/eprint/257164
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