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

Item Type Monograph (Working 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
Language English
Keywords Commodity futures, GARCH,Long-term volatility, Macroeconomic effects, Mixed data sampling
Subjects economics
finance
HSG Classification contribution to scientific community
HSG Profile Area SOF - System-wide Risk in the Financial System
Date 3 December 2018
Publisher SoF-HSG
Series Name School of Finance Working Paper Series
Depositing User Marion Stadelhofer
Date Deposited 03 Dec 2018 13:45
Last Modified 18 Jun 2021 00:24
URI: https://www.alexandria.unisg.ch/publications/255910

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Citation

Nguyen, Duc Khuong & Walther, Thomas: Modeling and Forecasting Commodity Market Volatility with Long-Term Economic and Financial Variables. School of Finance Working Paper Series, 2018,

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https://www.alexandria.unisg.ch/id/eprint/255910
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