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Modeling and Forecasting Commodity Market Volatility with Long-Term Economic and Financial Variables
Series
School of Finance Working Paper Series
Type
working paper
Date Issued
2018-12-03
Author(s)
Nguyen, Duc Khuong
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.
results are not alike across commodity futures as no single model fits all commodities.
Language
English
Keywords
Commodity futures
GARCH
Long-term volatility
Macroeconomic effects
Mixed data sampling
HSG Classification
contribution to scientific community
HSG Profile Area
SOF - System-wide Risk in the Financial System
Publisher
SoF-HSG
Division(s)
Eprints ID
255910