Abstract
Commodities, especially gold and crude oil, are obvious to have a high fluctuation in recent years and lead a severe risk to investors. In this study, we consider a hedging strategy as a tool for offsetting the potential losses of investors. We develop various classes of Markov Switching constant conditional correlation GARCH model (MS-CCC-GARCH) to compute the optimal hedge ratios and portfolio weights in commodity markets (gold and crude oil) for the period of 2000–2018. We estimate three multivariate distributions MS-CCC-GARCH models (namely normal, student-t, and skewed student-t). The results find that MS-CCC-GARCH with student-t and normal distribution, for oil and gold, respectively, are the best model for hedge ratios and portfolio weights calculation in terms of the lowest AIC and BIC. Finally, the results of volatility and correlation of the best fit model are used to compute the value of hedge ratios and portfolio weights on gold and oil returns.
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