Forecasting gold futures market volatility using macroeconomic variables in the United States

The U.S. gold futures market has recently attracted significant attention and the gold volatility is closely linked to macroeconomics. As such, the question is how to analyze the impact of various macroeconomic variables on gold. We use the GARCH-MIDAS (mixed data sampling) model to investigate whether macroeconomic variables can improve the predictions on the volatility structure of U.S. gold futures. Our empirical results reveal that macroeconomic variables have a significant influence on gold volatility, especially during and after the global financial crisis, indicating macroeconomic variables are driving factors of the long-term volatility on the U.S. gold futures market. Additionally, we use principal component analysis to obtain key information on different macroeconomic variables and further investigate their joint effects on the volatility of gold futures, finding that the first and second principal components are good proxies of macroeconomic variables. Our results show that principal components improve forecast accuracy, as do macrovariables, which are robust to various forecast rolling window schemes.