Econometric modelling of exchange rate volatility using mixed-frequency data

In the paper, we use generalized autoregressive conditional heteroskedasticity-mixed data sampling (GARCH-MIDAS) to study the impact of Australia’s commodity price index, Global economic conditions indicator, Global Economic Policy Uncertainty Index, monthly realised volatility of S&P/ASX 200 index and monthly realised volatility of money supply on the volatility of the Australian dollar during the period from 1999 to 2021. The results indicate that exchange rate volatility rises with a rise in fluctuations in S&P/ASX 200 index, money supply volatility, commodity price index and falls with a rise in global economic activity. For the GEPU index, the slope coefficient is positive and significant only in the 3- years lag and not significant in the 1- and 2-years lags. This means that a rise in economic turmoil leads to a rise in exchange rate volatility. We also find strong evidence for asymmetry in the short-term volatility component. The results obtained in the study show that there is co-movement of volatility across various financial markets.