Forecasting short-run exchange rate volatility with monetary fundamentals: A GARCH-MIDAS approach

Abstract We utilize a fundamentals-based component volatility model to forecast the short-run volatility of exchange rate changes using monetary fundamentals quoted at different frequencies. Specifically, we allow the component volatility model to distinguish short-run exchange rate fluctuations from long-run movements that are directly linked to monetary fundamentals. Relative to more traditional time series volatility models, we find significant improvements in the ability to forecast the daily volatility of exchange rate changes by incorporating the monthly monetary fundamentals’ volatilities as predictors into the component volatility model. In the utility-based comparisons, we find that an investor is willing to pay a positive annual management fee of 5.72% on average to switch from the benchmark model to the fundamentals-based models. Of these models, the model with the symmetric and homogeneous Taylor rule and interest rate smoothing obtains the highest positive annual management fee.