Forecasting exchange rates: The time-varying relationship between exchange rates and Taylor rule fundamentals

There is empirical evidence for a time-varying relationship between exchange rates and fundamentals. Such a relationship with time-varying coefficients can be estimated by a Kalman filter model. A Kalman filter estimates the coefficients recursively depending on the prediction error of the examined model. Using a Taylor rule based exchange rate model, which in the literature was found to have promising forecasting abilities, it is possible to further improve the performance if the utilization of information from the prediction error is restricted. This is necessary as classic exchange rate models do not perform badly solely because they neglect the time-varying relationship, but also due to missing explanatory information. So, if the Kalman filter uses the entire information from the prediction error, it would overestimate the need for coefficient adjustment. With this calibration of the Kalman filter model the short-term out-ofsample forecasting accuracy can be enhanced for 10 out of 12 exchange rates.