Forecasting exchange rates using panel model and model averaging

We propose to produce accurate point and interval forecasts of exchange rates by combining a number of well known fundamental based panel models. Combination of each model utilizes a set of weights computed using a linear mixture of experts's framework, where weights are determined by log scores assigned to each model's predictive performance. As well as model uncertainty, we take potential structural break in the parameters of the models into consideration. In our application, to quarterly data for ten currencies (including the Euro) for the period 1990q1–2008q4, we show that the forecasts from ensemble models produce mean and interval forecasts that outperform equal weight, and to a lesser extent random walk benchmark models. The gain from combining forecasts is particularly pronounced for longer-horizon forecasts for central forecasts, but much less so for interval forecasts. Calculations of the probability of the exchange rate rising or falling using the combined or ensemble model show a good correspondence with known events and potentially provide a useful measure for uncertainty of whether the exchange rate is likely to rise or fall.