Markov switching and exchange rate predictability

We first show that the recent success of modern macroeconomic models in forecasting nominal exchange rates, evaluated using the inference procedure, is partly due to the presence of the constant term (drift), in addition to the economic fundamentals. We then model the drift term using the two‐state Markov switching stochastic segmented trend model and present evidence of both short‐run (one month) and long‐run (up to one year) predictability for monthly exchange rates over the post‐Bretton Woods period. This is an important result, as the recent literature has typically failed to find evidence of consistent multi‐horizon predictability. The model strongly outperforms the random walk for 9 out of 12 exchange rate series at short horizons; for 7 of the 12 exchange rates, we find evidence of a long‐run predictability that declines as the forecast horizon increases. Our results remain robust to alternative test statistics and forecast windows.