The Dornbusch-Frankel monetary model is used to estimate the out-of-sample forecasting performance for the U.S. or Canadian dollar exchange rate. By using Johansen's multivariate cointegration, up to three cointegrating vectors were found between the exchange rate and macroeconomic fundamentals. This means that there is a long-run relationship between exchange rate and economic fundamentals. Based on error-correction models, the random-walk model outperforms the Dornbusch-Frankel model at every forecasting horizon. The random-walk model also dominates the Dornbusch-Frankel model with the modified money demand function at every forecasting horizon except one month. However, this paper shows that the share price variable can improve the accuracy of forecasts of exchange rates at short-run horizons.