A comparison of the accuracy of short term foreign exchange forecasting methods

The hypothesis that foreign exchange rate behaviour is non-linear has been examined by several authors; others have proposed a linear framework. Here, evidence for a non-linear generating process is evaluated by an analysis of the comparative accuracy of short term forecasts of FX rates. Forecasts were generated by a linear AR-GARCH model and four non-linear methods, including three nearest neighbour methods and locally weighted regression. Five data frequencies were used: daily, four-hourly, two-hourly, hourly and half-hourly. Using root mean square error as a measure, significantly greater accuracy than a no-change forecast was achieved for two-hourly and higher frequency data sets. Using a test by Peseran and Timmerman, significant predictive directional accuracy was found for four-hourly and higher frequency data sets. These results were supported by simulated trading based on forecast direction. No evidence was found that the FX rate behaviour is better represented by a non-linear generating process than by a linear model.