out rules yield better results than the moving averages. Although the trading rules show significant forecasting power, it is concluded that after correcting for transaction costs the trading rules cannot profitably be exploited. In contrast, Ming Ming, Mat Nor and Krishnan Guru (2000) find significant forecasting power for the strategies of Brock et al. (1992) when applied to the Kuala Lumpur Composite Index (KLCI) even after correction for transaction costs.
Detry and Gregoire (2001) test 10 moving-average trading rules of Brock et al. (1992) on the indices of all 15 countries in the European Union. They find that their results strongly support the conclusion of Brock et al. (1992) for the predictive ability of moving-average rules. However the computed break-even transaction costs are often of the same magnitude as actual transaction costs encountered by professional traders.
In his master's thesis Langedijk (2001) tests the predictability of the variable moving-average trading rules of Brock et al. (1992) on three foreign exchange rates, namely USD/DEM, JPY/DEM and USD/JPY, in the period July 1973 through June 2001. By using simple t-ratios he finds that technical trading rules have predictive ability in the subperiod July 1973 through June 1986, but that the results deteriorate for the period thereafter. Because for the USD/JPY exchange rate the strongest results in favor of technical trading are found, standard statistical analysis is extended by the bootstrap methodology of Brock et al. (1992). It is found that random walk, autoregressive and GARCH models cannot explain the results. However Langedijk (2001) shows that only large investors with low transaction costs can profitably exploit the trading rules.