No profitable results are found for the US, Japanese and Western European stock market indices. However, estimation of Sharpe-Lintner CAPMs indicates that the economic profits of technical trading in almost all stock market indices, except the Egypt CMA and the Russia Moscow Times, can be explained by risk, after a correction is made for sufficiently high transaction costs. Only for transaction costs below or equal to 0.25% some risk-corrected out-of-sample forecasting power is found for the Asian, Latin American, Middle East and Russian stock market indices.
Hence, in short, after correcting for sufficiently high transaction costs, risk, data-snooping and out-of-sample forecasting, we conclude that objective trend-following technical trading techniques, applied to local main stock market indices all over the world, are not genuine superior, as suggested by their in-sample performance results, to the buy-and-hold benchmark. Only for sufficiently low transaction costs some statistically significant risk-corrected out-of-sample forecasting power is found for the Asian, Latin American, Middle East and Russian stock market indices.
5.6 Comparing the US, Dutch and
Other Stock Markets
Table 5.18 summarizes for all transaction costs cases the results of testing the set of 787 trend following technical trading techniques on the DJIA and on stocks listed in the DJIA (Chapter 3), on the AEX-index and on stocks listed in the AEX-index (Chapter 4) and on 51 stock market indices world wide (Chapter 5). If the return of the best technical trading strategy, selected in sample, in excess of the risk free interest rate is regressed against a constant α and the return of a market portfolio in excess of the risk free interest rate (see CAPMs (3.5), (4.1) and (5.1)), then the rows labeled ``(1) in-sample CAPM: α > 0'' show for each chapter the fraction of data series for which the estimate of α is significantly positive at the 10% significance level. The rows labeled ``(2) pW<0.10'' show the fraction of data series for which White's (2000) RC p-value is smaller than 0.10. The rows labeled ``(3) pH<0.10'' show the fraction of data series for which Hansen's (2001) SPA-test p-value is smaller than 0.10. Finally, the rows labeled ``(4) out-of-sample CAPM: α > 0'' show as in the rows labeled ``(1) in-sample CAPM: α > 0'' the fraction of data series for which the estimate of α is significantly positive at the 10% significance level, but this time when the return of the best recursive optimizing and training procedure in excess of the risk free interest rate is regressed against a constant α and the return of a market portfolio in excess of the risk free interest rate. Panel A shows the results if the best technical trading strategy is selected by the mean return criterion and panel B shows the results if the best technical trading strategy is selected by the Sharpe ratio criterion.
In each chapter for all data series a technical trading strategy that is capable of beating the buy-and-hold benchmark can be selected in sample. In the case of zero transaction costs it can be seen in the rows labeled ``(1) in-sample CAPM: α>0'' that in each chapter for a majority of the data series the estimate of α is significantly positive, indicating that the best selected technical trading rule has statistically significant forecasting power after