strategy is not superior to the benchmark after correcting for data snooping is rejected by the RC, while for 14 data series the null hypothesis that none of the alternative strategies is superior to the buy-and-hold benchmark after correcting for data snooping is rejected by the SPA-test. The two data snooping tests thus give contradictory results for 12 data series. However, if we implement as little as 0.10% costs, then both tests do not reject the null anymore for almost all data series. Only for Robeco and UPC the null is still rejected by the SPA-test. Remarkably, for Robeco and UPC the null is rejected even if costs are increased to 0.50%, and for UPC only if costs per trade are even higher. Hence, we conclude that the best strategy, selected by the mean return criterion, is not capable of beating the buy-and-hold benchmark strategy, after a correction is made for transaction costs and data snooping.
4.3.2 Results for the Sharpe ratio criterion
Technical trading rule performance
Similar to tables 4.4 and 4.5, table 4.6 shows for some data series some statistics of the best strategy selected by the Sharpe ratio criterion, if 0 or 0.25% costs per trade are implemented. Only the results for those data series are presented for which the best strategy selected by the Sharpe ratio criterion differs from the best strategy selected by the mean return criterion. Further table 4.7B shows for each data series the Sharpe ratio of the best strategy selected by the Sharpe ratio criterion, after implementing 0, 0.10, 0.25, 0.50, 0.75 and 1% transaction costs, in excess of the Sharpe ratio of the buy-and-hold benchmark. It is found that the Sharpe ratio of the best-selected strategy in excess of the Sharpe ratio of the buy-and-hold benchmark is positive in all cases. In the last row of table 4.7B it can be seen that the average excess Sharpe ratio declines from 0.0477 to 0.0311 if transaction costs increase from 0 to 1%. For the full sample period table 4.6 shows that the best strategies selected in the case of zero transaction costs are mainly strategies that generate a lot of signals. Trading positions are held for only a short period. Moreover, for most data series, except 13, these best-selected strategies are the same as in the case that the best strategies are selected by the mean return criterion. If transaction costs are increased to 0.25% per trade, then the best strategies generate fewer signals and trading positions are held for longer periods. In that case for the AEX-index and 18 stocks the best-selected strategy differs from the case where strategies are selected by the mean return criterion.As for the mean return criterion it is found that for each data series the best technical trading strategy, selected by the Sharpe ratio criterion, beats the buy-and-hold benchmark