filter, time delay filter, fixed holding period, stop-loss]''. In the case of a trading range break, also called support-and-resistance (SR), strategy, the parameters are ``[the number of days over which the local maximum and minimum is computed]'' plus the refinement parameters as with the moving averages. In the case of a filter (FR) strategy the parameters are ``[the %-filter, time delay filter, fixed holding period]''. Columns 3 and 4 show the mean yearly return and excess mean yearly return of the best-selected strategy over the buy-and-hold benchmark, while columns 5 and 6 show the Sharpe ratio and excess Sharpe ratio of the best-selected strategy over the buy-and-hold benchmark. Column 7 shows the maximum loss the best strategy generates. Columns 8, 9 and 10 show the number of trades, the percentage of profitable trades and the percentage of days profitable trades last. Finally, the last column shows the standard deviation of the returns of the data series during profitable trades divided by the standard deviation of the returns of the data series during non-profitable trades.
To summarize, for each data series examined table 4.7A (i.e. table 4.7 panel A) shows the mean yearly excess return over the buy-and-hold benchmark of the best strategy selected by the mean return criterion, after implementing 0, 0.10, 0.25, 0.50, 0.75 and 1% costs per trade. This wide range of costs captures a range of different trader types. For example, floor traders and large investors, such as mutual funds, can trade against relatively low transaction costs in the range of 0.10 to 0.25%. Home investors face higher costs in the range of 0.25 to 0.75%, depending whether they trade through the internet, by telephone or through their personal account manager. Next, because of the bid-ask spread, extra costs over the transaction costs are faced. By examining a wide range of 0 to 1% costs per trade, we belief that we can capture most of the cost possibilities faced in reality by most of the traders.
The results in table 4.7A are astonishing. As can be seen in the last row of the table, on average, the mean yearly excess return of the best strategy over the buy-and-hold benchmark is equal to 152% in the case of zero transaction costs, and it still is 124% in the case of 1% transaction costs. These incredibly good results are mainly caused by the communications and cable network firms KPNQWest, UPC and Versatel. However, subtracting all stocks for which the best strategy generates a return of more than 100% yearly in excess of the buy-and-hold, then, on average, the yearly excess return of the best strategy is equal to 32% in the case of no transaction costs, declining to 15%, if transaction costs increase to 1% per trade. Thus from these results we conclude that technical trading rules are capable of beating a buy-and-hold benchmark even after correction for transaction costs. These results are substantially better than when the same strategy set is applied to the DJIA and to stocks listed in the DJIA. In that case in