But of these four systems, which are profitable? Which one is the “best?” Plotting the systems on the reward-to-risk vs. winning percentage curve gives the answers. This is shown in “Comparing systems” (below). With the four trading strategies plotted, it is easy to eliminate system No. 4 because it has a negative expectancy. This is a good example of a high winning percentage system not necessarily being a profitable system.
The other three strategies all have positive expectancy, but is one better than the others? Some traders will favor system No. 1 because it has the highest reward-to-risk ratio. The thrill of the occasional jackpot trade entices some traders, even if the winning percentage is low.
Other people will like system No. 3 the most because it has the highest winning percentage of the three profitable systems. These traders like to hear the cash register ring often from winning trades, even if those wins are relatively small. These are the traders who usually seem to win, and may even attract followers because of their seemingly prescient predictions.
Psychological (or marketing) reasons aside, the best system to trade is system No. 2. As shown on the plot, it is the furthest away from the breakeven line. Therefore, the expectancy of system No. 2 is the highest. It does not have the best reward-to-risk ratio, and it does not have the best winning percentage, but it does have the best combination of the two.
By themselves, reward-to-risk and winning percentage have little value. The same can be said about other trading statistics, such as net profit (which needs drawdown to quantify risk), consecutive winners/losers (which needs overall winning percentage for perspective) and average trade profit (which needs number of trades to gauge overall profitability). In each of these cases, the single statistic does not tell you enough about the strategy.
Even expectancy, by itself, does not tell the whole story. A lower expectancy system that trades frequently may indeed be preferable to a higher expectancy, but infrequently traded strategy. Again, focusing on just one number may lead to incorrect conclusions. The key is to evaluate all the pertinent statistics of a strategy at the same time. That way, some bad statistics can be overcome with the help of complementary statistics. In the end analysis, a thorough evaluation of all trading statistics, taken together, is the best approach for a good decision.
Kevin J. Davey has been trading for more than 20 years. Prior to trading full time starting in 2008, Kevin was a quality assurance and engineering executive for an aerospace company. You can reach him via his website www.kjtradingsystems.com.