Evaluating Trading Systems : Characteristics and Quality

The evaluation of trading strategies is certainly one of the most necessary processes in the trading of mechanical manual or automated systems. The value of evaluation is great since it allows traders to loose their irrational fear and greed emotions and gain a true understanding about the characteristics of the trading system they intend to trade. Part of the evaluation of trading systems involves the judging of different quality parameters to distinguish what makes a system better and what makes it worse, a process which although seemingly intuitive is not so straightforward. Adequate knowledge about the information pertaining to each parameter of the test and what it conveys the user is necessary to know what its consequences actually are in real trading and what their power is from a comparative standpoint. On today’s post I am going to talk about how to look at a system’s characteristics and what you should be looking for to judge the quality of a given strategy.

New traders are often confused when it comes to the evaluation of trading strategies something which is not surprising if you take into account the whole amount of information which can be derived for a given system. People new to trading first seem to focus on the absolute values of the profit and maximum draw down percentages but judging the quality of a trading system merely by looking at these two values without prior experience is very hard. It is also true that judging a system just through one of these two values is misleading in the sense that it doesn’t represent a good overall picture of the strategy’s characteristics. For example, saying that a system makes 100% a year does not make any sense if the actual potential draw down is not known and even if it is, other characteristics need to be taken into account.

The most simple way to compare a trading system to another effectively is to use ratios of profit and draw down variables. The profit factor, which compares the gross profit against the gross losses of a strategy is an initial measure of system quality. However, although this type of ratios do give us some information about the past risk to reward long term expectation (especially when evaluated over 10 year periods) they do not talk a lot about the problems the strategy would run into with increases in future risk. For this reason I believe that although these ratios are useful to some extent to compare simulations they do not fully represent the inherent market exposure of the system in a way in which a true comparison is made.

System quality – without a doubt – needs to include an analysis of increases in risk over the projected values achieved in simulations to know the true problems that the user may be running into if – for example – risk in the future increases or the estimation of profit and draw down targets is not accurate. For this reason it seems better to evaluate strategies based on projections of increased risk to know the true quality of the system and how dependent it may be on small glitches in simulations.

In this case our best shot at accurate quality comparisons seems to be the average compounded yearly profit to worst case scenario ratio in which the average yearly profit (over a 10 year period) is compared to twice the maximum draw down of the strategy (worst case ratio). To add more meaning to this increased risk comparison a careful user might also want to test the average compounded yearly profit to double consecutive loses after maximum draw down ratio (worst streak ratio). In this ratio, the average compounded yearly profit is compared to the maximum draw down percentage plus a string of loses equal to twice the number of maximum consecutive losing trades. The idea here is to get an idea about the robustness of the strategy and how bad things can turn before a bad scenario is bound to happen.

Systems that are very sensitive to small changes in the number of consecutive loses will give very unfavorable ratios in both cases while systems that have less dependency on individual trades will get better results. This way of evaluating strategies eliminates by default a lot of systems that use unsound trading tactics such as martingales and systems with very bad risk to reward ratios due to the fact that this ratio comparison makes them show their flaws if increases in risk are presented. One thing all traders should understand is that in the future the risk of any given strategy is bound to increase to some extent and having systems that are able to handle this risk increase is not only vital but necessary for successful long term trading.

The above evaluation criteria also allows you to use systems that don’t need to wipe accounts to demonstrate that the market has become too risky for them. For example, a strategy with a worst case ratio of 1:2 targeting a 20% yearly profit may be stopped from trading at a 40% draw down while a system that has a 1:5 ratio in the same situation would end up killing the account before we realize it has become to risky. It is also important here to note that sound systems will have a “worst case ratio” better or only slightly worse than their “worst streak ratio” while systems that use unsound techniques -which will be sensitive to small increases in consecutive loses – will have a much worse “worst streak ratio”.

In summary my advice is that you focus on the profit to draw down ratios when evaluating trading strategies but -most importantly – that you evaluate ratios in which the maximum draw down and maximum number of consecutive loses are increased so that you get a true idea about your system’s robustness. If you would like to learn more about automated trading and how you too can start designing your own likely long term profitable systems please consider buying my ebook on automated trading or joining Asirikuy to receive all ebook purchase benefits, weekly updates, check the live accounts I am running with several expert advisors and get in the road towards long term success in the forex market using automated trading systems. I hope you enjoyed the article !

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