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Improving Performance with a Losing Streak Filter: 1 Year Later

February 26, 2007

 

One year ago nearly to the day, we asked in our newsletter: "What if there was a way to increase a system's net profit by about 5%, while decreasing the Max DD by about 40% ? Would you be interested?" See the newsletter here: http://www.attaincapital.com/alternatives/alt_feb2706.htm#Topic

Well, several clients liked the idea of trying to filter out losing streaks, and applied our filter to several systems shortly after the newsletter. After trying several ideas of filtering on market volume, volatility, and more - we ended up using the equity curve itself as a filter, where we use moving average cross overs of the equity curve to signal whether to be "ON" or "OFF" a system.

Much in the way you might trade a stock around its 200 day moving average, the MA cross over filter we tested would have an investor "ON" a trading a system when the 10 day moving average of system equity is over the 200 day average, for example; and "OFF" the system when the 50 day average has dipped below the 200 day average. This is basic technical analysis 101, but its use on the actual equity curve of the system has been limited at best.

Those clients looking to apply the filter agreed that the filter made more sense on swing trading systems, especially those that reverse and are in the market a majority of the time. The logic was that swing trading systems can get "caught" in a consolidation pattern which "chops" the system up, buying the highs and selling the lows. So, our one year test is on swing trading systems Delphi and Tzar, operating on the eMD and eRL and ES and eRL respectively.

The results were impressive, with the average profit across the four systems moving up 9 percentage points, from 7.07% to 16.82%, and the average drawdown across the test period going down from 47.79% to 28.91%.

Hypothetical Model Accounts Using Actual Client Fills

This real time test of the filter logic further supported our earlier theory that such a filter will not look very good on pre-release testing, but will perform well on post-release performance. The theory is that hypothetical, pre-release testing of many trading systems has been developed on the known market environment up to that time, and that it is more than possible that the system will encounter a different trading environment in the future. And if you're a cynic and believe the pre-release testing contains a certain degree of curve fitting (intentionally or accidentally - it doesn't matter), then you're thinking that there will be a lot of poor trading environments for trading systems in the future.

So while the pre-release testing may have little or no "bad" environments, the future performance of the system will have several such environments, making it not only more important to try and filter out those bad times - but easier to identify them, as there will be more of them (and they will last longer). In short - there's not a lot of bad (or long) losing streaks in pre-release testing, as that would not wet an investor's appetite in the first place. But there is the very real chance that there will be some bad losing streaks in the future. Whether there are or not, it seems to make sense to have some hedge against them happening.

The moving average filter signals a system is entering a poor environment by seeing the current performance of the system not match up with the long term performance. That signal means the current environment may be a poor one for the system, and lets the investor sit on the sideline until that time is over (as signaled by the short term system performance moving back to or above its historical norms).

We ran the filter across our universe of systems using post-release data only, and came up with the following list of the top 15 systems the filter "benefits" most. You can see that in 11 out of the 15, the filter actually turns negative performance into positive performance, while the DD is reduced in all 15.

Want to trade using this filter, or have a system you want to see it tested on? Just pick up the phone and call us at (800) 311.1145. We're not giving out the exact parameters of this filter due to our excitement of the possibilities it may bring, but can of course implement it for Attain clients.