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In the previous part of this 3-part article, I explained the concept of my breakout ATS model that I’ve been successfully using for about seven years. We’ve learned about four crucial components of the model: POI, distance, time filter, and a regular filter. In this part, we’ll explore each filter more in detail.
Highest O/H/L/C X-days back All of these are very basic and obvious; still I was able to construct pretty impressive and robust strategies with just this beginner’s stuff. Plenty of these strategies are still part of my portfolio. Of course, over time, I’ve started thinking about other possibilities of different POIs and I’ve added many more:
POI +/- (X * TR) Again, you can stick to just these two for a very long time and get fantastic and robust strategies. But of course, you also want to keep evolving your approach so you start looking for different techniques to deploy. In my case, it was:
Highest High (X) – Lowest Low (X) differences Surprisingly, the results were not usually better than when using the most common and obvious ATR/TR! In fact, I quit GapLess variations completely and, although I still keep the other techniques in my D&P (Design & Prototype) code, the majority of my strategies still use ATR/TR. You don’t really need to be creative when it comes to the distance.
Time Filter At the very beginning, I used to be very “precise” when it came to the time filter. That said, I used to optimize the exact, most optimal start time and end time for every breakout ATS. Not surprisingly, I soon realized there was too much over-optimization (making it much harder to pass my very demanding robustness tests).
After a couple of years, I simplified the time filter approach pretty much and, right now, what I like is to divide the regular trading session into three or four equal parts and test the efficiency of each part separately (I call this T-Segmenting, because it’s just splitting the time into different segments). This is an absolutely sufficient solution and also a very logical one, as from my previous experience, I already know that the usual regular session behaves differently especially at its beginning, in its middle, and at its end.
Therefore T-Segmenting into three different parts is the most usual approach in the case of my breakout ATSs. Just to give you a small example, let’s say I develop a breakout ATS for e-mini Russell 2000 (TF). The regular trading hours are 9:30 – 16:15. So, I make three T-Segments:
Using certain absolute or relative difference between two ATRs with different periods I don’t have a bias towards any of the techniques and I freely use or test all of them. At the end of the day, it’s always the robustness test that will reveal the truth. Whatever passes the robustness testing is fine for me. Of course, over time, I’ve again developed plenty of my own filtering techniques and indicators, but still, I’ve been able to happily live just with the stuff I’ve described to you.
— By Tomas Nesnidal of Systems on The Road.
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