Peanut Butter Strategy

The Pullback strategy, which I actually got the idea from a ‘educational’ system, it had been a true ringing of what I had been studying. In the spirit of not giving up on a strategy quickly, this month marks one full year working on this concept.

Originally set to be a long term strategy, I have been working on it on smaller time frames, for no other reason than to refine the fractal I am trying to define.

The fractal:

When there is a strong breakout of any kind, even when not ranging, there is often a pullback. I ran the strategy on automation and found it to be quite accurate and way more practical in terms of long term trading ( not always watching the screen, etc,… ). From mid-august until December , it did about 17% on a couple instruments. I did intervene, but it was natural and based solely on fundamentals ( closing positions before nfp reports , elections, interest rate decisions , etc,… ).

The original robot eventually broke its code, and being that it was the first I programmed, I wasn’t to upset. It stopped doing longs and only was going shorts, for whatever reason. I poured over the code for a week trying to find where it broke, but in the mere 800 lines of code, rewriting it was not only necessary, but also welcomed.

Right now, I got 250 lines of code doing the same thing.

It waits for a cross over, a distance to be reached from a 50 and 200 moving average, and than places a limit order at a variable moving average, and changes the order to reflect a change for ever bar until the order is filled or a specific distance is reached , in which case it gives up.

So yeah, its working.

Now testing and fine tuning.

I think it is important to backtest for the past fifteen years. I place more weight on the last five years, but aim to make a generalized equity increase in both 2001-2011 and 2012 to now.

At first, I couldn’t get anything out of it but a dismal failure . As it is now, I have a break even from 2001 to 2009, and than 80% from 2010 until now.

I am doing my best to avoid over optimization, and looking more to finding the common in the trades to find the odds for each situation.


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