February 6th, 2017
My last article showed impressive test results.
Yet, my book states that one could do even better. One could start with a trading strategy having some built-in edge as was presented in Part one. And build from there. The portfolio equation to be used would still be:
A(t) = A(0) + (1+g)t ∙n∙u∙PT.
Raising g will increase the total output. You do not need to push by much since there is a compounding effect in place.
As a demonstration of the phenomenon, I used the same trading strategy as presented in the previous article. Raised its g value by 1.5%. A minor modification, yet, the impact is noteworthy.
The change of a single variable, a single number, and it raises the performance level. It is understandable since (1+g)t is a compounding factor. It is also a factor that could be controlled from outside the program. As if giving the ability to direct at will the strategy's orientation and behavior.
This is not an optimization factor, it is not over-fitting either. None of the trading logic was changed. The trading strategy was just taken as is. It was a request, an administrative one at that. The strategy was just asked (ordered) to do more of what it did. This evidently impacted a lot of the trades over the life of the portfolio since it was a time function. You can see this effect in the first cumulative return chart in the HTML file below.
There was no change to the trading strategy. It kept its signature. It is only that you demanded more.
Hope it helps. At least, it can give ideas as to how far one can go.
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Created... February 6th, 2017, © Guy R. Fleury. All rights reserved.