New article Developing a self-adapting algorithm (Part I): Finding a basic pattern has been published:
In the upcoming series of articles, I will demonstrate the development of self-adapting algorithms considering most market factors, as well as show how to systematize these situations, describe them in logic and take them into account in your trading activity. I will start with a very simple algorithm that will gradually acquire theory and evolve into a very complex project.
The EA features the ability to re-invest the earned funds. You need to use it. Until now, I showed the tests with conservative settings. But what if we set very aggressive settings and enable a lot increase? I am not a fan of high risks, but let's see what the algorithm is capable of. I will perform the test on GBPUSD from 2006.01.01 to 2020.11.25 in the "Every tick" mode. Of course, it is possible to test another symbol. The spread is reduced to 20. This is slightly above average. Figure 12 shows the backtest result for almost 15 years.
Figure 12. GBPUSD from 2006.01.01 to 2020.11.25, aggressive settings
As you may remember, the algorithm uses close prices. Therefore, this result is not a "test grail". In addition, the adequate spread of 20 is set. The algorithm's trading result on the real market usually coincides with the one obtained in the tester. I have never used it to trade with such aggressive settings. Besides, it is impossible to take into account real spreads in MetaTrader 4, so I will not argue that it would have passed this period as well in real trading.
Author: Maxim Romanov
Thank you, new articles have already been written and are in the process of being translated. They will be even more interesting.
Interesting concept and article, thank you!
I am working on a similar project, the main difference is that in the N-sized window (N is between 1-5 at first) I use the relation of HLOC values of consecutive candles and also the relation within all the bars in the window one by one. It seems this will make it too complex.
This concept is nice with its simpleness.
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