[Luis Getino]

Hello,

I’ve been using EA Studio since the beginning of the year, and I took most of the courses. The reactor here works most of the time daily and I have tested many combinations of acceptance criteria and timeframes and I played a lot with data horizons to simulate trading after the out of sample period.

I am not using normalization, it doesn’t seem to have much impact on the robustness of the strategies,

I am not using walk forward too, because 20% OOS with the minimum profit factor 1.2 or 1.1 seems to work better to generate robust strategies. Also this way I have the chance to delete strategies that have 1.1 OOS profit factor but are loosing recently or have huge stagnation.

I like to use minimum R Squared 70 and maximum consecutive losses 10, but what Andi said is really really important. There is a huge difference in miminum 300 trades or minimum 500 trades. The strategies with 300 to 500 trades are much less robust even if they passed Monte Carlo test.

[Luis Getino]

Hi,

Are you using default for the Monte Carlo validation? Minimum net profit 10 and minimum count of trades 100?

If you have a good number of strategies that passed acceptance criteria but they fail to pass Monte Carlo validation, probably there is a problem with data you are using, maybe too small number of bars loaded. How many bars do you have? Which timeframe?

About acceptance criteria, what is the minimum count of trades do you set? Minimum 300 or more?

Are you using out of sample?

 

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