Thank you.A poster from way back in 2003 acrary mentioned a minimum of 100 trades and putting that into 1/(sqrt(# trades)) = a standard error of 10% which would be acceptable.
Thank you.A poster from way back in 2003 acrary mentioned a minimum of 100 trades and putting that into 1/(sqrt(# trades)) = a standard error of 10% which would be acceptable.
In my day trading method, the profit/loss, a small number, is the difference of two large numbers and normally the R:R and the win rate are slightly above 1:1, 50/50. To defeat the null hypothesis (R:R=1:1, 50/50) may require more than a sample of 100 trades. 6 weeks of winning consistently could be an illusion and I don't want to scale up then find out it is an illusion.A poster from way back in 2003 acrary mentioned a minimum of 100 trades and putting that into 1/(sqrt(# trades)) = a standard error of 10% which would be acceptable.
I actually decided to go the other way, reduce size by 5x and stress test the hack out of the system. So starting Monday, I am trading for a cup of Starbuck instead of a Big Mac. But instead of making 5-10 trades and call it a day, I want to make 40-50 trades a day, from sun up to sun down and see what I get out of the system.If you scale up 2x to $2k size you won’t lose a lot even you’re wrong. I’d say scale up to 2x and see what happens.
A headache and prove nothing........and see what I get out of the system
Only increase timeframe is reliable to reduce noise.
%%And when you increase the timeframe, you will notice that you will be missing
tons and tons of trading opportunities.


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