Power Trading (based on Standard Deviation)
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I think the problem with the (n1, n2) and (a, b, c) is that you need to run an optimization, thus somehow curve fitting, and therefore requires updates to find the optimal parameters. When you at Indices, it’s clear the markets in 2022 are very different from 2021. There is no size fits all, like in any Algos. With that said, I tried your idea with only 4 parameters (n1, a1 and n2,b) and found an incredibly high win rate without adding sophisticated trailing stop or MM. So, it’s promising for sure. Need to find time to explore the subject.
Hi Khaled.
I was elaborating with values and indices but dont end up with “..incredibly high win rate..”
Would you like to share your code, timeframe and indice?
Hi SnorreDK, I actually spoke too quickly because I put a TP of 5 pts on ES (SP500), which was easy to reach. Using a TP of 1.5*ATR, I reached at best a win rate of 47%, without adding filters like RSI, MFI, etc. Please note that with the propose code BUY STD[n](close[n]) … you will reach a high number of lots very quickly.
JS, your idea is brilliant. It is actually close to Bollinger Bands concept.
It is nothing more than Bollinger Bands (not used for mean reversion but trend following)… Really nothing new.
I think, it would make more sense using linear regression coupled with standard deviation, like this below.
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