Power Trading (based on Standard Deviation)

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09/21/2022 at 8:13 AM #201119 quote

SnorreDK
Participant

Junior

Khaled wrote:

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?

09/21/2022 at 1:40 PM #201139 quote

Khaled
Participant

Veteran

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.

SnorreDK and jonpt88 thanked this post

12/11/2024 at 8:16 PM #241345 quote

j102491
Participant

New

Hello, I see this is an old thread but I’m new here and this caught my interest. In regards to Std[n](Close[n]). Is the Std multiplied by the close or is that the standard deviation of the close?

12/11/2024 at 9:44 PM #241346 quote

JS
Participant

Senior

Hi,

The formula Std[n](Close) calculates the standard deviation based on the “Close”, where [n] represents the period over which the standard deviation is calculated.

12/11/2024 at 10:04 PM #241347 quote

j102491
Participant

New

Thank you

12/21/2024 at 11:21 AM #241653 quote

LucasBest
Participant

Average

Khaled wrote:

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.

Capture-decran-2024-12-21-112042.png

12/21/2024 at 11:44 AM #241655 quote

LucasBest
Participant

Average

Here in 15min timeframe.

Capture-decran-2024-12-21-114031.png

12/21/2024 at 12:07 PM #241657 quote

LucasBest
Participant

Average

With 2 different standard deviation and offset you can even increase the accuracy of the entries following the breakouts

GraHal thanked this post

Capture-decran-2024-12-21-120350.jpg
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