Power Trading (based on Standard Deviation)

JS · Sat, 17 Sep 2022 11:27:01 +0000

Power Trading (a trading system based on the standard deviation) I want to share with you a trading system that is based on a difference equation. In this case, the difference equation describes the difference between two prices. The basic question was: how can I describe the difference between two prices or in formula form: Close = Close[n] + ??? What is it that causes the current rate to differ from the previous rate, what causes the price change? There are many different opinions about this, for example: 1: It is a deterministic process (it is already fixed) 2: It is the psychology of the investor 3: It is purely economical 4: It is a random, unpredictable stochastic process 5: etc. The change of course is probably the result of a mix of the above views… 🙂 Because you can’t figure this out, the next question is: how can I describe this change of course, in formula form, in the best possible way? To make a very long story short, it turned out that the standard deviation is the best (?) way to describe the price change. The difference equation then looks like this: Close = Close[n] + Std[n](Close[n]) Or for falling prices: Close = Close[n] – Std[n](Close[n]) Example: Suppose you want to build a LONG system for the Nasdaq, then your code, in its simplest form, can look like this: DefParam CumulateOrders = False If Close > Close[n] + Std[n](Close[n]) then Buy 1 contract at Market EndIf If Close < Close[n] – Std[n](Close[n]) then Sell at Market EndIf The only variable in this system is the period [n] and you can of course optimize this for the different markets. It turns out to be a robust system. It would be nice if we could use all the knowledge from the forum regarding optimization of the system (TF, Money Management, Stops, MTF, etc.) so that we can all benefit from it. DefParam CumulateOrders = False If Close > Close[n] + Std[n](Close[n]) then Buy 1 contract at Market EndIf If Close < Close[n] - Std[n](Close[n]) then Sell at Market EndIf

This topic has 16 replies, 4 voices, and was last updated 1 year ago by Khaled.

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

SnorreDK

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?

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

Khaled

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.

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jonpt88, SnorreDK

Khaled
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Power Trading (based on Standard Deviation)

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