Madness 

Hello Adilius, Sorry for the really late response. So, before you can understand my stop loss you have to understand the meaning of my thread. The whole point to my thread is to be able to test a strategy without being unskewed by stop-losses that are usually triggered by market makers running stops. There are 4 requirements I need to classify a strategy successful. These requirements are: 1) Your strategy has to give you a 90% or higher win rate. Meaning it reaches the price target. 2) Your trade only lasts at most a few minutes. (1 sec to 20 min) 3) It has to give you consistent backtesting results under normal market conditions for 60 days.

Hello Madness,

Thanks for sharing.

Why only back test for 60 days and not years?

Thank you

Was watching a video made by @kevinkdog this morning when he showed this great chart, which illustrates nicely the relationship between Risk Reward and Win%. (You can't talk about one of those without the other!). Wasn't sure where to post it but this seemed like a good thread, even if it is two years old now.




Full link to the video. (Its the website not me making it so large!) Kevin does a great job talking about trade statistics using the 30 odd systems he trades as an example.. also a great picture of Kevin himself!

I would say the best risk to reward for me, from my personal experience, is 1:2. It eases the mind and offers you an easy enough target and stop loss IF you’re taking trades from valid areas.

SMCJB 

Was watching a video made by @kevinkdog this morning when he showed this great chart, which illustrates nicely the relationship between Risk Reward and Win%. (You can't talk about one of those without the other!). Wasn't sure where to post it but this seemed like a good thread, even if it is two years old now. Full link to the video. (Its the website not me making it so large!) Kevin does a great job talking about trade statistics using the 30 odd systems he trades as an example.. also a great picture of Kevin himself!

The chart is nice but it's worth mentioning that even if a strategy has positive expectancy, the game changes when the bet becomes a function of the capital.
Mathematically you can take a RR/winrate relation that makese sense and when you risk too much (as a function of your capital), the equity goes to zero.
This is the the F_c value in paper by Kelly..... I recently read this in a book by Minervini (see below), and I think it is often overloooked.

Thanks @SBtrader82 very interesting. Counterintuitive but correct. If people are wondering about the Math ...
(1.04)^4 * (0.98)^6 = 1.03631 = 3.631% expected return
(1.42)^4 * (0.79)^6 = 0.98836 = -1.164% expected return