Great insight there… I have never looked at the factor of trade frequency in relation to risk reward and win rate…
Currently GBP/USD is trading at 1.6214,5…just to put a 10 pip SL into some prospective here.
A 10 pip move in GBP/USD = 0.062%. In simple terms you are giving yourself a 0.062% relative degree of breathing space. Really?
I would agree that if you’re risking 10 pips or less, slippage could mess things up…which is why you have to build the system from the ground up to be able to withstand things like the commission/spread cost and slippage. My thought is that you do something like use a trailing stop that kicks in and follows price up once the 1:2 R/R is hit. If your target was 20 pips, sometimes the trade would end up closing out at 22 pips or 25 pips or 28 pips. You just round all of these down to 20 pips “to be conservative” when gathering your historical testing data and when all these little extra pips here and there are gleaned, they make up for slippage. Some brokers, like FinFX, allow you to keep positive slippage as well, so this would help mitigate the impact of this nasty little factor over the course of many trades.
If you want to be even MORE conservative, if you build the system and it averages 300 entry signals p/month and when everything comes out of the laundry and you only end up with a 1.8 R/R ratio with the same 40% win ratio…well, on 300 trades you’d STILL doing a lot better than most. Right?
While it may seem that 0.062% “breathing space” isn’t very much, I think that short term systems (when executed as designed) have a different type of breathing space built in. Two types to be exact. Let me explain.
First of all, if historical testing gathers together the results of 5,000 trades and they show a 40% true win ratio (that is, with the break-even trades excluded) and a 1:2 R/R ratio….well, that’s a LOT of weight in that particular average. This isn’t a swing trading system that generates 60 signals in a year….we’re talking 300 signals in a month. Markets do change, but they’d have to SIGNIFICANTLY change in order to bring the average down close to 0.35 percent and that’s how far it would have to fall before the system would only become a break even system. Maybe even more since 33% is the break even point without commission or slippage factored in. If you had a high enough trade frequency (say 600 trades in a month),then a 35% win ratio might still be profitable. So while the 0.062% buffer you see on the screen isn’t very large, the win ratio buffer is QUITE large if you have a massive amount of data pinning the win ratio at 40% when measured across many months and a plethora of diverse market environments. Furthermore, there’s just as much of a chance that the market could change so that the win ratio INCREASES so that it’s higher than 40%.
The second type of buffer is even better. When trading on the M5 charts and targeting only 20 to 24 pips and risking 10 to 12, then what you’re doing is tapping into peoples “now” reactions to greed and fear – greed being the more important of the two. Again, the large sample size of the system showing a 40% true win rate is basically establishing the following statement, “I know that on this pair, when I see this particular entry signal I can be confident “enough” that people are “getting’ greedy” in a long direction or “getting’ greedy” in a short direction that if I jump in with a 10 pip stop loss I’ll be right 40% of the time and score a 20 pip winner.”
This is really key because the BASIS for this statement is the psychological metic of greed which people have demonstrated in a particular market. With a 5,000 trade sample that is winning 40% of the time, that means that in order to significantly decrease the system’s performance (assuming that you don’t blow it up yourself by committing any cardinal trading sins) is that the people themselves would have to begin thinking in a different way! They would have to become less greedy in order to demonstrate less greedy behavior in the market. In order to become less greedy they would need to be convinced that the resources available to them are pretty much limitless and they don’t have to get greedy because they can pretty much go out whenever they want and get what they need just by picking it off the shelf. Short of this situation (known commonly as utopia), they will most likely demonstrate the same type of thinking and the associated market behavior patterns seen in short time frame charts indefinitely. Since Jesus Christ has not setup his Millenial Kingdom yet, we are not in a position of utopia so the large sample size would tell me that I can rely on the behavior patterns of the people themselves to serve as an alternative buffer which increases the reliability of the system from behind the scenes so that the true buffer is greather than the static 0.062% figure seen on the screen.