Win or lose– does your trading make you feel like you are on a roller coaster? There is a reason for that.
I kinda knew the why in the back of my mind. But, Mark Melnick from T3 Live in his YouTube videos made it abundantly clear to me as to the why.
First, let us imagine you win 60% of your trades and your risk and reward are about even. That is a good sized edge. Most common technical methods will only yield a 2% to 5% edge, i.e. 55% win ratio. So, you have a real edge here.
It sounds good on paper, at least. However, let’s imagine you want to target a fairly modest 50k per year trading.
If we assume that your system generates 100 trades per year then you will need to risk $2,500 per trade and your expectancy will be $500 per trade. You will risk a total of $2500*100=$250,000 on this one system to achieve that return.
However, here’s the rub: with a 60% win ratio then you are only expected to win 1 trade more then chance would imply out of a 10 trade sequence. Out of a 100 trades, your expected profits essentially come from winning 10 trades more then chance! Of course, this also means you have 10 less losers.
The point that any trade is pretty much a coin flip. In fact, in the first simulation, one of the first 10 trade sequences was all winners. The fact is that if most traders won their first 10 trades with a new method they would think they hit the holy grail! But, another starting sequence was mostly losers!
If you lost 8 of your first 10 trades, would you be inclined to stop trading or question your method? Would you be able to keep trading even?
It gets worse though. We can never know whether or not we have an edge in the markets and most technical systems are necessarily simplified models. It means one should never blindly believe a model.
Notice, this is one of the big differences in discretionary vs system trading. In discretionary trading, if you have proven an ability to read and call markets over a long time then you can have higher confidence in your model but less certainty of the expectancy. A systematic strategy provides you the trader with greater certainty of the expectancy but less faith in the model. The goal is the right balance in model confidence and expectancy confidence.
So, what are you potential solutions to getting off the roller coaster?
Let us look at the trade more systems approach. In this same example, what if we only took the best 30 trades the system produced. Do you think our metrics would be slightly better? They should be.
Let’s imagine it boost our win ratio to 65% and then it follows we will only need to risk $1650 per trade. Of course, to hit our 50k goal we will need ~4 systems. The other benefit is we are only risking 50k per system versus 250k (30*1650=$49.5k versus 2500*100=$250k in the prior example). The risk per trade still seems high to me– so it also suggests you need more total trades or higher R factor, as well.
The solution seems to be simply this:
For your discretionary trades, you must find ways to get more edge. You need to take higher quality trades and boost your win ratio. If you are struggling then I can guarantee you aren’t winning 80% of the time.
For your systematic trades, then you must improve your systems to take higher quality trades and build & trade more systems.
The author is passionate about markets. He has developed top ranked futures strategies. His core focus is (1) applying machine learning and developing systematic strategies, and (2) solving the toughest problems of discretionary trading by applying quantitative tools, machine learning, and performance discipline. You can contact the author at firstname.lastname@example.org.
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