When a person first gets interested in stock market trading, it’s very natural to begin thinking thoughts like “How can I make trades, so that I can win most of the time” or “I’ve got to find a method that wins at least 80% of the time otherwise I’ll probably lose money” or even “This guy says he makes lots of money trading, but only wins 40% of the time. How absurd, he must be lying.”
It hurts to be wrong. You’ve learned that your entire life…from making bad scores on tests in school to making mistakes on important work at your job. Make bad decisions 60% of the time and you are considered a failure.
But, is that how it is in stock market trading? Do you have to win on a majority of your trades to be a success? Do you have ring the cash register on most of your trades to see the balance on your account rising over the long term? The answer is a big NO. It is a common misconception that you have to have many more winning trades than losing trades to be successful in this business.
I’m here to tell you that stock market trading is different, and success is not entirely defined by percentage of winning trades.
I’ll start with a quotation from a wise man that’s appropriate for this page on Expectancy:
For many, trading can be quite an enigma. But, if you learn some basic trading math, it starts to make better sense.
I felt the same way when started, but I quickly realized without knowing anything about expectancy at the time, that being right on as many trades as possible, was only part of the stock market trading equation.
My account was going up, but I had a lot of losing trades. Of course, I hated having losing trades, but as long as my account was getting larger I was happy. Well, not real happy, because at the time I remember feeling like “If I don’t have at least 85% winning trades, I still must be doing something wrong”.
That’s probably along the same line of what you’re thinking, right?
Well, that’s where Expectancy comes in. The formula for expectancy will show you that the win%, while important, is only part of the stock market trading equation.
If you hate math don’t worry. This is all really quite simple and I’ll give you some easy to understand examples.
This is the equation for Expectancy:
Expectancy = ( W% x AW ) – ( L% x AL )
W% = percentage of winning trades, L% = percentage of losing trades, AW = average of winning trades, AL = average of losing trades
EXPECTANCY EXAMPLES and EQUITY CHARTS
Keep in mind, that all of the following examples will not include commissions in order to keep the explanation as simple as possible.
In this first example, I’d like you to see that it is quite possible for a stock market trading system to make money with a low percentage of winners.
A trader’s methodology has the following stats over many trades. Only forty percent of his trades are winners, but his average winning trade is three times higher than his average loser. Which means his reward to risk ratio is 3:1
And that folks, makes all the difference. Lets calculate the expectancy of his system.
W% = 40% L% = 60% AW = $300 AL = $100
Expectancy = ( .40 x 300 ) – ( .60 x 100 ) = $60
The expectancy is positive. This means that over the long term he can expect this methodology to produce a net profit. As you can see in this example, even though this trader’s system only has 40% winners, he is still able to generate a nice profit.
When you have access to all the data you can also take the net profit and divide it by the total number of trades to get the expectancy.
The following chart is made up of five artificially generated equity curves, from over 450 simulated trades for each line, using the numbers from the above example. You can see that all are positive, even though only 40% of the simulated trades of each equity curve are winners.
A trading system with a high win% should be great to trade, right? Not always.
In this next example, a trader has a system that has alot of winning trades (80%), but keeps having some large losses. His losses, although only 20% of the time are on average five times larger than his winners. Not good.
Lets check out the expectancy of his trading system. His system statistics are:
W% = 80% L% = 20% AW = 100 AL = 500
Expectancy = ( .80 x 100 ) – ( .20 x 500 ) = $-20
A negative expectancy. As you can see, having a high percentage of winners is only part of the stock market trading picture. The size of his losing trades are just too high to give this system a positive expectancy.
If this trader continued to trade this high winning % system, below is what his equity curve could look like. Not a pretty picture.
Now in this next example, a trader has the type of trading system that every trader dreams of.
His stats are:
W% = 85% L% = 15% AW = 200 AL = 100
Expectancy = ( .85 x 200 ) – ( .15 x 100 ) = $155
His system has a high W% and the winners on average are twice the size of the losers. Fantastic numbers right?
There’s only one problem. Too bad the trades only occur at a frequency of once every other month ……. and he’s a day trader. So you see – how often a method trades has a lot to do with how good a system is. It doesn’t matter that the system has such a great expectancy, because the trades come so infrequently. I’d rather be trading a lesser method that has lots of trades.
So basically, stock market trading is really a numbers game. We’re looking for methods or systems that give us some decent numbers while at the same time trade often enough to take advantage of those numbers. Glue that together with some position sizing and rock solid trading discipline and you have a good shot at being a success.
Oh, and just for kicks here’s what your equity curve is going to look like if can create a day trading system like in this last example, that trades every day. 😉
If you’d like to try some different numbers out, you can find this equity curve generator at HQuotes.com