Lessons from the Pros


Successful Trading is Ultimately a Numbers Game

In last week’s article, I wrote that one of the golden rules of trading is to cut losses short, and let profits run. The reason this rule is tried and true (if one wants to be successful in trading) is simply because the lack of adherence to this basic tenet is just bad math. A trader needs to understand that ultimately, trading is about having the numbers skewed in his favor. Unfortunately, our human emotion of fear and greed gets in the way of thinking that profitable trading is a purely mathematical exercise.

You see, as humans we hate to lose, and we don’t like being wrong, these traits lead us to hang on to trades hoping that we’ll eventually be proven right.  These natural human instincts, also lead us to take profits quickly, as these give us a “good feeling.”  The problem (from a purely mathematical standpoint) is that having many small profits followed by a big loss, statistically will not produce consistent profits.  The percentages also make it tough to make money.

As an example: if a trader starts a futures account with a $10,000  balance, and makes an average return of 10% per week, this would equate to a 40% return for the month, which is very good.  He would start his second month of trading with an account balance of $14,641. If in month two this trader becomes reckless with his risk management and does things like pulling his stops, or adding to losing positions, and ends up losing 40% for his second month of trading, his new account balance is now $8784.00. Some of you are probably thinking: wait a minute, how can his account balance be lower after losing 40% when he just made 40% the month earlier?  Yes, compounding works both ways.  And here’s the rub, this trader now has to make 66% for the next month to regain his high watermark.

Needless to say, an understanding of how good versus bad  math works is important, because  then we can commit to no longer taking big loses, and letting our winners run.

In order to skew the math in our favor, we mustn’t be as concerned about how often we’re right, but we  should be more interested in how much we lose when we’re wrong, and how much we make when we are right.  Let’s look at how that math would work.  First, let’s start off with a sample size of 30 trades. Then, let’s assume that we are going to be right only half the time. In other words, our win/loss ratio is 50%. Now here are the two most important inputs of this equation: when we’re wrong , we lose $1.00, and when we make a profit we make $5.00.  Put another way, we put in a lot of effort to lose very little, and when we have a profit it has to be at least five times as big as the loss.  Some of you are already thinking that these ratios are tough to attain. Well, these ratios can be achieved only  if the strategy you’re using puts your entries in the lowest risk possible (the turning points).

If we do the math on the aforementioned example we find that we would have lost $15.00 (50%of 30=15) and made $75.00 on the winners (15×5=75). If we subtract our losing amount from the winners, we end up with a net amount of $60.00. Keep in mind, that in this example, we were wrong half the time and would have still made a nice profit.

Of course these are just numbers, and in order to achieve them; we need a solid strategy, and to execute it consistently. So at the end of the day, trading is just a numbers game so we better know the difference between good and bad math. Incidentally, you don’t need a degree in algebra to figure this stuff out, just some good old fashion common sense.

Until next time, I hope everyone has a great week.

DISCLAIMER This newsletter is written for educational purposes only. By no means do any of its contents recommend, advocate or urge the buying, selling or holding of any financial instrument whatsoever. Trading and Investing involves high levels of risk. The author expresses personal opinions and will not assume any responsibility whatsoever for the actions of the reader. The author may or may not have positions in Financial Instruments discussed in this newsletter. Future results can be dramatically different from the opinions expressed herein. Past performance does not guarantee future results. Reprints allowed for private reading only, for all else, please obtain permission.