At investment conferences, the hottest speakers are those who provide information about high probability entry techniques. If you say, "Trade with the odds on your side" and show someone a technique that is right 75% of the time, you’ll get a large audience. Yet most techniques of this nature usually have big losers and may not even make people money over the long haul.  Nevertheless, being right 75% of the time is all it takes to get people to trade them.

Some of you might be saying, "How could you be wrong 90% of the time and still make money?" The solution goes back to the golden rule of trading, "Cut your losses short and let your profits run."
 
Let’s say that you make nine losses of $100 each, and you make one profit of $2,000.  Your nine losses sum to a total loss of $900.  When you subtract that from your single $2,000 profit, you get a net profit of $1,100. That’s a huge profit, but you only made money on one trade out of ten.  And while most good trading systems don’t lose 90% of the time, most good trading systems probably make money on just 30-40% of their trades.

My guess is that 99% of the trading population could not trade a system that would produce 90% losses, not matter how profitable it is.  The reason is because they don’t get to be right enough. They have too many losing streaks. They have losing streaks that are longer than five in a row. Most people cannot tolerate long losing streaks. When these losses occur, traders totally abandon what they are doing. In such a system you could easily have 25 consecutive losses. At that point you become certain that your system is broken, and you try something else.

Let’s look at the opposite end. Suppose you got to be right 90% of the time. Suppose you make 100 trades and your average win was $100 while your average loss was $2,000. You make money on 90 trades, giving you a total of $9,000 in winnings, while you lose money in ten trades, giving you a total of $20,000 in losses. Overall, you would lose $11,000. Would people trade that system? Yes, they would.  And if the system only made four or five trades each year, they would probably trade it for a number of years until they went bankrupt. Why? Because they get to be right most of the time and that is very rewarding.

You might be saying, but how could people possibly tolerate losses of $11,000 after 100 trades? It is easy; they turn the losing trade into a long-term investment in their mind and say, "It’s only a paper loss." For example, I’ve had workshop attendees who were probably way above average in terms of sophistication. However, I asked them to raise their hands if they had an investment in their portfolio that was only worth 50% or less of what they paid for it. Eleven people raised their hands—over one-fourth of the class. And my guess is that among the overall population of investors, most people are sitting on a number of big losers, hoping they will come back. Why? Because they cannot stand to be wrong on an investment, and they are waiting to be right on those losing trades.

What is the cost of having losing investments in your portfolio? It’s major. First, you are using valuable capital up with nonproductive investments. Second, you are missing many good opportunities.

What Happens When You Have a “Bias to Be Right”?

When you have a bias to be right, the first thing you do is cut your profits short.  For example, suppose you are in a trade and it starts to make money.  The trade is up for three days in a row and you are up $500.  Suddenly, on the fourth day, the trade is down $150.  Now you are up only $350 and you think to yourself, “I’d better sell this pretty quickly because it might go down some more and I’d lose all my profit.”  What are you doing?  You are cutting your profits short, the opposite of the golden rule of trading, which says to let your profits run.

Now, let’s look at the other side of a trade, the down side.  Suppose you buy 100 shares of a $50 stock.  You are a good trader and you decide to sell if the stock drops to $45.  Thus, you are only risking $500 on your $5000 investment.  But what happens when the stock actually drops to $45?  You suddenly say to yourself, “If I sell now, it’ll probably go up tomorrow and I’ll be stuck with a $500 loss.  I think I’ll wait a day or two and see if the stock doesn’t go up.”  Two days later the stock is now at $41 and you have a $900 loss on the stock.  And if it was hard for you to take the $500 loss, it’s even harder now for you to take the $900 loss.  What do you do?  You say, “I know this must be the bottom.  It’s a much better buy here at $41 than it was at $50 and everyone must know that.  I can’t possibly sell now.”  So you don’t sell.

A week later the stock is at $29 per share.  What do you do?  Your loss is now $2100.  And if taking a $500 loss was hard, then how could you possibly take a $2100 loss?  It’s impossible.  Now you rationalize to yourself.  “This will end soon.  I’ll just put this away for a year or two.  Besides this stock is a fantastic bargain at $29.  I’ll just put this stock away and take a long-term view of things.” 

It’s now three years later.  Your stock is still around but it’s been unlisted, and it’s selling for 25 cents a share.  You’ve lost $4975.  You are a long-term investor, hoping that one day you’ll be right about this stock.

Why Being Right Seems So Important

There are two primary reasons why we focus on being right. First, we are conditioned to be right by the school system. In school you are taught that there are right answers and wrong answers. What is a right answer? If you learned how to survive in the system, you learned that a "right" answer was whatever the teacher wanted.

Your performance is measured periodically through tests in which you are asked to pick the right answer. If you cannot get more than 70% right on the test, you are labeled a failure and ostracized. Your humiliation might even be public, in front on all your friends. And if your humiliation isn’t revealed to your peers, it certainly is displayed elsewhere. Your "poor" performance goes home in the form of a grade with a comment that "Johnny is a little slow or Johnny is bright, but he just doesn’t try." Usually, at this point, the most important people in your young life get involved—your parents.

Even if you understand the system and work hard to know the right answers, you still might be taught that your performance is not good enough. It usually takes a score of 94% correct to get an excellent grade. But how many children go home and show their 94% test to dad only to get the response, "Why didn’t you get 100%?"

Thus, it is no wonder that traders want to be right all the time. And being right usually costs them dearly in terms of profits. Whether you’ve been through 20 years of schooling and have a graduate degree, or less than 10 years of schooling, you still have the same conditioning about being right.

The second reason people want to be right is that service providers for traders and investors feed the bias to be right. For example, software vendors tend to provide systems that can be highly optimized. Once you’ve optimized your trading, you can lay a line over the prices and see exactly where you should have bought and sold. It seems obvious. However, the same optimized system does very poorly when applied to the real world.  Nevertheless, the system attracts people because they think they get to be right.

We previously ran an ad for our systems development course on How to Develop a Trading System that Fits You.  Research has shown that the best traders in the world distinguish themselves by developing a trading system that is right for their personality and their beliefs about trading.  And our course is designed to show people how to do it.  Now, you’d think that would be attractive to people, wouldn’t you?  But compare that with a headline that someone who’s developed an optimized trading system might offer:  Amazing Trading System: Right 85% of the Time.  Now, which of those two headlines are you more attracted to—buying a course on how to develop a trading system that fits you or buying an amazing trading system that’s right 85% of the time?  Well, most people are attracted to the “amazing system” even if it never makes them a dime.  Why?  People have a bias to be right and the amazing system appeals to their bias.

The Solution: Expectancy

To survive in the real trading world, every trader must learn about the concept of expectancy.  On every trade you make you need to have an exit point—some point at which you decide you are wrong about the trade and will get out.  Let’s say that this is your worst-case risk in a trade or R for short.  Let’s say that if you take your worst-case loss, you’ll lose $100.  That means that a 1R loss is $100.

Now that you understand this concept, you can express all of your trading results as a multiple of your initial risk or as a set of R-multiples.  Table 1 shows some trading results expressed as R-multiples.

Table 1 – Trading Results As a Set of R-Multiples

There are several interesting aspects to the table.  First, 90% of the trades are losses, but we take the minimum loss of $100 each time.  Second, we have one gain, but that is $2000 or 20 times our initial risk.  The net result is that we make a total profit of $1100 over the 10 trades, even though 9 of the 10 were losers.

And notice that we can express each of the trades as a multiple of the initial risk (i.e., R-multiples).  When we do that, we notice that the average gain over the ten trades is 1.1R.  This is called the expectancy of our system.  In other words, we can lose 90% of the time in our trades and still have a positive expectancy.

Whenever you look at a trading system, start to think of it as a set of R-multiples.  Once you’ve done that, then ask yourself “What is the average R that this system will give me?”  That average R is your system’s expectancy.  And if that average R is a positive number, then you probably have a money-making system.  The bigger the expectancy and the more trades it generates, the better results you’ll have over a large number of trades.  That’s how to get around the bias of being right.