This article originally ran in November 1997 edition of Technically Speaking.
Imagine playing a game for money in which marbles are drawn out of a bag and then replaced. Sixty percent of the marbles are white. If one of the white marbles is drawn out, you win whatever you risked. The other forty percent are blue. If one of the blue marbles is drawn, then you lose whatever you risked. This game has an expectancy of 20 cents. That is, over a large number of trials, you’ll make 20 cents for every dollar you risk. That means it’s much better than any game you’ll ever play in Las Vegas. But what percentage of the people who play it make money?
I have introduced this game numerous times in talks that I’ve given and at seminars and conferences. Typically, we don’t play for real money, but the winner (i.e., the person who ends up with the most “money” after 50 trials) is given a prize. The results of a typical game are that one third of the audience ends up broke, another third of the audience loses money, and only a third of the audience makes money.
Ralph Vince, author of three books on money management, allowed 50 Ph.D.s who knew nothing about money management or statistics to play a game similar to the one described for 100 trials. They were not given any incentive for winning (which can cause stupid behavior). They were merely instructed to make as much money as they could playing the game. Guess how many of them made money? Only two, or 4%, made money!
Typically, except for going broke, there are as many different ending equities as there are people in the audience. Yet they all start out with the same amount of money and they all get the same trades (i.e., marbles). But. in the end, there are so many different results. Why? Poor money management and an undisciplined psychology. If people have trouble making money with a 60% marble system, what are their chances of making money in the market? Very slim!
There are only three critical factors to winning:
- A positive expectancy system,
- Money management, and
- Individual psychology.
All three factors tend to be neglected by the average trader. To illustrate why that occurs, I’ll use psychological biases to explain why people have problems with positive expectancy systems and money management, rather than treat psychology as a separate topic.
Traders Don’t Understand What a Positive Expectancy System Means
Problem I: The Need to be Right
Most of us grow up being exposed to an educational system that brainwashes us with the idea that you have to get 94-95% correct to be excellent. And if you can’t get at least 70% correct, you’re a failure. Mistakes are severely punished in the school system by ridicule and poor grades. Yet, it is only through mistakes that human beings learn.
Contrast that with the real world in which a .300 hitter in baseball gets paid millions. In fact, in the everyday world few people are close to perfect and most of us who do well are probably right less than half the time. Indeed, people have made millions on trading systems with reliabilities around 40%.
William Eckhard, in his marvelous interview in the book “New Market Wizards,” by Jack Schwager, says that the factor that most undermines the behavior of average trader is the overwhelming need to be right about the current trade. This one factor undoes most of us whenever we attempt to challenge the market.
Because of that factor, people are constantly looking for high probability trading systems; systems that make money 70% of the time or more. To find such systems, they are constantly looking for entry systems that produce such high reliability. If you teach such high probability entry systems at seminars, you’ll attract thousands of eager followers. You’ll only have to skim the subject of exits and money management in such a talk, because people think the secret is in the entries.
Unfortunately, if you really examine these high probability systems, you’ll notice the following:
1) The presentations go over well because they are illustrated with numerous best-case examples;
2) Exits are hardly mentioned except to state that you have to have a trailing stop; and
3) If you really put such systems to the test, the expectancy is not very good because most of them leave average losses that are bigger than the average gain.
Problem 2: We’re Conservative with Profits and Risky with Losses
The systems that do perform well tend to be systems with a reliability of around 40%, which have average gains that are much bigger than the average losses. Understanding and properly applying protective stops and profit taking exits is important to develop such systems. However, these exits are very difficult for the average person who tends to be risky when he or she is behind and conservative when he or she is ahead.
Let’s look at an example. Which would you prefer?
- A sure loss of $900 or
- A 95% chance of a $1,000 loss plus 5% chance of no loss at all?
Select either (1) or (2). Which do you pick?
Now let’s try one more. Which would you prefer 1) a sure gain of $900 or 2) a 95% chance of a $1,000 gain plus a 5% chance of no gain at all? Once again, select either (1) or (2). Most people would take the gamble in the first problem. They would take the 95% chance of a $1,000 loss plus the 5% chance of no loss at all. Is that what you picked?
Let’s take a look at how that works out. If you multiply $1,000 times 0.95, you get an expectancy of $950. That means you’ve elected the worse expectancy, a loss of $950, just for the remote possibility of getting back to even. Yet what is the first part of the golden rule of trading? Cut your losses short.
What did you pick in the second problem? Most people pick the sure gain of $900. Yet if you look at the gamble, item 2, it gives you an expectancy of $950 ($1,000 * 95% = $950). But that goes against the way most people think. They’d rather take the sure profit than be risky when they are ahead. Yet, what is the rest of the golden rule of trading? Let your profits run.
Great trading systems with a high expectancy are formed with the proper use of exits. But when the proper use of exits goes against the grain of how we tend to think it is very difficult to develop a good system.
Problem 3: People tend to abandon low-probability, high expectancy systems when they do manage to come up with one
Unfortunately, high expectancy systems, once developed, are also the most difficult for people to follow. What is likely to happen to a 40% system, generating 350 trades each year, over a three-year period? Well, during those three years it will generate about 1,000 trades, and during those 1,000 trades, it will have a string of losses in the neighborhood of 15-16 in a row. I know of few people who would not abandon a system that has 15 losses in a row as being broken even though that many loses can be expected by chance during a sample of 1000 trades.
People Totally Neglect Money Management
Money management is that part of your trading system that tells you how much. It’s not that sexy. It doesn’t seem to give you control over the market, like your entry method. It simply tells you how much to risk on a given trade. Yet academic research has shown that asset allocation (another fancy word for how much) will account for over 90% of the variance of the performance of portfolio managers. You’ve already learned from the marble game that many people can lose money in a 60% system, just from very poor money management. So why is the appropriate use of money management such a problem?
Problem 4: The Gambler’s Fallacy
How can you lose money in a sixty percent system with a one-to-one payoff? In a sixty percent system, you are likely to have seven or eight losses in a row during 1,000 trials. But you could easily have five losses in a row in such a system during a 50-trial run. Let’s say that we are about to start such a streak and that you’ve adopted a strategy of betting 10% of your equity. For the sake of simplicity, let’s say your stake when the losing streak starts is $1,000. You begin by betting 10% or $100 and you hit the first loss. You now have $900 left. You decide to bet $90 and you have another loss. You now have $810 left. After the third loss, you decide to bet $81 and we have our third consecutive loss. Now you have $719 left.
At this point, your thought process might be the following; “We’ve had three losses in a row and we’re really due for a win now. After all, this is a 60% system. I’ll risk $300 on this one.” Now you get loss number four and you only have $419 left. You feel desperate. You are down almost 60% in just four trials. You think, “We have to have a winner now,” and you decide to risk another $300. Loss number five comes up and you are down to $119. You now have to make nearly 900% just to make up for the losses on the last five trials and your chances of doing so are very slim.
Some of you might be thinking, you should have waited until the five losses in a row and then bet $300. If that’s your thought process, you have the same problem as the original trader. It’s called the gambler’s fallacy. Your chances of losing on any given draw are 40%. They have nothing to do with what happened in the past. When you think that way, just as you bet $300, you’ll have the sixth straight loss.
Problem 5: Money Management is complex
The science of money management is every bit as complex as the art of entry into the market. Furthermore, since few people are interested in money management, the software vendors who sell system-related software have neglected it or ignored it entirely. As a result, if you want to practice sound money management in today’s world of computers, you must do it yourself on a spreadsheet. However, a colleague of mine is currently in the process of developing software to remedy this problem.
From my research and other sources, I know how a number of “market wizard” caliber traders function. They have good systems with a strong positive expectancy. But those systems are not much different than the kind of systems that the average person can get. The difference between making a fortune in the markets, as most of them have done, and average performance is simply one of money management. Great traders apply great money management to good systems and have the discipline to carry it out. Just read the book Market Wizards, by Jack Schwager. Every person interviewed talks about the importance of money management.
Several years ago, I spoke at a Market Wizards conference in San Francisco. One of the speakers, Ed Seykota, emphasized money management in his talk. He suggested to people that they calculate payoff vectors for their system and develop money management appropriate to those payoff vectors. By payoff vectors, he meant what percentage of your trades are 10:1 winners, what percentage are 5:1 winners, etc. Yet, when someone asked him, “How do you develop the appropriate money management to those vectors?” His response was to point to the side of his head and say, “Think.”
Most traders find that the simplest solution to money management is simply to trade one contract per so much equity. While this is one solution, for traders with small amounts of money (i.e., most traders), it amounts to no money management because it means that they effectively have to double their account equity before they can increase their risk.
Problem 6: Most traders don’t have enough money
In that same conference, Ed Seykota made the statement that anyone risking more than 3% of his or her equity on a given trade was probably a “gunslinger.” Now, your risk on a given trade is the amount of exposure you have on that trade; the difference between your entry price and your stop price. For example, if you enter in a gold position at $400 with a stop at $390, then your $10 stop represents a risk of $1,000. If you had an account of $25,000, then your risk for one contract would be 4%. You’d be called a gunslinger.
Most traders enter into the market with accounts of $10,000 or less. They trade just about everything and all of their trades are very risky because their account size is too small. Sure, you can trade some agricultural markets with a $10,000 account. In fact, you can trade a lot of other markets if your stops are typically tight and your system is designed for tight stops. But most people who enter the market simply don’t have the money to do what they are trying to do.
Consequently, they typically don’t think about the most important factor in trading, the issue of how much, because they are already trading too much. If they do survive in the market, as their account begins to grow, they start thinking about the simplest form of money management. “I now have $20,000 in my account; perhaps I should trade two contracts?”
What’s the Solution?
Each of the six problems I’ve covered stem from major psychological biases that shape our thinking. The first step in overcoming those problems lies in recognizing that they exist. For example, once you recognize that a key issue in successful trading is having a high expectancy system rather than a highly reliable system then you’ve come a long way in your search for the Holy Grail. You can start looking for exits that give you a high expectancy, rather than entry techniques that increase the reliability of your system.
Second, when you have a high-reliability system that gives you many trades, you’ll begin to realize that the key to achieving that expectancy is money management. If you know what you want to achieve as a trader (e.g., a high reward-to-risk ratio, low drawdowns, or a very high annual return rate, etc.), you can use money management to design a system that will achieve those objectives.
I’ve written a report on money management detailing three different equity models and nine different money management models giving a total of 27 different models. The report also touches on creative money management, showing just how much is possible in this area. The key to the Holy Grail is in applying money management to a high expectancy system and in controlling yourself. When you realize this deep inside, you’ve taken a giant leap forward in your personal evolution as a trader.
Van K. Tharp, P.D is an internationally renowned investing and trading coach. He’s written a Peak Performance home study course for traders and investors; published a monthly newsletter and leads seminars. https://learn.vantharp.com/
