As I’ve mentioned, we have a limited capacity for processing information. In fact, consciously we can hold seven (plus or minus two) chunks of information. That number is reduced dramatically under stress, when blood flow is diverted from the brain to the major muscles of the body to deal with approaching danger. In today’s world, the danger is usually mental, and being able to run faster or perform feats of strength doesn’t help us deal with trading dangers.
Every year the total amount of information we have to deal with as traders doubles, but our capacity stays the same. As a result, we’ve developed a number of shortcuts (that is, heuristics) to process information. In fact, psychologists have been documenting many of them over the years and have been calling them “judgmental heuristics.”
The overall conclusion is that human beings are very inefficient at processing information. In fact, some economists have begun to move away from the efficient market camp into the idea that markets are inefficient. They are inefficient because humans are inefficient decision makers.
Their conclusion is excellent, but what they’ve done with it is not. What’s happened is that a new school of economics—behavioral finance—has sprung up. Now economists are asking, “If markets are not efficient because humans are inefficient, how can we use what we now know about human inefficiencies to predict what the markets will do?” In my opinion, this is lunacy.
You might call what I do with traders “applied behavioral finance,” and I take a different approach. I say that if most human beings are inefficient in the way they process information, what would happen if you made them efficient? Let’s say a human being is 5% efficient in dealing with market information, although this is probably a high estimate for most people. What would happen if I could make a person 25% efficient? What would happen if I could make that person 50% efficient or even 100% efficient? The results might surprise you.
I previously talked about how trading systems may be considered a distribution of R multiples with a mean (that is, expectancy) and standard deviation that characterize the distribution. Let’s look at what inefficiency might do to the trading results from that distribution. Let’s return to our system that gives you an expectancy of 0.8R and generates 100 trades each year. That system is not unrealistic. In fact, our sample system was barely a tradable system. I’ve seen much better systems. Yet that system, on average, will generate a return of 80R per year.
If you were to risk 1% per trade, you probably could make 100% per year trading it (that is, 1% gets bigger as your equity grows, which is why you could make 100% instead of 80%). However, because of behavioral inefficiencies, most people will make lots of mistakes, where a mistake means that documented trading rules were broken. What’s a mistake worth? I don’t know for sure. We need to collect a lot of data to figure that out, and it’ll be different for everyone. However, for now, let’s say a mistake is worth on average 4R.
If that’s the case and you made a mistake on every other trade (that is, 40 mistakes per year), then you’d have 160R worth of mistakes. You’d lose money trading a system that potentially could give you 100%.
In contrast, let’s say you make only one mistake a month (most profitable traders probably do that). If you make a mistake a month, that’s 48R lost out of 80R, leaving you 32R in profits. During a severe drawdown in the system, you might give up on the system, thinking it no longer works. Our system generates about seven to eight trades per month, and so we could say that this trader makes one mistake per eight trades in executing the system; in other words, she’s 87.5% efficient in terms of mistake-free trades. However, in terms of profits, she’s made only 32R out of a potential 80R. Thus, in terms of profits, she’s only 40% efficient.
What would happen if she could become 60% efficient in terms of profits, or 80%, or more? The increase in return would be phenomenal. Perhaps it’s time to read about some of the common inefficiencies that human beings have and learn how to become more efficient as a trader. Follow the suggestions in this book and you’ll become much more efficient.
A mistake occurs when you don’t follow your written trading rules. If you develop a working business plan to guide your trading, you’ll have numerous rules that you’ll need to follow. If you don’t develop such rules, everything you do will be a mistake.
I’ve been asking the traders I coach to keep track of their mistakes in terms of R. For example, if you enter the market on emotion and make 2R, that counts as +2R toward that mistake. If you do it again and lose 4R, you now have −2R toward that mistake. If you do that for about a year, you’ll have a good idea about how efficient you are as a trader and what your efficiency costs you.
One of my clients was a futures trader who was running a $200 million account. We estimated that over one nine-month period he made 11 mistakes, costing him 46.5R. He made 1.2 mistakes per month at a cost of 4.23R per mistake. Overall, his profit was probably 50% less than it could have been because of mistakes. Thus, if he made 20%, he probably could have been up 70%. Can you begin to see the impact of such mistakes?
Another client was a long-term position trader who primarily traded ETFs with wide stops. In a year of trading, he made 27 mistakes, costing him 8.2R. Thus, over a year he made 2.25 mistakes per month. However, because he was trading long term with large stops and no leverage, his mistakes were not as costly. Each mistake was costing him 0.3R. During the year of trading, he was up 31R (and about 30%). If he had not made any mistakes, he would have been up 39.2R. Thus, his mistakes cost him 20% of his profits.
A third client was just starting to swing trade, and many of his errors were beginner types of mistakes. Over the course of his first year of trading, he broke even, but he made 28 mistakes during that year costing him a total of 31R. Had he traded at 100% efficiency, or even 95%, his first year would have been quite profitable.
We might be able to guess that mistakes are worth 4R to a futures trader, 1R to an equity swing trader, and 0.3R to a longer-term position trader. However, this is still just speculation. What are your mistakes costing you?
I’ve always said that trading is mostly psychological and that traders should spend a lot of time working on their core issues. In fact, most of my Super Traders spend at least a year working on psychological issues before they get to work on their business plan or trading systems. One area where psychological issues can appear in trading is in mistakes.
So let’s look at the psychology of trading from the angle of mistakes. When you don’t follow your rules, you make a mistake. It’s that simple. And making the same mistake repeatedly is called self-sabotage. Self-sabotage is another area of psychology rich with the opportunity for understanding yourself to improve your trading results. Here, however, we’ll focus on mistakes relating to some broad categories of traders.
First, let me introduce one way to measure the impact of mistakes on your trading. Trader efficiency is a measure of how effective a trader is in making mistake-free trades. So a person who makes five mistakes in 100 trades is 95% efficient. In the last five years I’ve requested that my Super Traders document their mistakes so that we can look at their efficiency levels. I have found that 95% is actually a very good trading efficiency level; many traders can’t even trade at 75% efficiency—which is terrible. That’s one mistake in about every 4 trades. This is most important for one category of traders: rule-based discretionary traders. In my opinion, when rule-based discretionary traders become efficient, they are by far the best type of trader.
There are two other groups of traders I’d like to talk about: (1) mechanical traders and (2) no-rules discretionary traders.
First, we’ll look at mechanical traders. Mechanical traders believe that they can eliminate psychologically related trading problems by becoming mechanical. Many people aspire to be mechanical traders, letting a computer make all the decisions for them, because they believe it will factor out many human-based errors.
In fact, one of my best trader friends said to me once that psychology didn’t enter into his trading because his operation was totally automated. My response was, “You could decide not to take a trade.” About 18 years after I made that statement, his commodity trader advisor (CTA) business closed down. His partner decided against taking one trade—the trade that would have made their entire year had they taken it.
I’ve always said that people can trade only their beliefs about the market, so let’s look at some of the most important beliefs that a pure mechanical trader might have:
• With mechanical trading, I can be objective and not make mistakes (except the psychological mistake of overriding my system).
• Mechanical trading is objective. My system testing will allow me to determine my future results.
• Mechanical trading is accurate.
• If a system’s underlying logic cannot be turned into a mechanical trading system, it probably isn’t worth trading.
• Human judgment is too prone to errors. I can eliminate those through mechanical trading.
So then, is mechanical trading truly objective? I tend to think not because there are all sorts of errors that can creep into an automated trading system: data errors, errors in the software platform, errors in your own programming, and many more. (Interestingly, one of the main categories of errors that my Super Traders come up with consistently is programming errors.)
Let’s consider data errors. Is your data accurate, or does it have bad ticks and other issues with it? Mechanical traders are always dealing with data errors of some sort. For example, price errors can show up in streaming data quite regularly. Sometimes those are resolved within seconds and the error “disappears,” but by that point, the bad data may have triggered a trade already. Additionally, historical stock data may or may not have dividend and split adjustments. And what happens when a company goes bankrupt? What if it goes private, or it is bought out by another company? Those companies’ data may simply disappear from your data set.
I once wanted to research an efficient stock trading system. We looked for efficient stocks (moving up without much noise) and bought them with a 25% trailing stop. We had an S&P 500 data set going back 40 years that was supposed to be clean and adjusted for splits and dividends. I was very pleased with the results because my system made a small fortune. I didn’t realize this at the time, however, but the system traded on “inside information.” Because of the data set, I was able to buy stocks at the IPO that would later become part of the S&P 500. Thus, my system, in back test, bought Microsoft, eBay, Intel, and many other companies before anyone knew they would become part of the S&P 500. Why? Because, as I said, my data set was today’s S&P 500 going back 40 years.
And what about Thursday, May 6, 2010? The Dow Jones dropped 1,000 points in the space of about 20 minutes. Blue chip stocks like Procter & Gamble dropped over 20 points, and Accenture even went to a penny per share briefly. While there may not have been one root cause for that mini-crash, it had a major effect on mechanical trading systems. Things like that happen in the markets; such are the challenges (errors and/or mistakes) for mechanical systems. (That afternoon’s swing affected lots of regular traders too. One client said he used 25% trailing stops on all of his positions and got stopped out of every single stock.)
Meanwhile, one of our instructors, Ken Long, trades rule-based discretionary systems and made 100R in that same week. As always, he was very conservative in his trading and very careful to make sure that he fully managed his risk.
There is another class of error that is made by mechanical trading systems: the error of omission. Because the criteria by which trade setups and entries are so precisely defined, mechanical systems miss many good (or great) trades that a discretionary trader would spot easily.
For example, suppose your system screens for five consecutive lower closes. After you get five consecutive lower closes, you then look for an inside day. Now you have your full setup. Your entry is a few cents above yesterday’s high.
So let’s look at some examples of other entry signals you might miss by being so precise. You could have four down days that were extreme—perhaps the price is down 30%. Or you could have fewer than four down days where the price is 30% lower or more. However, neither of those examples would be an adequate down move according to your strict mechanical criteria.
Let’s say you found something that had five days of new lower lows, but the fifth down day opens on a new low and then closes on a new high. That’s usually an extremely bullish signal, but you’d miss it by your precise definition. Or you could have five days of lower closes and the sixth day opens on a new low but closes on a new high. Thus, the precise entry definition would miss a trade opportunity with even more weakness followed by an extreme bullish signal.
There are a lot more variations of this entry that a mechanical system would miss, but you get the point. As soon as you state your rules so precisely that a computer can execute the trades, you open yourself to errors of omission—good or outstanding trades that your automated system cannot take because of its precision. Those missed opportunities don’t qualify as mistakes, but they severely limit the potential results of the underlying logic behind the system. The mechanical system results will look rather weak next to the results of a trader who used that same system and was allowed some discretion to take all of those other trades that didn’t quite fit the precise mechanical system rules.
Many of my initial models of good traders were pure mechanical traders:
I’m 90% sure about the following, but I haven’t modeled them:
Renaissance Capital Management (one of the best trading firms ever, and they computerize day-trading systems through neural networks)
Thus, I’m not saying don’t be a mechanical trader. Just realize the limitations of mechanical trading.
Next, we’ll look at mistakes and another type of trader: the no-rules discretionary trader.
In my experience, when most people say “I am a discretionary trader,” it basically means that they are free to do whatever they want. They can take a newsletter recommendation, trade a high probability setup based on what some guru said in a workshop last year, or perhaps just buy something on a whim. They might feel they have 20 different systems with none of them rigid.
In reality, they have no systems at all. What they really have is a little bit of nothing and a lot of “into-wishing” (as opposed to intuition). As a result of having no system and no rules, they have no way of effectively managing their trading. How well do you think a company would operate with no plans, no business systems, and no rules? Because they have no rules to follow, everything no-rules discretionary traders do is a mistake.
Now in fairness, some discretionary traders have rules for at least a portion of their trading. There’s hope for these people because they have a starting point. Those who are totally no-rules discretionary traders, however, have no hope and should either stop trading or totally revamp their trading business.
Are you a discretionary trader? How would you be able to tell? Here is a quiz that will help you decide. Answer yes or no to the following questions:
1. Do you sometimes buy newsletter recommendations without having a real plan for how you’ll get out of the trade?
2. Do you occasionally (or often) take trades based upon some interesting indicator that you learned in a workshop (that is, when you see that indicator go, you usually get into a trade, but again you have no real plan about how you’ll get out of the trade)?
3. Do you trade three or more different systems in the same account?
4. Do you trade more than 10 different systems?
5. Do you sometimes enter a trade and later not remember why?
6. Are you unsure of how many systems you have?
7. Do most of your systems lack a complete set of rules to guide your behavior?
8. Are your systems equivalent to the setups used to get into the trades and nothing more?
9. Are you unable to list the rules for the last trade you made?
10. Are you unable to list the rules for any of the last five trades you made?
If you answered yes to as many as two of the questions above, you have some elements of a no-rules discretionary trader. However, if you answered yes to six or more questions above, you definitely are a no-rules discretionary trader.
Chances are you seldom make money in the market because you are not playing a winning game. You probably make many mistakes. In fact, since you don’t have rules, I would consider everything you do to be a mistake until you have a set of rules in place. How can you effectively learn from any of your trading experiences if you do not know which ones are mistakes?
If it is any consolation, most traders fall into the no-rules discretionary category. The best among this group might be dedicated to following the trades of a single newsletter. If that applies to you, do you even know the rules of the newsletter? Does the newsletter writer have rules to guide his trading? Chances are, if he must come out with a specific recommendation once every month on a specific date, he doesn’t have such rules. And chances are also good that you don’t follow the recommendations of the newsletter writer exactly: you don’t take some trades, you may miss some others, you buy at a price other than that recommended, and you probably don’t sell when you are told to. Again, these are all signs of a no-rules discretionary trader.
Next, we’ll look at rule-based discretionary traders.
Chances are you’ve never heard of a rule-based discretionary trader. They are rare, but they are among the best traders in the world. I can safely say that anyone who graduates from my Super Trader program has either become a rule-based discretionary trader or a mechanical trader.
Here are some rules that such a trader might have:
• Look at a small universe of stocks that behave well according to my rules. (In other words, not every stock has to behave according to your rules; you just find stocks that do.)
• Look for a strong overreaction to the downside. (This would have a very specific description—for example, market closes down for six straight days.)
• Look for move with a high probability for a continuation in my favor. (This might be one or several rules that are clearly specified.)
• Have a likely target in mind based on a prior swing high so that the difference between the entry price and the high is my likely target.
• Place a stop below the most recent low of the last down day so that the difference between that low and the entry price is the risk of the trade.
• Make sure that the reward-to-risk ratio of any trade is at least 3 to 1. If it’s not, look for another trade.
• Raise the stop when the market makes a new level of support and rises to a new high. Make sure that the ongoing reward to risk in the trade is always above 1 to 1, to allow for profits bigger than 3R.
• Never have more than four active positions at a time so that every trade can be carefully managed.
• Never risk more than 0.5% of equity per position.
• Never have more than 1% open risk in my account at any given time.
• Evaluate my mistakes each evening, and work to make my trading efficiency 95% or better.
• Reevaluate my rules if I’m not up by at least 5R at the end of the month.
Notice how every aspect of trading is covered by these rules. They allow for some discretion (that is, what constitutes a 3-to-1 reward-to-risk trade and the ability to stay in the trade after it reaches your target), but at the same time there are clear guidelines for the trade. In addition, the trader could add a few other discretionary rules to improve his or her performance:
• I can reenter the trade once if the reward-to-risk potential is still at least 3 to 1.
• I can add a second position to the trade the first time I raise my stop if the new reward-to-risk ratio is at least 5 to 1.
• If something really bothers me about the trade and I can document it, I don’t take it.
The rules I’ve given are just examples. I’m not even saying that they are profitable rules, although I’ve seen similar rule sets that are exceptionally good.
What I am saying is that at the end of the day, this trader can do a daily debriefing and ask, “Did I make any mistakes? Did I follow my rules?” He can (1) record any mistakes, (2) assess the impact of the mistakes in terms of R multiples, and (3) take corrective steps to avoid those mistakes in the future. These tasks are critical to developing strong, consistent performance. Can you see how these steps are impossible for the no-rules discretionary trader?
The list of superb rule-based discretionary traders that I know of is very long. Here are just a few of them:
1. Paul Tudor Jones (and probably all the traders that work for him, including several that I’ve consulted with)
2. Richard Dennis and most Turtles that I know of
3. William O’Neil
4. David Ryan
5. Marty Schwartz
6. Peter Steidlymayer
7. Chuck Whitman (the president of Infinium Capital Management and the author of the foreword to Trade Your Way to Financial Freedom)
Of all the good to great traders I’ve worked with, I’d estimate that 90% fit here, while the other 10% are totally mechanical.
Let’s look at some of the common mistakes that each of our three trader types might make.
In my opinion, everything they do is a mistake because they are never following written, documented rules. But here are the most common ones:
• Entering on a tip or emotion or something that doesn’t correspond to one of your well-thought-out systems
• Doing anything because of an emotional reaction
• Blaming someone or something for what happens to you rather than accepting personal responsibility
• Not having a predetermined exit when you enter the trade
• Trading so many trades in the same account that you cannot keep track of them
• Thinking a setup indicator is a system
• Concentrating on the entry for a system, not the potential reward-to-risk ratio in the trade
• Not exiting when you should be stopped out
• Risking too much money on any particular trade
• Exiting too soon on emotion
• Not following your daily routine
• Trading multiple systems in the same account
• Trading a system when the market type has changed and you know that the system now will perform poorly
• Needing to be right and taking a profit too quickly or not taking a loss just to be right
• Not keeping track of the R multiples and the general performance of your trading system
• Order execution errors, including pressing the wrong button
• Position sizing errors
• Plus, most of the errors a mechanical trader or a no-rules discretionary trader might make
• General programming mistakes
• Programming mistakes that overlook contingencies that might happen in the market that a discretionary trader would catch such as a major change in market conditions
• Data mistakes
• Electing to override the system and not taking a trade
• Missing lots of good trades because the rules are too rigid
• Trying to fit the system to all market conditions (in fact, that’s usually a criteria for a mechanical system)
• Assuming that backtesting results will indicate the results you’ll get when you do real trading with the system
I recommend that at the beginning of each day, you go through a mental rehearsal. Ask yourself, “What could go wrong today that might cause me to make a mistake?”
Here is an example. One of my clients in Europe was a superb day trader. He made huge profits daily trading the stock index futures. One day a local hospital called him. His girlfriend had been in a car accident and was seriously injured. He immediately rushed to the hospital to be with her, forgetting about his market positions. He didn’t have actual stops in the market. He exited with mental stops because he felt that was generally safer for him. However, on this day, he thought only about his girlfriend.
When he was finally informed that his girlfriend would be fine, the market had closed. Later, he checked on his positions and discovered that he’d lost about a year’s worth of profits that one day.
When I started coaching him, the first thing I had him do was develop a worst-case contingency plan and make sure that every contingency was rehearsed properly. Generally, the better your worst-case contingency plan is, assuming that all your contingency plans are well rehearsed and automatic for you, the less daily mental rehearsal you have to do.
When I originally wrote Super Trader in late 2008, market volatility was as high as 10 standard deviations bigger than the norm. As I am finishing off the updated edition, in May 2010, we just had a day in which the Dow Jones dropped 1,000 points in minutes only to recover about 60% of the loss within minutes. Many people got stopped out of long-term positions because of that short-term down move. Both the mini-crash and subsequent recovery have almost a zero probability of occurring if market volatility is normally distributed. But they occurred! If you are not prepared to trade in these sorts of conditions, your account could experience a disaster.
Similarly, who would have imagined that the U.S. stock market would close for a while because the World Trade Center was destroyed and the New York financial district was full of rubble? Did you predict that one? Would you be able to predict that a squirrel could chew on wires in your attic and disrupt your trading? These things happen, so prepare for it.
And are you aware that the New York Stock Exchange was once closed for a considerable period of time because the United States feared that other countries would make a run on our gold? The theory was that foreigners might accomplish that through the U.S. stock market. As a result, the government simply closed down the stock market for a while. So these are just a few examples to justify the belief that “anything” is possible and you need to be prepared for it.
Thus, I recommend that everyone go through a daily mental rehearsal. Ask yourself, “What could go wrong today to cause me to make a mistake?” Become creative and think of everything. For everything you come up with, rehearse how you’ll perform to make sure that it has a minimal impact on your trading.
One day you might meet that big losing trade in the markets that has your number on it. Wouldn’t it be a good idea to be prepared for it ahead of time? Increasing your efficiency from 90% (that is, one mistake every 10 trades) to 98% (that is, one mistake every 50 trades) could double your return rate or more.
There is one more task that you should consider doing on a daily basis. I call this task the daily debriefing. It is designed to ensure that you do not repeat mistakes where again a mistake means not following your written rules.
At the end of the trading day, ask yourself a simple question: “Did I make any mistakes?” If the answer is no, pat yourself on the back. If the answer is no and you lost money, pat yourself on the back twice. Good job; you followed your rules.
However, if you did make a mistake, your new task is to make sure that you never repeat it. Ask yourself, “What sorts of conditions were present when I made my mistake? When might they occur again?”
Once you’ve answered these questions, the task becomes a matter of mental rehearsal, which we discussed earlier. Come up with something you can do to make sure you don’t repeat that mistake under those similar conditions, or any other conditions for that matter. Once you come up with the solution, rehearse it in your mind a number of times until it becomes second nature to you.
In my opinion, it is essential that you do this task every day. A few minutes each day on this task alone, along with effective solutions, could end up increasing your returns by 20% to 50% each year.
Up until this point, our focus in Part 5 has been on avoiding mistakes. As we conclude this final section of the book, I want to close with some discussion directly related to the simplest and most common goal of all—profit. The first lesson and first step I’d like you to incorporate applies to many things in life, including anything you might do in trading or investing: Keep things simple. The more you try to make things complex, the harder it will be for you to be successful. Keeping things simple works both in life and in the markets.
Your mind has a conscious capacity of only about seven chunks of information. You cannot hold any more than that in your consciousness. Have someone give you a series of 10 two-digit numbers, and you’ll probably find that you have trouble remembering more than 5 of them because of this limitation in capacity. If you attempt to do complex things with the market that require you to use more capacity than you have, you’ll probably fail.
Keeping it simple doesn’t mean that you can’t use a computer to sort through the vast amount of information available about the market. On the contrary, I highly recommend it. However, it means that your methodology and your daily tasks do not have to be rocket science. In fact, the more you try to do, the less likely you are to succeed.
I did a psychological profile of a broker-trader who ranked in the bottom 1% of all the investors who had taken my psychological test, the Investment Psychology Inventory Profile. He had high stress, a lot of internal conflict, poor organization, no system, a negative attitude, and probably everything else you could name. I then did a 10-minute consultation with him, but he really needed several days. The key issue for him was how overwhelmed he felt by everything that came across his desk. How could he find good stocks when there were so many stocks? How could he follow any plan when his clients all had conflicting goals and motivations? His life was a mess.
This broker needed to do a lot of psychological work. His life was in chaos because his mind was in a state of chaos. Simplify the chaos in your mind and you’ll simplify the chaos in your life. You can start doing that by deciding what you want in life (that is, your dream life) and then focusing on only one or two simple goals from that dream life.
Second, he needed a simple system to track his own trading, preferably a long-term system that gave him only a few signals each week and required that he look at the market only after the close. That way, his personal decisions had to be made only once each day, away from the chaos of the market. That system could be something as simple as buying on a 110-day channel breakout, using the weekly volatility as a worst-case exit, trailing it from the close as a profit-taking stop, and not risking more than 1% of his equity on any trade. In his case, he needed to do a survey of all his beliefs about himself and that market. From that survey, he could begin to design a trading method that fit him.
These are all simple steps. Success comes from following simple steps. When you understand that and practice it, your performance will improve dramatically.
You can grow your business, especially when capital isn’t the problem. Instead, your problem is finding the best use for your capital. When you think about these methods, they may seem obvious, but most people don’t think about them enough. Here are the key ways you can grow your business:
1. First, develop new, improved trading systems. Each system can help you make more profits, especially if it is not correlated with the other systems. Continue to conduct research to find new systems that can become new profit centers for your trading research. By the way, some of your systems may stop working in certain market conditions, so it’s always good to have more systems in the pipeline.
2. Second, find more markets in which to apply each system. Let’s say you develop a great system that works on the S&P 500 Index. It gives you five trades a month and has an expectancy of 2R. That means that on average you probably can make 10R from that system each month. But what if the system also works on other major stock market indexes with the same results? If you can add 10 more indexes to trade, you may be able to make 100R each month.
3. Third, add traders. Each trader can handle only so much work and so many markets effectively. Let’s say a good trader can trade $50 million effectively. When the total goes above that level, your experience is that the trader’s effectiveness seems to drop off. One way to grow your business is to have more traders. Ten good traders now may be able to handle $500 million effectively.
4. Fourth, make your traders more effective at what they are doing. Let’s say a trading system generates an average return of 40% each year. You can measure the effectiveness of a trader by the number of mistakes that trader makes. For example, a typical trader may make 20% worth of mistakes each year on a 40% system. That kind of trader, at 80% effectiveness, would allow you to generate 32% from the system. But what if you could make the trader more effective? What would happen if you gave your traders effective coaching that could reduce their mistakes to 5% each year? That amounts to a 75% increase in effectiveness per trader per system per year. You can expand a trading business immensely through coaching that allows your traders to become more effective.
5. Fifth, optimize your position sizing strategies for meeting your objectives. To do that, you must take each of the following steps:
• Clearly determine what the objectives are for your business. Many people and many firms do not do this task well, if at all.
• Determine the R-multiple distribution generated by each of the systems you use.
• Simulate different position sizing algorithms to determine which of the thousands of possible algorithms will meet your objectives most effectively.
• Apply that algorithm to your systems.
For example, suppose you want to make 200% on your capital allocated to a particular system. You have a system that generates on average 70R each year. If you risk 1% of your allocated capital per trade, you may find that you can make 70% per year from the system. However, if you increase the position sizing risk to 3%, you may find that you can make the 200% you desire. Of course, increasing the position sizing risk will increase the potential drawdowns. You need to be fully aware of the downside to such changes.
All these factors can be multiplicative. For example, suppose you have three traders, each trading two systems in three markets. Each system makes about 60R per year per market, but the traders are only 75% effective in trading them. This means that they make about 15R in mistakes per system per market per year.
Let’s look at what is generated for the company. We have three traders times two systems times three markets times 45R. If you multiply these out, you’ll find that the company generates 810R each year. Now let’s look at the effect of the various changes we could make:
First, what if we added three more traders? We might be able to double the total return to 1,620R.
Second, what if we added three more markets for each system? We might now increase the returns to 3,240R.
What if we added one more system per trader? We might now increase the return to 4,860R.
What would happen if we increased the efficiency of our traders to 90% (which we might have to do for them to handle the extra work)? We’d get an additional 20% more profit and now be at 5,832R.
Finally, what if we made our position sizing method more effective to increase our profits another 50%? Well, you get the idea.
No business would be able to do all of the things I’ve suggested at the same time, but what if you could do a few of them? What would be the impact on your bottom line? If you are considering some of these changes, concentrate on trader efficiency and on more effective position sizing methods to meet your objectives.
Most people make a big deal out of market prediction. They think they need to be right 70% of the time or more to pass the exam that the market gives them. They also believe that they might get an A if they could be right 95% of the time. The need to predict the market stems from this desire to be right. People believe that they cannot be right unless they can predict what the market is doing.
Among our best clients, I have traders who continually make 50% or more each year with very few losing months. Surely, they must be able to predict the market very well to have that kind of track record. I recently sent out a request for predictions, and here is what I got back from some of the better traders:
Trader A: I don’t predict the market, and I think this is a dangerous exercise.
Trader b: These are just scenarios. The market is going to do what the market is going to do.
I got these comments from them despite the fact that I was not interested in any of their specific opinions, just the consensus opinion.
How do they make money if they have no opinions about what the market is going to do? There are five critical ingredients involved:
1. They follow the signals generated by the system.
2. They get out when the market proves them wrong.
3. They allow their profits to run as much as possible; that means they have a high positive expectancy system.
4. They have enough opportunity that there is a greater chance of realizing the positive expectancy in any particular month and little chance of having a losing month.
5. They understand position sizing strategies well enough that they will continue to be in the game if they are wrong and make big money when they are right.
Most traders, including most professionals, do not understand these points. As a result, they are very much into prediction. The average Wall Street analyst usually makes a large six-figure income by analyzing companies; yet very few of these individuals, in my opinion, could make money trading the companies they analyze. Nevertheless, many investors believe that if analysts tell them the fundamentals of the marketplace, they can use that information to make money.
Others have decided that fundamental analysis doesn’t work. Instead, they have chosen to draw lines on the computer or in a chart book to analyze the market technically. These people believe that if they draw enough lines and interpret enough patterns, they can predict the market. Again, it doesn’t work.
Instead, cutting losses short, riding profits hard, and managing risk so that you continue to survive is what really makes you money. When you finally understand this at a gut level, you will know one of the key secrets to trading success.
Quite often people make great progress psychologically, but when it comes to some of the fundamental issues that we teach in trading, they ignore them and say, “I don’t understand.” Most people’s response is to ignore the fundamentals rather than do whatever is necessary to increase their understanding.
Here is a brief quiz on some key elements that I consider absolute fundamentals for all traders. You must understand these elements if you want to compete as a successful trader. Answer these questions before you read the answers in the next section.
1. You buy a stock for $25. You want a 25% trailing stop. Where is your initial stop?
2. The same stock moves as high as $40 and then goes back down to $37. Where is your stop?
3. You have a $25,000 account and don’t want to risk more than 1% of your account on that stock. How much of your account can you risk?
4. In light of your answers to questions 1 and 3, how many shares did you buy?
5. You buy another stock for $38, but this time your stop is only 50 cents away. How many shares can you buy to risk only 1%?
6. You think that’s too many shares, and so you want to base your stop on the volatility. The average true range over the last 10 days of the stock has been $3. You decide to base your allocation on volatility. How many shares can you buy?
7. Since your stop is still at 50 cents, how much are you risking on this position?
8. What’s your total investment amount for the first stock and for the second stock? How is this different from risk?
9. What is the variable that accounts for most of the performance variability you are likely to encounter (assuming that you have your psychology together)?
10. What have I defined self-sabotage to be?
Bonus question: You sell the first stock for $50, or a $25 profit. What is your R multiple? In other words, your profit is what multiple of your initial risk?
1. Your stop should be the current price times 0.75, or $18.75. If you subtract 25% of the price from the current price, you have your stop, and that’s equivalent to 75% of the entry price. Give yourself 10 points if you got it right.
2. You have a 25% trailing stop. That means that each time the stock makes a new high (or closing high if you prefer), you take 25% of that as your stop. This is your new stop. Thus, the prior high was $40, and your new stop is 75% of that, or $30. When the price moves down, you do not change your stop. Give yourself another 10 points if you got it right.
3. Your risk is 1% of $25,000, which is $250. Give yourself 10 points if you got it right.
4. Your risk is $6.25. If you divided your risk per share into your total risk allowed ($250), you would end up with 40 shares. Again, give yourself 10 points for a correct answer.
5. Since your risk is only 50 cents, if you divide 50 cents into $250, you end up with 500 shares. Give yourself 10 points if you got it right.
6. Here you divide your 1% risk, or $250, by $3 per share. Your answer is 83.33333333 shares. Round down to the nearest whole share, and the answer is 83. Give yourself 10 points if you got it right.
7. You actually are risking 83 times 50 cents, or $41.50. Give yourself 10 points for that one. Your allocation went down because it was based on volatility, but your stop stayed the same.
8. In the first example, you bought 40 shares of a $25 stock. Your total risk was $250, but your total investment was 40 times $25, or $1,000. Notice that you have a 25% stop and that your risk is 25% of your investment. Give yourself 3 points for that one if you got it right. In the second example, you either bought 500 shares based on risk for a $19,000 investment, or you bought 83 shares based on volatility for a $3,154 investment. Either one is acceptable, and so if you answered one of those correctly, give yourself 3 points. Total investment is the number of shares (that is, 40) multiplied by the total cost of the share (that is, $25). In contrast, risk is the number of shares (that is, 40) multiplied by how much you are willing to let the price drop before you exit (that is, $6.25). Give yourself 4 points for this answer.
9. Position sizing strategies. Give yourself 10 points if you got it right.
10. Repeating mistakes. Give yourself 10 points if you answered correctly.
Bonus question: If you sold the stock at $50, you made a profit of $25. That’s four times your initial risk of $6.25, and so you made a 4R profit. Give yourself 10 more points if you got it right. Thus, your total score could be as high as 110.
If you scored 100 or better, your understanding of these fundamentals is excellent. Keep up the good work.
If you scored 80 to 99, you need a little work. Figure out where you are weak, and do some homework.
If you scored 60 to 79, you need a lot of work. Again, figure out where you are weak, and make the effort to understand the material.
If you scored 59 or less, it might be because you are new to trading and these principles. If that’s the case, you have significant work to do. If you’ve been studying this material for some time and still got 50 or less, perhaps trading is not for you.