“Market Wizards” Advice: Doing the Uncomfortable Thing
Excerpted with permission of the publisher, John Wiley & Sons, from “The Little Book of Market Wizards: Lessons from the Greatest Traders,” by Jack D. Schwager. Copyright © 2014 by Jack D. Schwager. All rights reserved. This book is available at all bookstores and online booksellers.
Jack Schwager interviewed the top traders about their experiences and wrote about his conversations in “Market Wizards,” a 1989 book that became a bestseller and spawned three other volumes. This article is an excerpt from his new book, “The Little Book of Market Wizards,” which distills the valuable insights from these interviews over the years into essential lessons every investor can benefit from.
William Eckhardt, a long-term successful trader and commodity trading advisor, believes that the natural human tendency to seek comfort leads people to make decisions that are worse than random in trading.
I want to be clear. You have probably heard the famous quote by Princeton University economics professor Burton Malkiel, “A blindfolded monkey throwing darts at a newspaper’s financial pages could select a portfolio that would do just as well as one carefully selected by experts,” or some variation of that theme frequently uttered by those deriding the purported folly of trying to beat the market. Eckhardt is not saying that. He is not saying a monkey could do as well as the professional money managers. Eckhardt is saying the monkey will do better.
Now, why will the monkey do better? The monkey will do better because humans have evolved to seek comfort, and the markets don’t pay off for seeking comfort. In the markets, seeking comfort means doing what is emotionally satisfying. Eckhardt says, “What feels good is often the wrong thing to do.” He quotes his former trading partner, Richard Dennis, who used to say, “If it feels good, don’t do it.”
As an example of doing what feels good in the markets, Eckhardt cites what he terms “the call of the countertrend.” Buying on weakness and selling on strength appeals to the human desire to buy cheap and sell dear. If you buy a stock when it falls to a six-month low, it feels good because you feel smarter than everyone else who bought that stock in the past six months. Although these trades may feel better at the moment of implementation, for most people, following such a countertrend approach will be a losing, and possibly even disastrous, strategy.
As another example, Eckhardt explains that because most small profits tend to vanish, people learn the lesson to cash in profits right away. This may feel good, but it is detrimental over the long run because it will also impede the ability to earn large profits on any trade. As a third example, Eckhardt says that the tendency of markets to trade through the same price repeatedly leads people to hold on to bad trades in the hope that if they wait long enough, the market will return to their entry level.
In all these cases, the action that feels good—getting a bargain, locking in a profit, holding out hope for avoiding a loss—is usually the wrong thing to do. The need for emotional satisfaction will lead most people to make decisions that are even worse than random, which is why the dart-throwing monkey will do better.
As an empirical demonstration of how most people’s biases will lead them to make decisions that are worse than random, Eckhardt told the story of how one of Richard Dennis’s employees entered a charting contest that required predicting the year-end prices for a number of markets. This employee simply used the current prices of all the markets for his predictions. He finished in the top five among hundreds of contestants. In other words, at least 95%, and probably closer to 99%, of all the entrants’ predictions were worse than random.
When Everything Is Going Wrong
Okay, good trading should be effortless. But what do you do when you hit prolonged periods when trading is a struggle? How do you handle the periods when almost everything seems to be going wrong and you are in a steadily deepening drawdown? Even great traders can experience demoralizing losing periods. The Market Wizards I interviewed were quite consistent in the advice they offered about handling difficult losing periods. They had two basic recommendations:
1. Reduce your trading size. Paul Tudor Jones, one of the great futures traders of our time, said, “When I am trading poorly, I keep reducing my position size. That way, I will be trading my smallest position size when my trading is worst.”
Ed Seykota, a pioneer in systematic futures trading who achieved astounding cumulative returns, offered similar advice when I asked him if he had locked away several million dollars to avoid the Jesse Livermore experience. (Livermore was a famous speculator of the early 20th century who made and lost several fortunes.) Seykota replied that a better alternative was to “Keep reducing risks during equity drawdowns. That way you will approach your safe money asymptotically and have a gentle financial and emotional touchdown.”
Marty Schwartz, who had run a $40,000 account into over $20 million when I interviewed him, will cut his trading size to a fifth or even a 10th of normal if he experiences losses that shake his confidence. “After a devastating loss,” Schwartz said, “I always play very small and try to get black ink, black ink. . . . And it works.” Schwartz recalls that after he took an unusually large $600,000 hit in his account on November 4, 1982, he responded by drastically reducing his trading size, piecing together many small gains and finishing the month with only a $57,000 loss.
Randy McKay, who parlayed an initial $2,000 trading stake into tens of millions in profit by the time I interviewed him 20 years later, is even more extreme in reducing his position size when he is in a losing streak. “I’ll keep on reducing my trading size as long as I’m losing,” he says. “I’ve gone from trading as many as 3,000 contracts per trade to as few as 10 when I was cold, and then back again.” He considered this drastic variation in position size as a key element in his trading success.
2. Stop trading. Sometimes reducing trading size is simply not enough, and the best remedy to break the downward spiral is to simply stop trading. As futures trader Michael Marcus explained, “I think that, in the end, losing begets losing. When you start losing, it touches off negative elements in your psychology; it leads to pessimism… When I have had a bad losing streak, I have been able to say to myself, ‘You just can’t trade anymore.’”
Richard Dennis, who turned a $400 trading stake into a fortune, estimated by some to be near $200 million at the time of our interview, had a very similar perspective, expressing that losses beyond a certain level will adversely impact the trader’s judgment. His straightforward advice: “When you are getting beat to death, get your head out of the mixer.”
If you are in a losing streak, the best solution is not trying harder, but rather the exact opposite: Stop trading. Take a break or even a vacation, liquidating all positions or protecting them with stops before you leave. A physical break can serve to interrupt the downward spiral and loss of confidence that can develop during losing periods. Then when you return, ease back into trading, starting small, and gradually increasing if trading has again become effortless.
Although traders will know when they are in losing streaks, they may be slow to realize the dimensions of the problem until the loss has far exceeded acceptable levels. They allow losses to mount without changing anything and then suddenly are shocked to realize the magnitude of their drawdown. One way to become cognizant of these persistent losing periods more quickly and in time to take corrective action before excessive damage is done is to plot your equity daily. Marcus offered this advice, noting, “If the trend in your equity is down, that is a sign to cut back and reevaluate.”
—“The Little Book of Market Wizards,” by Jack D. Schwager (John Wiley & Sons, 2014)
The Inadvertent Experiment
In his book “The Little Book That Beats the Market” (John Wiley & Sons, 2005), Joel Greenblatt provided a value-based indicator for ranking stocks. He called this ranking indicator the Magic Formula, a name that poked fun at the hype normally accompanying market indicators, but also referred to the surprising efficacy of the measure.
In fact, Greenblatt and his trading partner, Rob Goldstein, were so impressed with how well the Magic Formula worked that they set up an eponymous website that investors could use to pick their own stocks from a limited list of equities selected based on the value rankings of the formula. Investors were encouraged to pick at least 20 to 30 stocks from the list to get close to the average performance of these stocks, as opposed to being overly dependent on a few names. As a last-minute addition, the partners also included a check box that gave investors the option of having their account managed rather than picking the stocks themselves. It turned out that less than 10% of people using the site for investment chose to do their own selection—the original concept—while the overwhelming majority chose the managed portfolio option.
Greenblatt then tracked how the self-managed portfolios fared versus the managed portfolios. After the first two years, on average, the managed portfolios outperformed the self-managed portfolios by 25%, even though both were constructed from the same list of stocks. The differential between the managed and the self-managed portfolios reflected the impact of human selection and timing decisions. Letting investors make their own decisions (picking specific stocks from the list and timing the purchase and sale of these stocks) destroyed all the performance gained by investing equal dollar amounts in a diversified portfolio of these stocks without any attempt to time the entries and exits of the holdings.
I asked Greenblatt why he thought the investors making their own decisions did so much worse. Greenblatt replied, “They took their exposure down when the market fell. They tended to sell when individual stocks or their portfolio as a whole underperformed. They did much worse than random in selecting stocks from our prescreened list, probably because by avoiding the stocks that were particularly painful to own, they missed some of the biggest winners.” Think about it. Don’t these sound like decisions made to seek comfort?
Greenblatt had inadvertently created a control group experiment that demonstrated the impact of human decisions in the market by way of a well-defined benchmark—a diversified portfolio consisting of the same list of stocks without any selection or timing inputs. Investors could have achieved the same expected return (with sampling variation) if they had randomly selected their stocks, invested equal dollar amounts in each and applied the same timing-free buy-and-hold approach. Or, equivalently, the same expected return could have been achieved from a portfolio based on the dart throws of a monkey at the list of the selected stocks. Greenblatt’s inadvertent experiment effectively provided a real-life validation of Eckhardt’s contention that the proverbial monkey would outperform humans making their own investment decisions.
Behavioral Economics and Trading
Eckhardt ties in human biases to the tendency for the majority of market participants to lose. As Eckhardt explains it, “There is a persistent overall tendency for equity to flow from the many to the few. In the long run, the majority loses. The implication for the trader is that to win you have to act like the minority. If you bring normal human habits and tendencies to trading, you’ll gravitate toward the majority and invariably lose.”
Eckhardt’s observations are well aligned with the findings of behavioral economists whose research has demonstrated that people inherently make irrational investment decisions. For example, in one classic experiment conducted by Daniel Kahneman and Amos Tversky, pioneers in the field of prospect theory, subjects were given a hypothetical choice between a sure $3,000 gain versus an 80% chance of a $4,000 gain and a 20% chance of not getting anything (“Prospect Theory: Analysis of Decision under Risk,” Econometrica, March 1979). The vast majority of people preferred the sure $3,000 gain, even though the other alternative had a higher expected gain (0.80 × $4,000 = $3,200). Then they flipped the question around and gave subjects a choice between a certain loss of $3,000 versus an 80% chance of losing $4,000 and a 20% chance of not losing anything. In this case, the vast majority chose to gamble and take the 80% chance of a $4,000 loss, even though the expected loss would be $3,200. In both cases, people made irrational choices because they selected the alternative with the smaller expected gain or larger expected loss. Why? Because the experiment reflects a quirk in human behavior in regard to risk and gain: People are risk-averse when it comes to gains, but are risk-takers when it comes to avoiding a loss.
This behavioral quirk relates very much to trading, as it explains why people tend to let their losses run and cut their profits short. So the old cliché (but not any less valid advice) to “let your profits run and cut your losses short” is actually the exact opposite of what most people tend to do.
Why Emotions Affect Even Computerized Trading
Interestingly, the need for emotional comfort will even have a detrimental impact on systematic trading (i.e., computerized, rule-driven trading), an area of trading one might reasonably have assumed would be free of emotionally based decisions. Typically, when people approach systematic trading they will test their system rules and then discover that there are many past instances when following the system rules would have led to uncomfortably large equity drawdowns—an observation that will be true even if the system is profitable over the long run. The natural instinct is to revise the system rules or add additional rules that mitigate these poorly performing past periods. This process can be repeated multiple times, making the simulated equity curve smoother and smoother with each iteration. In effect, the natural inclination is to optimize system rules for past price behavior. The resulting final optimized system will generate an equity curve that looks like a money machine. Such a highly optimized system will be much more comfortable to trade because, after all, look how well it would have done in the past.
The irony, however, is that the more a system has been optimized, the less likely it is to perform well in the future. The rub is that the system’s impressive simulated results are achieved with the hindsight knowledge of past prices. Future prices will be different, so the more the system rules are tweaked to fit historical prices, the less likely the system will work on future prices. Once again, the human instinct to seek emotional comfort has negative consequences in trading—even in computerized trading!
The lesson is that most people lose money in trading not only because they lack skill (that is, they don’t have an edge), but also because their inclination to make the comfortable choices in trading (or investing) will actually lead to worse-than-random results. Awareness of this inherent human handicap in trading is the first step in resisting the temptation to make trading decisions that feel good but are wrong on balance.