More Than You Know
Page 2
SFI has sparked my interest in disparate topics—sprinkled throughout the following essays—including ant colonies, power laws, human cognition, and the role of feedback mechanisms. The best way to describe how I feel following an SFI symposium is intellectually intoxicated.
You can read about the Santa Fe Institute’s history in Mitchell Waldrop’s Complexity. While the book came out during the first decade of the institute’s existence, it captures much of SFI’s spirit.
Finally, a word on how to read this book. Unlike a best-selling thriller, you can read More Than You Know from back to front just as easily as from front to back. But I recommend you simply go to the table of contents, find something that interests you, and jump in.
While the essays cover a range of topics, I categorize them into four parts—investment philosophy, psychology of investing, innovation and competitive strategy, and science and complexity theory. Consider these compartments in a toolbox, each addressing a distinct facet of investing. That said, every essay is meant to stand by itself.
This edition has updated tables and charts and new chapters in each part. Fresh topics include thoughts on management assessment, the role of intuition, applications of game theory, and the mechanisms behind the market’s mood swings.
More Than You Know leverages the research of many top-flight academics. But given the book’s format, there is no way to give those academic ideas their full due. That’s why I assembled a detailed reference section, including suggestions for further reading. Hopefully, the references will give you plenty to dig in to should you choose to follow up on an idea or theme.
My sincerest wish is that More Than You Know provides readers with some intellectual fun—a new perspective, a cool idea, or a path to self-improvement. I hope you get a fraction of the satisfaction from reading the essays that I got from writing them.
Part 1
Investment Philosophy
INTRODUCTION
Out of the blue one day, I received a complimentary e-mail from a guy who had read one of my essays. I was appreciative but didn’t think much of it until I noticed he had found the piece on a Web site dedicated to traders. Given that my focus is almost exclusively on long-term investing, I found it odd that a trader would find use for these ideas.
So I looked to see what else was out there and found something that surprised me even more: one of the essays was highlighted on a gambling Web site. While I study and appreciate gambling methods, I felt—as most self-righteous investors do—that long-term investing is nearly the opposite of most forms of gambling. After thinking about it, though, I realized there is a tie that binds all of these worlds: investment philosophy.
Investment philosophy is important because it dictates how you should make decisions. A sloppy philosophy inevitably leads to poor long-term results. But even a good investment philosophy will not help you unless you combine it with discipline and patience. A quality investment philosophy is like a good diet: it only works if it is sensible over the long haul and you stick with it.
Investment philosophy is really about temperament, not raw intelligence. In fact, a proper temperament will beat a high IQ all day. Once you’ve established a solid philosophical foundation, the rest is learning, hard work, focus, patience, and experience.
Quality investment philosophies tend to have a number of common themes, which the essays in this part reveal. First, in any probabilistic field—investing, handicapping, or gambling—you’re better off focusing on the decision-making process than on the short-term outcome. This emphasis is much easier announced than achieved because outcomes are objective while processes are more subjective. But a quality process, which often includes a large dose of theory, is the surest path to long-term success.
That leads to the second theme, the importance of taking a long-term perspective. You simply cannot judge results in a probabilistic system over the short term because there is way too much randomness. This creates a problem, of course; by the time you can tell an investment process is poor, it is often too late to salvage decent results. So a good process has to rest on solid building blocks.
The final theme is the importance of internalizing a probabilistic approach. Psychology teaches us there are a lot of glitches in the probability module of our mental hardwiring. We see patterns where none exist. We fail to consider the range of possible outcomes. Our probability assessments shift based on how others present information to us. Proper investment philosophy helps patch up some of those glitches, improving the chances of long-term success.
A closing thought: The sad truth is that incentives have diluted the importance of investment philosophy in recent decades. While well intentioned and hard working, corporate executives and money managers too frequently prioritize growing the business over delivering superior results for shareholders. Increasingly, hired managers get paid to play, not to win.
So ask the tough question: Does an intelligent investment philosophy truly guide you or the people running your money? If the answer is yes, great. If not, figure out a thoughtful philosophy and stick with it.
1
Be the House
Process and Outcome in Investing
Individual decisions can be badly thought through, and yet be successful, or exceedingly well thought through, but be unsuccessful, because the recognized possibility of failure in fact occurs. But over time, more thoughtful decision-making will lead to better overall results, and more thoughtful decision-making can be encouraged by evaluating decisions on how well they were made rather than on outcome.
—Robert Rubin, Harvard Commencement Address, 2001
Any time you make a bet with the best of it, where the odds are in your favor, you have earned something on that bet, whether you actually win or lose the bet. By the same token, when you make a bet with the worst of it, where the odds are not in your favor, you have lost something, whether you actually win or lose the bet.
—David Sklansky, The Theory of Poker
Hit Me
Paul DePodesta, a baseball executive and one of the protagonists in Michael Lewis’s Moneyball, tells about playing blackjack in Las Vegas when a guy to his right, sitting on a seventeen, asks for a hit. Everyone at the table stops, and even the dealer asks if he is sure. The player nods yes, and the dealer, of course, produces a four. What did the dealer say? “Nice hit.” Yeah, great hit. That’s just the way you want people to bet—if you work for a casino.
This anecdote draws attention to one of the most fundamental concepts in investing: process versus outcome. In too many cases, investors dwell solely on outcomes without appropriate consideration of process. The focus on results is to some degree understandable. Results—the bottom line—are what ultimately matter. And results are typically easier to assess and more objective than evaluating processes.1
But investors often make the critical mistake of assuming that good outcomes are the result of a good process and that bad outcomes imply a bad process. In contrast, the best long-term performers in any probabilistic field—such as investing, sports-team management, and pari-mutuel betting—all emphasize process over outcome.
Jay Russo and Paul Schoemaker illustrate the process-versus-outcome message with a simple two-by-two matrix (see exhibit 1.1). Their point is that because of probabilities, good decisions will sometimes lead to bad outcomes, and bad decisions will sometimes lead to good outcomes—as the hit-on-seventeen story illustrates. Over the long haul, however, process dominates outcome. That’s why a casino—“the house”—makes money over time.
EXHIBIT 1.1 Process versus Outcome
Source: Russo and Schoemaker, Winning Decisions, 5. Reproduced with permission.
The goal of an investment process is unambiguous: to identify gaps between a company’s stock price and its expected value. Expected value, in turn, is the weighted-average value for a distribution of possible outcomes. You calculate it by multiplying the payoff (i.e., stock price) for a given outcome by the probability that the outcome materi
alizes.2
Perhaps the single greatest error in the investment business is a failure to distinguish between the knowledge of a company’s fundamentals and the expectations implied by the market price. Note the consistency between Michael Steinhardt and Steven Crist, two very successful individuals in two very different fields:I defined variant perception as holding a well-founded view that was meaningfully different from market consensus.... Understanding market expectation was at least as important as, and often different from, the fundamental knowledge.3
The issue is not which horse in the race is the most likely winner, but which horse or horses are offering odds that exceed their actual chances of victory.... This may sound elementary, and many players may think that they are following this principle, but few actually do. Under this mindset, everything but the odds fades from view. There is no such thing as “liking” a horse to win a race, only an attractive discrepancy between his chances and his price.4
A thoughtful investment process contemplates both probability and payoffs and carefully considers where the consensus—as revealed by a price—may be wrong. Even though there are also some important features that make investing different than, say, a casino or the track, the basic idea is the same: you want the positive expected value on your side.
From Treasury to Treasure
In a series of recent commencement addresses, former Treasury Secretary Robert Rubin offered the graduates four principles for decision making. These principles are especially valuable for the financial community:5 1. The only certainty is that there is no certainty. This principle is especially true for the investment industry, which deals largely with uncertainty. In contrast, the casino business deals largely with risk. With both uncertainty and risk, outcomes are unknown. But with uncertainty, the underlying distribution of outcomes is undefined, while with risk we know what that distribution looks like. Corporate undulation is uncertain; roulette is risky.6
The behavioral issue of overconfidence comes into play here. Research suggests that people are too confident in their own abilities and predictions.7 As a result, they tend to project outcome ranges that are too narrow. Over the past eighty years alone, the United States has seen a depression, multiple wars, an energy crisis, and a major terrorist attack. None of these outcomes were widely anticipated. Investors need to train themselves to consider a sufficiently wide range of outcomes. One way to do this is to pay attention to the leading indicators of “inevitable surprises.”8
An appreciation of uncertainty is also very important for money management. Numerous crash-and-burn hedge fund stories boil down to committing too much capital to an investment that the manager overconfidently assessed. When allocating capital, portfolio managers need to consider that unexpected events do occur.9
2. Decisions are a matter of weighing probabilities. We’ll take the liberty of extending Rubin’s point to balancing the probability of an outcome (frequency) with the outcome’s payoff (magnitude). Probabilities alone are insufficient when payoffs are skewed.
Let’s start with another concept from behavioral finance: loss aversion. For good evolutionary reasons, humans are averse to loss when they make choices between risky outcomes. More specifically, a loss has about two and a half times the impact of a gain of the same size. So we like to be right and hence often seek high-probability events.10
A focus on probability is sound when outcomes are symmetrical, but completely inappropriate when payoffs are skewed. Consider that roughly 90 percent of option positions lose money. Does that mean that owning options is a bad idea? The answer lies in how much money you make on the 10 percent of options positions that are profitable. If you buy ten options each for $1, and 9 of them expire worthless but the tenth rises to $25, you’d have an awful frequency of success but a tidy profit.11
So some high-probability propositions are unattractive, and some low-probability propositions are very attractive on an expected-value basis. Say there’s a 75 percent probability that a stock priced for perfection makes its earnings number and, hence, rises 1 percent, but there’s a 25 percent likelihood that the company misses its forecast and plummets 10 percent. That stock offers a great probability but a negative expected value.12
3. Despite uncertainty, we must act. Rubin’s point is that we must base the vast majority of our decisions on imperfect or incomplete information. But we must still make decisions based on an intelligent appraisal of available information.
Russo and Schoemaker note that we often believe more information provides a clearer picture of the future and improves our decision making. But in reality, additional information often only confuses the decision-making process.
Researchers illustrated this point with a study of horse-race handicappers. They first asked the handicappers to make race predictions with five pieces of information. The researchers then asked the handicappers to make the same predictions with ten, twenty, and forty pieces of information for each horse in the race. Exhibit 1.2 shows the result: even though the handicappers gained little accuracy by using the additional information, their confidence in their predictive ability rose with the supplementary data.13
4. Judge decisions not only on results, but also on how they were made. A good process is one that carefully considers price against expected value. Investors can improve their process through quality feedback and ongoing learning.
EXHIBIT 1.2 More Information Does Not Lead to More Accuracy
Source: Russo and Schoemaker, Winning Decisions, 124. Reproduced with permission.
One of my former students, a very successful hedge fund manager, called to tell me that he is abolishing the use of target prices in his firm for two reasons. First, he wants all of the analysts to express their opinions in expected value terms, an exercise that compels discussion about payoffs and probabilities. Entertaining various outcomes also mitigates the risk of excessive focus on a particular scenario—a behavioral pitfall called “anchoring.”
Second, expected-value thinking provides the analysts with psychological cover when they are wrong. Say you’re an analyst who recommends purchase of a stock with a target price above today’s price. You’re likely to succumb to the confirmation trap, where you will seek confirming evidence and dismiss or discount disconfirming evidence.
If, in contrast, your recommendation is based on an expected-value analysis, it will include a downside scenario with an associated probability. You will go into the investment knowing that the outcome will be unfavorable some percentage of the time. This prior acknowledgement, if shared by the organization, allows analysts to be wrong periodically without the stigma of failure.
Prioritizing Process
The investment community, because of incentives and measurement systems, is too focused on outcome and not enough on process. In Rubin’s words:It’s not that results don’t matter. They do. But judging solely on results is a serious deterrent to taking risks that may be necessary to making the right decision. Simply put, the way decisions are evaluated affects the way decisions are made.14
2
Investing—Profession or Business?
Thouhts on Beating the Market Index
I’m beginning to wonder how to persuade the businessperson who owns a large investment management organization that the first and essential priority is to protect the vital core: the classic disciplines of investing as a profession.
—Charles D. Ellis, “Will Business Success Spoil the Investment Management Profession?”
There seems to be some perverse human characteristic that likes to make easy things difficult. It’s likely to continue that way. Ships will sail around the world but the Flat Earth Society will flourish.
—Warren Buffett, “The Superinvestors of Graham-and-Doddsville”
The Scouting Report
To prepare to win, most sports teams scout their competition. The objective is to create a game plan that exploits the competition’s weaknesses and neutralizes its strengths. Teams generally consider intelligent scouti
ng vital to their long-term success.
So what’s the competition for a money manager? Investors with particular objectives can typically invest either with active managers or with index funds. For example, an investor seeking exposure to large-capitalization stocks can place money with a large-cap active manager or with an index fund that mirrors the S&P 500.
Accordingly, we can consider an appropriate index’s return to be a measure of an investor’s opportunity cost—the cost of capital—and that beating the benchmark over time should be an active manager’s measure of success.
So how do active managers fare against the competition? Not well. Over a recent five-year period, the indexes outperformed over forty percent of all active managers, and more than half of active funds underperformed the benchmark over ten years. And this type of result has been consistent over time.1 Given how well the indexes have fared, it might be useful to provide a scouting report on how the indexes compete.
The most widely used benchmark for equity fund performance is the S&P 500. The S&P Index Committee uses five main criteria when looking for index candidates. Here they are—the heart of the strategy that beats the majority of active managers, year in and year out:1. Liquidity. As the committee wants the benchmark to be “investable,” it selects stocks with sufficient liquidity (a ratio of monthly trading volume divided by shares outstanding of at least 0.3) and float.