2. Fundamental analysis. The profitability criteria are “four quarters of positive net income on an operating basis.” That’s it.
3. Market capitalization. Companies must have market capitalizations in excess of $4 billion. “The guiding principle for inclusion in the S&P 500 is leading companies in leading U.S. industries.”
4. Sector representation. The committee tries to keep the weight of each sector in line with the sector weightings of the universe (of eligible companies with market cap in excess of $4 billion). It typically does so by adding stocks in underweighted sectors, not by removing stocks in overweighted sectors.
5. Lack of representation. S&P defines the lack of representation as follows: “If the index were created today, this company would not be included because it fails to meet one or more of the above criteria.” Of the more than 1,000 companies removed from the S&P 500 over the past seventy-five years, the overwhelming majority were the result of mergers and acquisitions.
Our scouting report of the S&P 500 might also note that the committee does no macroeconomic forecasting, invests long-term with low portfolio turnover, and is unconstrained by sector or industry limitations, position weightings, investment-style parameters, or performance pressures. Also critical is that index funds closely track the S&P 500 at a very low cost.
Evaluating the Winners
Some actively managed funds clearly do beat the benchmark, even over longer time periods. To see if we could come to some stylized conclusions about how these successful investors did it, we created a screen of the general equity funds that beat the S&P 500 over the decade that ended with 2006 where the fund had one manager and assets in excess of $1 billion (see exhibit 2.1).2
Four attributes generally set this group apart from the majority of active equity mutual fund managers:• Portfolio turnover. As a whole, this group of investors had about 35 percent turnover in 2006, which stands in stark contrast to turnover for all equity funds of 89 percent. The S&P 500 index fund turnover was 7 percent. Stated differently, the successful group had an average holding period of approximately three years, versus roughly one year for the average fund.3
• Portfolio concentration. The long-term outperformers tend to have higher portfolio concentration than the index. For example, these portfolios have, on average 35 percent of assets in their top ten holdings, versus 20 percent for the S&P 500.
• Investment style. The vast majority of the above-market performers espouse an intrinsic-value investment approach; they seek stocks with prices that are less than their value. In his famous “Superinvestors of Graham-and-Doddsville” speech, Warren Buffett argued that this investment approach is common to many successful investors.
• Geographic location. Only a small fraction of high-performing investors hail from the East Coast financial centers, New York or Boston. These alpha generators are based in cities like Chicago, Memphis, Omaha, and Baltimore.
EXHIBIT 2.1 A Sample of General Equity Funds That Beat the S&P 500, 1997-2006
Source: Morningstar, Inc.
Based on the S&P scouting report, these managers seem to follow the index’s strategy with regard to turnover and limited time on macro forecasting, and they deviate from the index’s strategy with regard to concentration and a sharp focus on price-to-value discrepancies.
I am not suggesting that all investors should or can embrace the approach of this group. A broad ecology of investors constitutes a well-functioning market. The market needs investors with varying time horizons, analytical approaches, and capital resources. And many money managers have seen outstanding results pursuing very different strategies than the ones we describe.
Further, it is worth underscoring that the success of these investors is not the result of their portfolio structure but more likely reflects the quality of their investment processes. I once overheard an investor remark to one of these superior performers, “You can have low turnover because your performance is so good.” At once, the manager shot back, “No, our performance is good because we have low turnover.” It would be futile to try to replicate the portfolio attributes (i.e., low turnover, relatively high concentration) without an appropriate process.
That noted, there is still an obvious question: Why is the profile of an average fund so different from these superinvestors?
The Investment Profession Versus the Investment Business
Part of the answer lies in the tension—and perhaps growing imbalance—between the investment profession and the investment business. The investment profession is about managing portfolios to maximize long-term returns, while the investment business is about generating (often short-term) earnings as an investment firm. There is nothing wrong with having a vibrant business, of course, and, indeed, a strong business is essential to attracting and retaining top talent.4 But a focus on the business at the expense of the profession is a problem.
A historical perspective on mutual funds suggests a strong swing to the business side. One person uniquely qualified to document the industry’s changes is the legendary Jack Bogle, who over the past half century has been an industry advocate, visionary, and gadfly. Here are some of the profound changes Bogle notes:5 • The number of common stock funds swelled from 49 in 1945 to over 4,200 in 2006, and they now offer greater specialization as well as geographic scope. The number of new stock funds the industry created (as a percentage of those in existence) reached a record of nearly 600 percent in the 1990s, up from about 175 percent in the 1980s. Notable, too, is that 50 percent of funds failed in the 1990s, and almost 1,000 failed in 2000 through 2004 alone.
• Competition leads to margin compression in most industries. But mutual fund expense ratios, which averaged about 90 basis points in the late 1970s and early 1980s, have risen steadily in recent decades, standing at 156 basis points in 2004. We can attribute a good part of the fee increase to asset-gathering costs. And costs matter: from 1945 through 1965, funds generated returns that were 89 percent of the market’s. From 1983 through 2003, that ratio was 79 percent.
• Until 1958, the SEC restricted sales of management companies. After the courts struck down the SEC’s position, the investment-management industry saw a flurry of initial public offerings and mergers and acquisitions activity. Of the fifty largest fund organizations today, only six are privately held. Eight are public independent companies, U.S. financial conglomerates (twenty-two), foreign financial firms (seven), and major brokerage firms own the rest (six). One mutual remains—Vanguard.
• One nonobvious consequence of active mutual fund marketing, as well as investor proclivity to invest in the latest hot-performing funds, is that the average fund performance has no resemblance to actual investor returns. The reason is that investors crowd into where the performance has been and inevitably suffer as returns revert to the mean. For example, growth stocks saw their greatest quarter of net inflows ($120 billion) in the first quarter of 2000, coincidental with the Nasdaq’s peak, while value funds suffered significant outflows. Bogle calculates that while the market rose 12 percent from 1986 through 2005, the average fund return was less than 10 percent, but the average investor return was only 6.9 percent.
Charley Ellis draws up a list of initiatives an investment firm might pursue to maximize its value as a business. I summarize these in exhibit 2.2. Ellis points out that the crux of the tension between the profession and business is that they operate at different rhythms. Long time horizons, low fees, and contrarian investing are good for the profession. In contrast, short time horizons, higher fees, and selling what’s in demand are good for the business.
EXHIBIT 2.2 Pointers to Make an Investment Firm a Business
Source: Ellis, “Will Business Success Spoil the Investment Management Profession?” 14. Reproduced with permission.
So what should investment firms do? Ellis says it well:The optimal balance between the investment profession and the investment business needs always to favor the profession, because only in devotion to the disciplines of the profession can an org
anization have those shared values and cultures that attracts unusually talented individual professionals.6
I would argue that many of the performance challenges in the business stem from an unhealthy balance between the profession and the business. Many of the investment managers that do beat the market seem to have the profession at the core.
3
The Babe Ruth Effect
Frequency Versus Magnitude in Expected Value
In the real world there is no “easy way” to assure a financial profit. At least, it is gratifying to rationalize that we would rather lose intelligently than win ignorantly.
—Richard A. Epstein,
The Theory of Gambling and Statistical Logic
Batting with the Babe
Hang around a brokerage office and it will only be a matter of time before you hear one of those great-sounding lines, “Hey, if I can be right 51 percent of the time, I’ll come out ahead.” If this thought seems sensible to you, read on. You’re about to discover one of the most important concepts in investing.
First off, let’s acknowledge that the idea that an investor should be right more than wrong is pervasive and certainly comes with intuitive appeal. Here’s a portfolio manager’s story that illuminates the fallacy of this line of thinking.
This well-known investor explained he was one of roughly twenty portfolio managers a company had hired. The company’s treasurer, dismayed with the aggregate performance of his active managers, decided to evaluate each manager’s decision process with a goal of weeding out the poor performers. The treasurer figured that even a random process would result in a portfolio of stocks with roughly one-half outperforming the benchmark, so he measured each portfolio based on what percentage of its stocks beat the market.
This particular portfolio manager found himself in an unusual spot: while his total portfolio performance was among the best in the group, his percentage of outperforming stocks was among the worst. The treasurer promptly fired all of the other “poor” performing managers, and called a meeting with the investor to figure out why there was such a large discrepancy between his good results and his bad batting average.
The portfolio manager’s answer is a great lesson inherent in any probabilistic exercise: the frequency of correctness does not matter; it is the magnitude of correctness that matters. Say that you own four stocks, and that three of the stocks go down a bit but the fourth rises substantially. The portfolio will perform well even as the majority of the stocks decline.
Building a portfolio that can deliver superior performance requires that you evaluate each investment using expected value analysis. What is striking is that the leading thinkers across varied fields—including horse betting, casino gambling, and investing—all emphasize the same point.1 We call it the Babe Ruth effect: even though Ruth struck out a lot, he was one of baseball’s greatest hitters.
The reason that the lesson about expected value is universal is that all probabilistic exercises have similar features. Internalizing this lesson, on the other hand, is difficult because it runs against human nature in a very fundamental way. While it’s not hard to show the flaw in the treasurer’s logic, it’s easy to sympathize with his thinking.
The Downside of Hardwiring
In 1979, Daniel Kahneman and Amos Tversky outlined prospect theory, which identifies economic behaviors that are inconsistent with rational decision making.2 One of the most significant insights from the theory is that people exhibit significant aversion to losses when making choices between risky outcomes, no matter how small the stakes. In fact, Kahneman and Tversky found that a loss has about two and a half times the impact of a gain of the same size. In other words, people feel a lot worse about losses of a given size than they feel good about a gain of a similar magnitude.
This behavioral fact means that people are a lot happier when they are right frequently. What’s interesting is that being right frequently is not necessarily consistent with an investment portfolio that outperforms its benchmark (as the story above illustrates). The percentage of stocks that go up in a portfolio does not determine its performance; it is the dollar change in the portfolio. A few stocks going up or down dramatically will often have a much greater impact on portfolio performance than the batting average.
Bulls, Bears, and Odds
In his provocative book Fooled by Randomness, Nassim Taleb relates an anecdote that beautifully drives home the expected value message.3 In a meeting with his fellow traders, a colleague asked Taleb about his view of the market. He responded that he thought there was a high probability that the market would go up slightly over the next week. Pressed further, he assigned a 70 percent probability to the up move. Someone in the meeting then noted that Taleb was short a large quantity of S&P 500 futures—a bet that the market would go down—seemingly in contrast to his “bullish” outlook. Taleb then explained his position in expected-value terms. Exhibit 3.1 clarifies his thought.
EXHIBIT 3.1 Frequency Versus Magnitude
Source: Author analysis.
In this case, the most probable outcome is that the market goes up. But the expected value is negative, because the outcomes are asymmetric.4 Now think about it in terms of stocks. Stocks are sometimes priced for perfection. Even if the company makes or slightly exceeds its numbers the majority of the time (frequency), the price does not rise much. But if the company misses its numbers, the downside to the shares is dramatic. The satisfactory result has a high frequency, but the expected value is negative.
Now consider the downtrodden stock. The majority of the time it disappoints, nudging the stock somewhat lower. But a positive result leads to a sharp upside move. Here, the probability favors a poor result, but the expected value is favorable.
Investors must constantly look past frequencies and consider expected value. As it turns out, this is how the best performers think in all probabilistic fields. Yet in many ways it is unnatural: investors want their stocks to go up, not down. Indeed, the main practical result of prospect theory is that investors tend to sell their winners too early (satisfying the desire to be right) and hold their losers too long (in the hope that they don’t have to take a loss). We now turn to three leading practitioners in separate probabilistic fields: investing, pari-mutuel betting, and blackjack.
From OTC to OTB
Warren Buffett, undoubtedly one of the twentieth century’s best investors, says that smarts and talent are like a motor’s horsepower, but that the motor’s output depends on rationality. “A lot of people start out with a 400-horsepower motor but only get 100 horsepower of output,” he said. “It’s way better to have a 200-horsepower motor and get it all into output.” 5 And one of the keys is to consider all investment opportunities in terms of expected value. As Buffett’s partner Charlie Munger notes, “one of the advantages of a fellow like Buffett is that he automatically thinks in terms of decision trees.”6 Says Buffett, “Take the probability of loss times the amount of possible loss from the probability of gain times the amount of possible gain. That is what we’re trying to do. It’s imperfect, but that’s what it’s all about.”7
Naturally, coming up with likely outcomes and appropriate probabilities is not an easy task. But the discipline of the process compels an investor to think through how various changes in expectations for value triggers—sales, costs, and investments—affect shareholder value, as well as the likelihood of various outcomes. Such an exercise also helps overcome the loss-aversion pitfall.8
The expected-value mindset is by no means limited to investing. The book, Bet with the Best, offers various strategies for pari-mutuel bettors. Steven Crist, CEO, editor, and publisher of the Daily Racing Form, shows the return on investment, including the track’s take, of a hypothetical race with four horses. To summarize the lesson, he writes, “The point of this exercise is to illustrate that even a horse with a very high likelihood of winning can be either a very good or a very bad bet, and that the difference between the two is determined by only one thing: the odds.�
�� So a horse with a 50 percent probability of winning can be either a good or bad bet based on the payoff, and the same holds true of a 10-to-1 shot. He is saying, in plain words, it is not the frequency of winning that matters, but the frequency times the magnitude of the payoff.9
Crist also solicits a confession from his readers: “Now ask yourself: Do you really think this way when you’re handicapping? Or do you find horses you ‘like’ and hope for the best on price? Most honest players admit they follow the latter path.” Replace the word “handicapping” with “investing” and “horses” with “stocks,” and Crist could be talking about the stock market.
Yet another domain where expected-value thinking is pertinent is blackjack, as Ed Thorp’s best-selling book, Beat the Dealer, shows. In blackjack, the payoffs are set, and the player’s principal task is to assess the probability of drawing a favorable hand. Thorp showed how to count cards in order to identify when the probabilities of a winning hand tilt in a player’s favor. When the odds favor the player, the ideal strategy is to increase the bet (effectively increasing the payout). Thorp notes that even under ideal circumstances, favorable situations only arise 9.8 percent of the time; the house has the advantage the other 90.2 percent.10
So we see that the leading thinkers in these three domains—all probabilistic exercises—converge on the same approach. We also know that in these activities, the vast majority of the participants don’t think through expected value as explicitly as they should. That we are loss averse and avoid losses compounds the challenge for stock investors because we shun situations where the probability of upside may be low but the expected value is attractive.
More Than You Know Page 3