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Figure 3-4. Performance of 243 large pension plans, 19871999. ( Performance of 243 large pension plans, 19871999. (Source: Dimensional Fund Advisors, Piscataqua Research.) Dimensional Fund Advisors, Piscataqua Research.) Small investors, though, have not "gotten it" yet; hope triumphs over experience and knowledge. If the nation's largest mutual funds and pension funds, with access to the very best information, a.n.a.lysts, and computational facilities, cannot successfully pick stocks and managers, what do you think your your chances are? How likely do you think it is that your broker or financial advisor will be able to beat the market? And if there actually were money managers who could consistently beat the market, how likely do you think it would be that you would have access to them? chances are? How likely do you think it is that your broker or financial advisor will be able to beat the market? And if there actually were money managers who could consistently beat the market, how likely do you think it would be that you would have access to them?

Comic Relief from Newsletter Writers and Other Market Timers The straw that struggling investors most frequently grasp at is the hope that they can increase their returns and reduce risk by timing the market-holding stocks when they are going up and selling them before they go down. Sadly, this is an illusion-one that is exploited by the investment industry with bald cynicism.

It is said that there are only two kinds of investors: those who don't know where the market is going and those who don't know that they don't know. But there is a rather pathetic third kind-the market strategist. These highly visible brokerage house executives are articulate, highly paid, usually attractive, and invariably well-tailored. Their job is to convince the investing public that their firm can divine the market's moves through a careful a.n.a.lysis of economic, political, and investment data. But at the end of the day, they know only two things: First, like everybody else, they don't know where the market is headed tomorrow. And second, that their livelihood depends upon appearing to know. And second, that their livelihood depends upon appearing to know.

We've already come across Alfred Cowles's a.s.sessment of the dismal performance of market newsletters. Some decades later, noted author, a.n.a.lyst, and money manager David Dreman, in Contrarian Market Strategy: The Psychology of Stock Market Success, Contrarian Market Strategy: The Psychology of Stock Market Success, painstakingly tracked opinions of expert market strategists back to 1929 and found that their consensus was mistaken 77% of the time. This is a recurring theme of almost all studies of "consensus" or "expert" opinion; it underperforms the market about three-fourths of the time. painstakingly tracked opinions of expert market strategists back to 1929 and found that their consensus was mistaken 77% of the time. This is a recurring theme of almost all studies of "consensus" or "expert" opinion; it underperforms the market about three-fourths of the time.

The sorriest corner of the investment prediction industry is occupied by market-timing newsletters. John Graham and Campbell Harvey, two finance academicians, recently performed an exhaustive review of 237 market-timing newsletters. They measured the ability of this motley crew to time the market and found that less than 25% of the recommendations were correct, much worse than the chimps' score of 50%. Even worse, there were no advisors whose calls were consistently correct. Once again, the only consistency was found at the bottom of the pile; there were several newsletters that were wrong with amazing regularity. They cited one very well-known advisor whose strategy produced an astounding 5.4% loss during a 13-year period when the S&P 500 produced an annualized 15.9% gain.

More amazing, there is a newsletter that ranks the performance of other newsletters; its publisher believes that he can identify top-performing advisors. The work of Graham and Harvey suggests that, in reality, he is actually the judge at a coin flipping contest. (Although the work of Graham, Harvey, Cowles, and others does suggest one promising strategy: pick the very worst newsletter you can find. Then do the opposite of what it recommends.) When it comes to newsletter writers, remember Malcolm Forbes's famous dictum: the only money made in that arena is through subscriptions, not from taking the advice. The late John Brooks, dean of the last generation of financial journalists, had an even more cynical interpretation: when a famous investor publishes a newsletter, it's a sure tip-off that his techniques have stopped working.

Eugene Fama Cries "Eureka!"

If Irving Fisher towered over financial economics in the first half of the twentieth century, there's no question about who did so in the second half: Eugene Fama. His story is typical of almost all of the recent great financial economists-he was not born to wealth, and his initial academic plans did not include finance. He majored in French in college and was a gifted athlete. To make ends meet, he worked for a finance professor who published-you guessed it-a stock market newsletter. His job was to a.n.a.lyze market trading rules. In other words, to come up with strategies that would produce market-beating returns.

Looking at historical data, he found plenty that worked-in the past. But a funny thing happened. Each time he identified a strategy that had done beautifully in the past, it fell flat on its face in the future. Although he didn't realize it at the time, he had joined a growing army of talented finance specialists, starting with Cowles, who had found that although it is easy to uncover successful past past stock-picking and market-timing strategies, none of them worked going forward. stock-picking and market-timing strategies, none of them worked going forward.

This is a concept that even many professionals seem unable to grasp. How many times have you read or heard a well-known market strategist say that since event X had just occurred, the market would rise or fall, because it had done so eight out of the last ten times event X had previously occurred? The cla.s.sic, if somewhat hackneyed, example of this is the "Super Bowl Indicator": when a team from the old NFL wins, the market does well, and when a team from the old AFL wins, it does poorly.

In fact, if one a.n.a.lyzes a lot of random data, it is not too difficult to find some things that seem to correlate closely with market returns. For example, on a lark, David Leinweber of First Quadrant sifted through a United Nations database and discovered that movements in the stock market were almost perfectly correlated with b.u.t.ter production in Bangladesh. This is not one I'd want to test going forward with my own money.

Fama's timing, though, was perfect. He came to the University of Chicago for graduate work not long after Merrill Lynch had funded the Center for Research in Security Prices (CRSP) in Chicago. This remarkable organization, with the availability of the electronic computer, made possible the storage and a.n.a.lysis of a ma.s.s and quality of stock data that Cowles could only dream of. Any time you hear an investment professional mention the year 1926, he's telling you that he's gotten his data from the CRSP.

Fama had already begun to suspect that stock prices were random and unpredictable, and his statistically rigorous study of the CRSP data confirmed it. But why should stock prices behave randomly? Because all publicly available information, and most privately available information, is already factored into their prices. Because all publicly available information, and most privately available information, is already factored into their prices.

Sure, if your company's treasurer has been recently observed to be acting peculiarly and hurriedly obtaining a Brazilian visa, you may be able to profit greatly (and illegally) from this information. But the odds that you will be able to repeat this feat with a large number of company stocks on a regular basis are zero. And with the increasing sophistication of Securities and Exchange Commission (SEC) surveil-lance apparatus, the chances of pulling this off even once without winding up a guest of the state grow dimmer each year.

Put another way, the simple fact that there are so many talented a.n.a.lysts examining stocks guarantees that none of them will have any kind of advantage, since the stock price will nearly instantaneously reflect their collective collective judgment. In fact, it may be worse than that: there is good data to suggest that the collective judgment of experts in many fields is actually more accurate than their separate individual judgments. judgment. In fact, it may be worse than that: there is good data to suggest that the collective judgment of experts in many fields is actually more accurate than their separate individual judgments.

A vivid, if nonfinancial, example of extremely accurate collective judgment occurred in 1968 with the sinking of the submarine Scorpion. Scorpion. No one had a precise idea of where the sub was lost, and the best estimates of its position from dozens of experts were scattered over thousands of square miles of seabed. But when their estimates were averaged together, its position was pinpointed to within 220 yards. In other words, the market's estimate of the proper price of a stock, or of the entire market, is usually much more accurate than that of even the most skilled stock picker. Put yet another way, the best estimate of tomorrow's price is . . . today's price. No one had a precise idea of where the sub was lost, and the best estimates of its position from dozens of experts were scattered over thousands of square miles of seabed. But when their estimates were averaged together, its position was pinpointed to within 220 yards. In other words, the market's estimate of the proper price of a stock, or of the entire market, is usually much more accurate than that of even the most skilled stock picker. Put yet another way, the best estimate of tomorrow's price is . . . today's price.

There's a joke among financial economists about a professor and student strolling across campus. The student stops to pick up a ten-dollar bill he has noticed on the ground but is stopped by the professor. "Don't bother," he says, "if that were really a ten-dollar bill, someone would have picked it up already." The market behaves exactly the same way.

Let's say that XYZ company is selling at a price of 40 and a clever a.n.a.lyst realizes that it is actually worth 50. His company or fund will quickly buy as much of the stock as it can get its hands on, and the price will quickly rise to 50 dollars per share. The whole sequence usually takes only a few days and is accomplished in great secrecy. Further, it is most often not completed by the original a.n.a.lyst. As other a.n.a.lysts notice the stock's price and volume increase, they take a closer look at the stock and also realize that it is worth 50. In the stock market, one occasionally does does encounter ten-dollar bills lying about, but only very rarely. You certainly would not want to try and make a living looking for them. encounter ten-dollar bills lying about, but only very rarely. You certainly would not want to try and make a living looking for them.

The concept that all useful information has already been factored into a stock's price, and that a.n.a.lysis is futile, is known as "The Efficient Market Hypothesis" (EMH). Although far from perfect, the EMH has withstood a host of challenges from those who think that actively picking stocks has value. There is, in fact, some evidence that the best securities a.n.a.lysts are are able to successfully pick stocks. Unfortunately, the profits from this kind of sophisticated stock a.n.a.lysis are cut short by impact costs, as well as the above-described piggybacking by other a.n.a.lysts. able to successfully pick stocks. Unfortunately, the profits from this kind of sophisticated stock a.n.a.lysis are cut short by impact costs, as well as the above-described piggybacking by other a.n.a.lysts.

In the aggregate, the benefits of stock research do not pay for its cost. The Value Line ranking system is a perfect example of this. Most academics who have studied the system are impressed with its theoretical results, but, because of the above factors, it is not possible to use its stock picks to earn excess profits. By the time the latest issue has. .h.i.t your mailbox or the library, it's too late. In fact, not even Value Line itself can seem to make the system work; its flags.h.i.+p Value Line Fund has trailed the S&P 500 by 2.21% over the past 15 years. Only 0.8% of this gap is accounted for by the fund's expenses. If Value Line cannot make its system work, what makes you think that you can beat the market by reading the newsletter four days after it has left the presses?

There's yet another dimension to this problem that most small investors are completely unaware of: you only make money trading stocks when you know more than those on the other side of your trades. The problem is that you almost never know who those people are. If you could, you would find out that they have names like Fidelity, PIMCO, or Goldman Sachs. It's like a game of tennis in which the players on the other side of the net are invisible. The bad news is that most of the time, it's the Williams sisters.

It never ceases to amaze me that small investors think that by paying $225 for a newsletter, logging onto Yahoo!, or following a few simple stock selection rules, they can beat the market. Such behavior is the investment equivalent of going up against the Sixth Fleet in a rowboat, and the results are just as predictable.

Buffett and Lynch Any discussion about the failure of professional a.s.set management is not complete until someone from the back of the room triumphantly raises his hand and asks, "What about Warren Buffett and Peter Lynch?" Even the most diehard efficient market proponent cannot fail to be impressed with their track records and bestow on them that rarest of financial adjectives-"skilled."

First, a look at the data. Of the two, Buffett's record is clearly the most impressive. From the beginning of 1965 to year-end 2000, the book value of his operating company, Berks.h.i.+re Hathaway, has compounded at 23.6% annually versus 11.8% for the S&P 500. The actual return of Berks.h.i.+re stock was, in fact, slightly greater. This is truly an astonis.h.i.+ng performance. Someone who invested $10,000 with Buffett in 1964 would have more than $2 million today. And, unlike the theoretical graphs which graced the first chapter, there are real investors who have actually received those returns. (Two of whom are named Warren Buffett and Charlie Munger, his Berks.h.i.+re partner.) But it's worth noting a few things.

In the first place, Berks.h.i.+re is not exactly a risk-free investment. For the one-year period ending in mid-March of 2000, the stock lost almost half its value, compared to a gain of 12% for the market. Second, with its increasing size, Buffett's pace has slowed a bit. Over the past four years, he has beaten the market by less than 4% per year. Third, and most important, Mr. Buffett is not, strictly speaking, an investment manager-he is a businessman. The companies he acquires are not pa.s.sively held in a traditional portfolio; he becomes an active part of their management. And, needless to say, most modern companies would sell their metaphorical mothers to have him in a corner office for a few hours each week.

Peter Lynch's accomplishments, while impressive, do not astound as Buffett's do. Further, his personal history, while exemplary, gives pause. For starters, Lynch's public career was much shorter than Buffett's. Although he had worked at Fidelity since 1965, he was not handed the Magellan fund until 1977. Even then, the fund was not opened to the public until mid-1981-before that it was actually the private investment vehicle for Fidelity's founding Johnson family.

From mid-1981 to mid-1990, the fund returned 22.5% per year, versus 16.53% for the S&P 500. A remarkable accomplishment, to be sure, but not in the same league as Buffett's. In fact, not at all that unusual. As I'm writing this, more than a dozen domestic mutual funds have beaten the S&P 500 by more than 6%-Lynch's margin-during the past 10 years. This is about what you would expect from chance alone.

The combination of his performance and Fidelity's marketing muscle resulted in a cash inflow the likes of which had never been seen before. Beginning with a.s.sets of under $100 million, Magellan grew to more than $16 billion by the time Lynch quit just nine years later. Lynch's name and face became household items; even today, more than a decade after his retirement, his white-maned gaunt visage is among the most recognized in finance.

The combination of Magellan's rapidly increasing size and fame's klieg light took its inevitable toll. With an unlucky draw of the cards, Lynch was out of the country in the days leading up to the market crash of 1987. That year, he underperformed the market by almost 5%. Driven by mild public criticism and a stronger need to prove to himself that he still had the magic, he threw himself into his work, turning in good performances in 1988 and 1989. As the fund's a.s.sets swelled, he had to make two major accommodations.

First, he had to focus on increasingly large companies. Magellan originally invested in small- to mid-sized companies: names like La Quinta and Congoleum. But by the end of his tenure, he was buying Fannie Mae and Ford. If there is such a thing as stock selection skill, then the greatest profits should be made with smaller companies that have scant a.n.a.lyst coverage. By being forced to switch to large companies, which are extensively picked over by stock a.n.a.lysts, Lynch found the payoff of his skills greatly diminished.

Second, he had to purchase more and more companies in order to avoid excessive impact costs. By the end of his tenure, Magellan held more than 1,700 names. Both of these compromises drastically lowered his performance relative to the S&P 500 Index. Figure 3-5 Figure 3-5 vividly plots his decreasing margin of victory versus the index. During his last four years, he was only able to outperform the S&P 500 by 2%. Exhausted, he quit in 1990. vividly plots his decreasing margin of victory versus the index. During his last four years, he was only able to outperform the S&P 500 by 2%. Exhausted, he quit in 1990.

Now, having considered these two success stories, let's take a step back and draw some conclusions: * Yes, Lynch and Buffett are skilled. But these two exceptions do not disprove the efficient market hypothesis. The salient observation is that, of the tens of thousands of money managers who have practiced their craft during the past few decades, only two showed indisputable evidence of skill-hardly a ringing endors.e.m.e.nt of professional a.s.set management.* Our eyes settle on Buffett and Lynch only in retrospect. The odds of picking these two out of the pullulating crowd of fund managers ahead of time is nil. (It's important to note that just before Magellan was opened to the public, Fidelity merged two unsuccessful It's bad enough that mutual-fund manager performance does not persist and that the return of stock picking is zero. This is as it should be, of course. These guys are are the market, and there is no way that they can all perform above the mean. Wall Street, unfortunately, is not Lake Wobegon, where all the children are above average. the market, and there is no way that they can all perform above the mean. Wall Street, unfortunately, is not Lake Wobegon, where all the children are above average.

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Figure 3-5. Magellan versus S&P 500: The Lynch years. ( Magellan versus S&P 500: The Lynch years. (Source: Morningstar Principia Pro Plus.) Morningstar Principia Pro Plus.) * For the mutual fund investor, even Peter Lynch's performance was less than stellar. After his talent became publicly known around 1983, this intensely driven individual could continue outperforming the market for just seven more years before he saw the handwriting on the wall and quit at the top of his game. It is not commonly realized that the investing public had access to Peter Lynch for exactly nine years, the last four of which were spent exerting a superhuman effort against transactional expense to maintain a razor thin margin of victory.

"incubator funds"-Ess.e.x and Salem-into it.) On the other hand, there have been hundreds of stories like Tsai's and Sanborn's-managers who excelled for a while, but whose performance flamed out in a hail of a.s.sets attracted by their initial success.

The Really Bad News The bad news is that the process of mutual fund selection gives essentially random results. The really really bad news is that it is expensive. Even if you stick with no-load funds, you will still incur hefty costs. Even the best-informed fund investors are usually unaware as to just how high these costs really are. bad news is that it is expensive. Even if you stick with no-load funds, you will still incur hefty costs. Even the best-informed fund investors are usually unaware as to just how high these costs really are.

Most investors think that the fund's expense ratio expense ratio (ER) listed in the prospectus and annual reports is the true cost of fund owners.h.i.+p. Wrong. There are actually three more layers of expense beyond the ER, which only comprises the fund's advisory fees (what the chimps get paid) and administrative expenses. The next layer of fees is the commissions paid on transactions. These are not included in the ER, but since 1996 the SEC has required that they be reported to shareholders. However, they are presented in the funds' annual reports in such an obscure manner that unless you have an accounting degree, it is impossible to calculate how much return is lost as a percentage of fund a.s.sets. (ER) listed in the prospectus and annual reports is the true cost of fund owners.h.i.+p. Wrong. There are actually three more layers of expense beyond the ER, which only comprises the fund's advisory fees (what the chimps get paid) and administrative expenses. The next layer of fees is the commissions paid on transactions. These are not included in the ER, but since 1996 the SEC has required that they be reported to shareholders. However, they are presented in the funds' annual reports in such an obscure manner that unless you have an accounting degree, it is impossible to calculate how much return is lost as a percentage of fund a.s.sets.

The second extra layer of expense is the bid/ask "spread" of stocks bought and sold. A stock is always bought at a slightly higher price than its selling price, to provide the "market maker" with a profit. (Most financial markets require a market maker-someone who brings together buyers and sellers, and who maintains a supply of securities for ready sale to ensure smooth market function. The bid/ask spread induces organizations to provide this vital service.) This spread is about 0.4% for the largest, most liquid companies, and increases with decreasing company size. For the smallest stocks it may be as large as 10%. It is in the range of 1% to 4% for foreign stocks.

The last layer of extra expense-market impact costs, which we've already discussed-is the most difficult to estimate. Impact costs are not a problem for small investors buying shares of individual companies but are a real headache for mutual funds. Obviously, the magnitude of impact costs depends on the size of the fund, the size of the company, and the total amount transacted. As a first approximation, a.s.sume that it is equal to the spread.

The four layers of mutual fund costs: * Expense Ratio * Commissions * Bid/Ask Spread * Market Impact Costs Taken together, these four layers of expense are least for large-cap funds, intermediate for small-cap and foreign funds, and greatest for emerging market funds. They are tabulated in Table 3-1 Table 3-1.

Table 3-1. The Expense Layers of Actively Managed Mutual Funds The Expense Layers of Actively Managed Mutual Funds [image]

Recall that the nominal return of stocks in the twentieth century was 9.89% per year, and that, based on the DDM, the actual real returns that future investors will receive may be very much smaller. It should be painfully obvious that this is not the return that you, the mutual fund investor, will actually receive. You must subtract from that return your share of the fund's total investment expense.

Now the full magnitude of the problem becomes clear. The bottom row of Table 3-1 Table 3-1 shows the real costs of owning an actively managed fund. In fairness, this does overstate things a bit. Money spent on research and a.n.a.lysis is not a total loss. As we've seen, such research does seem to increase returns, but almost always by an amount less than that spent. How much of the first expense-ratio line is spent on research? Figure about half, if you're lucky. So, even if we use the more generous historical 9.89% stock return as our guideline, active management will lose you about 1.5% in a large-cap fund, 3.3% in a foreign/small cap fund, and 8% in an emerging markets fund, leaving you with 8.4%, 6.6%, and 1.9%, respectively. Not an appetizing prospect. shows the real costs of owning an actively managed fund. In fairness, this does overstate things a bit. Money spent on research and a.n.a.lysis is not a total loss. As we've seen, such research does seem to increase returns, but almost always by an amount less than that spent. How much of the first expense-ratio line is spent on research? Figure about half, if you're lucky. So, even if we use the more generous historical 9.89% stock return as our guideline, active management will lose you about 1.5% in a large-cap fund, 3.3% in a foreign/small cap fund, and 8% in an emerging markets fund, leaving you with 8.4%, 6.6%, and 1.9%, respectively. Not an appetizing prospect.

The mutual fund business has benefited greatly by the high returns of recent years that have served to mask the staggering costs in most areas. One exception to this has been in the emerging markets, where the combination of low a.s.set cla.s.s returns and high expenses has resulted in a ma.s.s exodus of investors.

Bill Fouse's Bright Idea By 1970, professional investors could no longer ignore the avalanche of data doc.u.menting the failure of supposed expert money managers. Up until that point, money management was based on the Great Man theory: find the Great Man who could pick stocks and hire him. When he loses his touch, go out looking for the next Great Man. But clearly, that idea was bankrupt: there were no Great Men, only lucky chimpanzees.

There is no greater test of character than confrontation with solid evidence that the whole of your professional life has been a lie-that the craft that you have struggled so hard to master is worthless. Most money managers fail this trial and are still in the deepest stages of denial. We'll examine their rationalizations for active management at the end of this chapter.

The cream of the crop-thoughtful and intelligent observers like Peter Bernstein (no relation), Ben Graham, James Vertin, and Charles Ellis-painfully reexamined their beliefs and adjusted their practices. Let's summarize the bleak landscape they surveyed: * The gross returns obtained by money managers were in the aggregate the market's, since they were were the market. the market.* The average net return to investors was the market return minus the expense of active stock selection. Since this averaged between 1% and 2%, the typical investor received about 1% to 2% less than the market return.* There seemed to be few managers capable of consistently beating the market. Worst of all, there were almost no managers capable of persistently beating it by the 1% to 2% margin necessary to pay for their expenses.

One of the professionals surveying the scene in the late 1960s was a young man named William Fouse. Excited by the new techniques of portfolio evaluation, he began evaluating the performance of his colleagues at his employer, Mellon Bank. He was aghast-none of those money managers came even close to beating the market. Today, for a dollar, you can pick up The Wall Street Journal The Wall Street Journal and compare the performance of thousands of mutual funds to the S&P 500. It's remarkable to remember that 30 years ago, investors and clients never thought to compare their performance to an index, or, in many cases, even to ask what their performance was. Sadly, the average client and his broker still do not calculate and benchmark their returns. and compare the performance of thousands of mutual funds to the S&P 500. It's remarkable to remember that 30 years ago, investors and clients never thought to compare their performance to an index, or, in many cases, even to ask what their performance was. Sadly, the average client and his broker still do not calculate and benchmark their returns.

The solution was obvious to Mr. Fouse, however. Create a fund that would buy all the stocks in the S&P 500 Index. This could be done with a minimum of expense and was guaranteed to produce very close to the market return. His idea was met with approximately the same enthusiasm as a stink bomb at a debutante ball. Very soon he found himself looking for alternative employment. Fortunately, Fouse wound up at Wells Fargo, which provided a more receptive environment for the ideas of modern finance.

In 1971, the old-school head of the trust department, James Vertin, reluctantly gave the go-ahead and Wells Fargo founded the first index fund. It was an unmitigated disaster. Instead of using Fouse's original S&P 500 idea, they decided to hold an equal dollar amount of all 1,500 stocks on the New York Stock Exchange. Since the stock price of its companies often moved in radically different directions, this required almost constant buying and selling to keep the values of each position equal. This, in turn, resulted in expenses equal to that of an actively managed fund. It was not until 1973 that Fouse's original idea, a fund that held all of the stocks in the S&P 500 in proportion to their market value (and thus did not need rebalancing), was adopted.

At this point, it's necessary to define what we mean by an "index fund." This usually refers to a fund that owns all, or nearly all, of the stocks in a given index, with no attempt to pick those with superior performance. Less commonly, it refers to a fund that holds all stocks meeting certain rigid criteria, usually having to do with market size or growth/value characteristics, such as price-to-book ratio. Today, almost all index funds are "cap weighted." This means that if the value of a stock doubles or falls by half, its proportional contribution in the index does as well, so it is not necessary to buy or sell any to keep things in balance. Thus, as long as the stocks remain in the index, it is not necessary to buy or sell stocks because of changes in market value.

Wells Fargo's index fund was not initially available to the general public, but that was soon to change. A few years later, in September 1976, John Bogle's young Vanguard Group offered the first publicly available S&P 500 Index fund. Vanguard's fund was not exactly a roaring success out of the starting gate. After two years, it had collected only $14 million in a.s.sets. In fact, it did not cross the billion-dollar mark-the radar threshold of the fund industry-until 1988. But as the advantages of indexing became evident to small investors, it took off. For the past few years, it has been running neck-and-neck for the number one spot in a.s.set size with Lynch's old fund, Magellan.

Truth be told, the Vanguard 500 Index Fund has gotten a little too too popular. Of all the major stock indexes, the S&P 500 has done the best in recent years. Much of the new a.s.sets that the fund has collected are "hot money," coming from naive investors who are simply chasing performance. popular. Of all the major stock indexes, the S&P 500 has done the best in recent years. Much of the new a.s.sets that the fund has collected are "hot money," coming from naive investors who are simply chasing performance.

There's another facet to this as well: Dunn's Law, a phenomenon that affects index funds. Dunn's Law states that when an index does well (that is, it does better than other a.s.set cla.s.ses), indexing that particular a.s.set cla.s.s does very well compared to actively managed funds. For example, in each of the years between 1994 and 1998, the Vanguard 500 Index Fund ranked in the top quarter in its peer group of funds-the so-called "large blend" category. But in 2000, it dropped into the lower half of the category. This was largely because the S&P 500 dramatically outperformed all other indexes from 1994 to 1998, but was the worst of the indexes in 2000.

How well has indexing worked? The proper way to judge is to compare like with like-that is, to compare a large-growth index fund with all the funds in the large growth category. Morningstar Inc. is the world's premier purveyor of mutual fund investment tools. I've used their Principia Pro software package to rank the performance of the appropriate Vanguard index fund or S&P/Barra index in its Morningstar category for the five years ending March 31, 2001. The rankings are percentile rankings, ranging from a ranking of 1 for the top percentile and 100 for the worst: [image]

So, in seven of nine categories, the index approach produces above-average results, and in four of the nine categories, top-quarter performance. A few observations are in order.

First, the Morningstar database suffers from survivors.h.i.+p bias-it does not include the deceased funds in each group. Were these to be included, the performance of the indexes would look even better. Second, as the time horizon lengthens, index fund relative performance improves even more. In the words of Jonathan Clements of The Wall Street Journal, The Wall Street Journal, "Performance comes and goes. Expenses are forever." "Performance comes and goes. Expenses are forever."

We have data for four categories-large growth, large blend, large value, and small blend-going back 15 years (ending March 31, 2001). The percentile rankings for these indexes and funds are 24, 20, 17, and 23.

Clearly, the best way to avoid the expensive chimpanzees is to simply keep your expenses to a minimum and buy the whole market with an index index fund. fund.

Taxes If the case I've presented for indexing is not powerful enough for you, then consider the effect of taxes. While many of us hold funds in our retirement accounts, where taxability of distributions is not an issue, most investors also own funds in taxable, nonsheltered accounts.

While it is probably a poor idea to own actively managed funds in general, it is truly a terrible idea to own them in taxable accounts, for two reasons. First, because of their higher turnover, actively managed funds have higher distributions of capital gains, which are taxed at both the federal and state level. The typical actively managed fund distributes several percent of its a.s.sets each year in capital gains. If turnover is high enough, a substantial portion of these will be short-term, which are taxed at the higher ordinary rate: this will amount to a 1% to 4% drag on performance each year. Many index funds allow your capital gains to grow largely undisturbed until you sell.

There is another factor to consider as well. Most actively managed funds are bought because of their superior performance. But, as we've demonstrated above, outperformance does not persist. As a result, most small investors using active-fund managers tend to turn over their mutual funds once every several years in the hopes of achieving better returns elsewhere. What actually happens is that they generate more unnecessary capital gains and resultant taxes. For the taxable investor, indexing means never having to pay the tax and investment consequences of a bad manager. For the taxable investor, indexing means never having to pay the tax and investment consequences of a bad manager.

Why Can't I Just Buy and Hold Stocks on My Own?

Some of you may ask, "If the markets are efficient, why can't I simply buy and hold my own stocks? That way, I'll never sell them and incur capital gains as I would when an index occasionally changes its composition, forcing capital gains in the index funds that track it. And since I'll never trade, my expenses will be even lower than an index fund's."

In fact, until recently, periodic turnover in the stock composition of some indexes has has been a problem at tax time. An excellent example is Vanguard's Small-Cap Index Fund, which in recent years has penalized its taxable shareholders by distributing about 10% of its value each year as capital gains. Fortunately, there are now "tax-efficient" index funds designed for taxable accounts, which are generally able to avoid capital gains. In 1999, Vanguard created its Tax-Managed Small-Cap Index Fund, which minimizes both capital gains and dividend distributions. been a problem at tax time. An excellent example is Vanguard's Small-Cap Index Fund, which in recent years has penalized its taxable shareholders by distributing about 10% of its value each year as capital gains. Fortunately, there are now "tax-efficient" index funds designed for taxable accounts, which are generally able to avoid capital gains. In 1999, Vanguard created its Tax-Managed Small-Cap Index Fund, which minimizes both capital gains and dividend distributions.

But there is a much more important reason why you should not attempt to build your own portfolio of stocks, and that is the risk of buying the wrong ones. You may have heard that you can obtain adequate diversification by holding as few as 15 stocks. This is true only in terms of lowering short-term volatility. But the biggest danger facing your portfolio is not short-term volatility-it's the danger that your portfolio will have low long-term returns.

In other words, you can buy a 15-stock portfolio that has low volatility, but it may put you in the poorhouse just the same. In order to demonstrate the risks of not owning enough stocks, Ronald Surz of PPCA Inc., a provider of investment software, kindly supplied me with some data he generated on the returns of random stock portfolios, which I plotted in Figure 3-6 Figure 3-6. Mr. Surz examined 1,000 random portfolios of 15, 30, and 60 stocks. What you are looking at is the final wealth of these portfolios relative to the market. For example, look at the cl.u.s.ter of bars on the left-the 15-stock portfolios.

First, note the middle black bar and the thick horizontal line through it, which represents the market return at the 50th percentile (the median performance). By definition, this returned $1.00 of wealth after 30 years relative to the market-that is, it got the market return. The bar at the extreme left, representing 5th percentile performance, beating 95% of all of the random portfolios, returned two-and-one-half times the wealth of the market portfolio. At the 25th percentile-the top quarter of performance-you got almost 50% more than the market's final wealth.

Figure 3-6 shows us just how much luck can contribute to portfolio performance. The 60-stock portfolios are about the size of a small mutual fund. Notice that, purely by chance, one out of 20 of the portfolios had a 30-year wealth of $1.77 or more, relative to the market's $1.00. This means that, by accident, these portfolios beat the market by more than 2% per year over 30 years-enough to put any manager in the Mutual Fund Hall of Fame. (The 95th-percentile-by-accident portfolios would similarly be expected to beat the market by more than 10% in any one-year period.) shows us just how much luck can contribute to portfolio performance. The 60-stock portfolios are about the size of a small mutual fund. Notice that, purely by chance, one out of 20 of the portfolios had a 30-year wealth of $1.77 or more, relative to the market's $1.00. This means that, by accident, these portfolios beat the market by more than 2% per year over 30 years-enough to put any manager in the Mutual Fund Hall of Fame. (The 95th-percentile-by-accident portfolios would similarly be expected to beat the market by more than 10% in any one-year period.) Now, go back to the 15-stock portfolios on the left. If you were unlucky and got bottom quarter performance (the fourth bar), after 30 years you only received 70 cents on the dollar. And if you were really unlucky and got bottom 5% performance (95th percentile), then you received only 40 cents on the dollar.

Note how adding more stocks (the 30-stock and 60-stock portfolios) moderates the differences in returns-the lucky picks don't do quite as well, and the bad draws don't do quite as badly. Finally, if you own all the stocks in the market, you will always get the market return, with no risk of failing to obtain it.

Figure 3-6 demonstrates the central paradox of portfolio diversification. Obviously, a concentrated portfolio maximizes your chance of a superb result. Unfortunately, at the same time, it also maximizes your chance of a poor result. This issue gets to the heart of why we invest. You can have two possible goals: One is to maximize your chances of getting rich. The other is to minimize your odds of failing to meet your goals or, more bluntly, to make the likelihood of dying poor as low as possible. demonstrates the central paradox of portfolio diversification. Obviously, a concentrated portfolio maximizes your chance of a superb result. Unfortunately, at the same time, it also maximizes your chance of a poor result. This issue gets to the heart of why we invest. You can have two possible goals: One is to maximize your chances of getting rich. The other is to minimize your odds of failing to meet your goals or, more bluntly, to make the likelihood of dying poor as low as possible.

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Figure 3-6. 30-year wealth of nondiversified portfolios relative to the S&P 500. ( 30-year wealth of nondiversified portfolios relative to the S&P 500. (Source: Ronald Surz.) Ronald Surz.) It's important for all investors to realize that these two goals are mutually exclusive. For example, let's say that you have $1,000 and want to turn it into $1,000,000 within a year. The only legal way that you have a prayer of doing so is to go out and buy 1,000 lottery tickets. Of course, you will almost certainly lose most of your money. On a more mundane level, let's say that in order to retire in ten years, you need to obtain a 30% annualized return during that period. It is quite possible to do this: 113 of the 2,615 stocks with ten-year histories listed in the Morningstar database have had ten-year annualized returns in excess of 30%. Of course, 496 of those 2,615 stocks had negative negative returns and that doesn't count the bankrupted stocks missing from the database. In fact, only 885 of the stocks had returns higher than the S&P 500. returns and that doesn't count the bankrupted stocks missing from the database. In fact, only 885 of the stocks had returns higher than the S&P 500.

In other words, concentrating your portfolio in a few stocks maximizes your chances of getting rich. Unfortunately, it also maximizes your chance of becoming poor. Owning the whole market-indexing-minimizes your chances of both outcomes by guaranteeing you the market return.

A recent innovation-stock "folios"-have been touted as an inexpensive and tax-efficient way for small investors to own portfolios of 30 to 150 stocks. As you can see, these new vehicles fail to provide investors with an adequate degree of diversification.

Take a long, hard look at Figure 3-6 Figure 3-6. Realize that the market return is by no means certain: neither I nor anyone else really knows precisely what it will be. Failing to diversify properly is the equivalent of taking that uncertain return and then going to Las Vegas with it. It's bad enough that you have to take market risk. Only a fool takes on the additional risk of doing yet more damage by failing to diversify properly with his or her nest egg. Avoid the problem-buy a well-run index fund and own the whole market.

Why Indexing "Doesn't Work," and Other Transparent Rationalizations It should be painfully apparent by now that most of the investment industry is engaged in nonproductive work. When faced with ironclad data, it takes intellectual honesty in tank-car quant.i.ty to admit that you are harming your clients, or that your entire professional life has been for naught. Unfortunately, the investment industry is not known for an abundance of critical self-examination.

It is much easier to offer excuses and rationalizations about why you should avoid indexing and continue to use active management. Here are the most common ones you'll hear: * "Indexing did terribly last year." It's true. In some years, "indexing" (by which is usually meant the S&P 500) does sometimes underperform most actively managed funds. For example, in 1977, 1978, and 1979, Vanguard's S&P 500 index fund ranked in the 85th, 75th, and 72nd percentiles of all stock funds. The reason was Dunn's Law: in those three years, small stocks did much better than large stocks. Since the S&P 500 consists only of the largest stocks, it could not benefit from holding better-performing small stocks, whereas the active managers were free to own them. In fact, in any given year, you can predict roughly how well an S&P 500 index fund will rank by comparing the returns of small versus large stocks-it will do well when large stocks do better, and worse when small stocks do better. There's an even more important point to be made here, which is that the "index advantage," typically 1% to 2% per year, is small enough that, in any given year, a large number of actively managed funds will beat the market. Remember Mr. Clements' dictum: "Performance comes and goes. Expenses are forever." As the time horizon lengthens, the odds that an active manager will beat the index by enough to pay for her expenses slowly vanish.* "Indexing works fine for large stocks, but in the less efficient small-cap market, active a.n.a.lysis pays off." This is really the flip side of Dunn's Law. It's true: indexing small stocks has not worked terribly well over the past decade. But it is because small-cap stocks have not done well.

Dimensional Fund Advisors runs the oldest small-cap index fund: It ranks in the 23rd percentile of all surviving surviving small cap funds for the past 15 years. In those years when small caps have done well, indexing them has also done well. For example, for the years 19921994, this Fund ranked in the 13th percentile of the Morningstar small-cap category, and, for the three years ending August 2001, in the 29th percentile. If survivors.h.i.+p bias were taken into account, it would almost certainly have had even higher rankings. Even if it is possible for active managers to successfully pick small stocks, transactional costs in this arena are much higher than with large stocks, so any gains from stock picking will be more than offset by the costs of trading small stocks. small cap funds for the past 15 years. In those years when small caps have done well, indexing them has also done well. For example, for the years 19921994, this Fund ranked in the 13th percentile of the Morningstar small-cap category, and, for the three years ending August 2001, in the 29th percentile. If survivors.h.i.+p bias were taken into account, it would almost certainly have had even higher rankings. Even if it is possible for active managers to successfully pick small stocks, transactional costs in this arena are much higher than with large stocks, so any gains from stock picking will be more than offset by the costs of trading small stocks.

* "Active managers do better than index funds in down markets." This is flat-out wrong-they certainly do not. For example, from January 1973 to September 1974, according to Lipper Inc., the average domestic stock fund lost 47.9%, versus a loss of 42.6% for the S&P 500. And from September to November 1987, the average stock fund lost 28.7%, only slightly better than the S&P 500's 29.5% loss. This is particularly amazing in view of the fact that most actively managed funds generally carry about 5% to 10% in cash, whereas, by definition, index funds hold hardly any.* "Index funds expose you to forced capital gains in the event of a market panic." The argument here is a subtle one: During a market panic, investors will pull their money out of index funds, forcing the funds to sell appreciated shares, saddling the remaining shareholders with unwanted capital gains. Even at first glance, this is a nonstarter. Most index fund investors, like active fund investors, are simply chasing performance and, as such, tend to buy at high prices. As prices fall, the fund can sell those shares at a loss. The fund most vulnerable to this concern is the Vanguard 500 Index Fund, which, because of its age and size, contains some shares bought 25 years ago at a small fraction of their current value. After the events of September 11, its shareholders did not panic and the fund experienced only minuscule net sales. By month's end, the fund contained less than 10% embedded capital gains. Any further fall in prices, even if it precipitated panic selling of the fund, would thus also have completely wiped out the embedded capital gains problem. At the present time, no other Vanguard stock-index fund has any significant remaining embedded capital gains exposure. Vanguard's popular Total Stock Market Fund, which tracks the Wils.h.i.+re 5000, has a significant negative negative capital gains exposure. capital gains exposure.* "An index fund dooms you to mediocrity." Absolutely not: it virtually guarantees you superior performance. Over the typical ten-year period, most money managers would kill for index-matching returns. Money manager and author Bill Schultheis likens the active-versus-indexed fund choice to a sh.e.l.l game in which there are ten boxes, with the following amounts under each box: [image]

You can pick a random box, or you can take a guaranteed payment of $8,000. Yes, it's possible to beat the index, but since we've shown that because of expenses, active managers do worse than chimpanzees, the more likely probability is that you'll also do much worse.

Finally, there is one legitimate criticism that can be leveled at an indexing strategy: You will never have exceptional returns; you will never get fabulously rich. As we've already discussed, poorly diversified strategies do indeed maximize your chances of winding up with bags of money. Unfortunately, they also maximize your chances of ending your days in a trailer park. Giving up a shot at the bra.s.s ring does bother a lot of investors. But that's your own choice; no one else can make it for you.

The market possesses an awesome power that cannot be easily overcome. Were Obi-Wan Ken.o.bi an investment advisor, it's clear what he'd tell his clients: "Use the force. Index your investments."

Chapter 3 SUMMARY.

1. There is almost no evidence of stock-picking skill among professional money managers; from year to year, manager relative performance is nearly random.2. There is absolutely no evidence that anyone can time the market.3. The gross (before expenses) return of the average money manager is the market return.4. The expected net (after expenses) return of a money manager is the market return minus expenses.5. The most reliable way of obtaining a satisfying return is to index (own the whole market).

4.

The Perfect Portfolio Let's summarize the practical lessons from the first three chapters: * Risk and reward are inextricably intertwined. If you desire high returns, you will have to purchase risky a.s.sets-namely, stocks.* You are not capable of beating the market. But do not feel bad, because no one else can, either.* Similarly, no one-not you, not anyone else-can time the market. As Keynes said, it is the duty of shareholders to periodically suffer loss without complaint.* Owning a small number of stocks is dangerous. This is a particularly foolish risk to take, since, on average, you are not compensated for it.

We have already come to some conclusions about what this means: the intelligent investor's stock exposure should be to the entire market. What we haven't yet discussed is exactly how much of your a.s.sets you should expose to the market, or even what we mean by "the market."

These two issues-how much of your overall a.s.sets you should place in stocks and how you should allocate your a.s.sets between different cla.s.ses of stocks-form the core of "a.s.set allocation." In the 1980s, famed investor Gary Brinson and his colleagues published a pair of papers purporting to demonstrate that more than 90% of the variation in investment returns is due to a.s.set allocation and less than 10% to timing and stock selection.

These articles have been hotly contested by pract.i.tioners and academicians ever since. However, this controversy completely misses the point: it does not matter how much of your return is determined by timing or stock selection-no sane investor denies that these are important determinants of return. It's just that you can't control the results of timing and selection-a.s.set allocation is the only factor you can positively impact. In other words, since you cannot successfully time the market or select individual stocks, a.s.set allocation should be the major focus of your investment strategy, because it is the only factor affecting your investment risk and return that you can control. In other words, since you cannot successfully time the market or select individual stocks, a.s.set allocation should be the major focus of your investment strategy, because it is the only factor affecting your investment risk and return that you can control.

It's important to make perfectly clear what we can and cannot do. In examining the behavior of different kinds of portfolios, all we have to rely on is the historical record. It is easy to obtain the monthly or annual returns of various cla.s.ses of stock a.s.sets, feed them into a spreadsheet or a device called a "mean variance optimizer" (MVO) and determine precisely which combinations of these a.s.sets worked the best. But we can only do this in the past tense; it tells us nearly nothing about future portfolio strategy. If anyone tells you that he knows the future's best allocation, nod slowly, slide back several steps, turn, and run like h.e.l.l.

Let me give you a simple example. For the 20 years from 1970 to 1989, the best performing stock a.s.sets were j.a.panese stocks, U.S. small stocks, and precious metals (gold) stocks. At the end of that period, MVOs began making their way to the desktops of financial planners. In went the historical data and out came portfolios consisting almost exclusively of, you guessed it, j.a.panese, U.S. small company, and gold stocks. These turned out to be the worst performing a.s.sets over the next decade. In fact, designing stock portfolios based on past performance is usually a prescription for disaster.

Is it possible to predict which portfolios will perform best in the future? Of course not. In order to do so, you need to be able to predict future a.s.set cla.s.s behavior with a high degree of accuracy. This is the same thing as timing the market which, you already know, cannot be done. And if it could, you would not need an MVO or any of its fancier relatives. You would simply go out and buy the best performing a.s.sets. (Or, to paraphrase Will Rogers, buy only those stocks that are going to go up.) The Portfolio's the Thing First and foremost, it's important that you manage all of your financial a.s.sets-retirement accounts, taxable accounts, kids' college money, emergency money, etc.-as a single portfolio. single portfolio. For example, a.s.sume you own an S&P 500 index fund. If it returns, say, 10% in a given year, does it bother you that some of the stocks in it may have lost more than 80% of their value, as will happen to a few each year? Of course not. A globally diversified portfolio behaves the same way, except that the performance of each component is now more visible to you in the form of returns data in the daily paper and your quarterly statements. As an example, I've listed the returns for 1998, 1999, and 2000 for some of the most commonly used stock a.s.set cla.s.ses: For example, a.s.sume you own an S&P 500 index fund. If it returns, say, 10% in a given year, does it bother you that some of the stocks in it may have lost more than 80% of their value, as will happen to a few each year? Of course not. A globally diversified portfolio behaves the same way, except that the performance of each component is now more visible to you in the form of returns data in the daily paper and your quarterly statements. As an example, I've listed the returns for 1998, 1999, and 2000 for some of the most commonly used stock a.s.set cla.s.ses: [image]