Put another way, since the earnings stream of an auto manufacturer is less reliable than that of a food company, you will pay less for its earnings and dividends because of the high DR you apply to them. All other things being equal (which they never are!), you should earn a higher return from the auto manufacturer than from the food company in compensation for the extra risk involved. This is consistent with what we saw in the last chapter: "bad" (value) companies have higher returns than "good" (growth) companies, because the market applies a higher DR to the former than the latter. Remember, the DR is the same as expected return; a high DR produces a low stock value, which drives up future returns.

Probably the most vivid example of the good company/bad stock paradigm was provided in the popular 1982 book, In Search of Excellence In Search of Excellence, by management guru Tom Peters. Mr. Peters identified numerous "excellent" companies using several objective criteria. Several years later, Mich.e.l.le Clayman, a finance academic from Oklahoma State University, examined the stock market performance of the companies profiled in the book and compared it with a matched group of "unexcellent" companies using the same criteria. For the five-year period following the book's publication, the unexcellent companies outperformed the excellent companies by an amazing 11% per year.

As you might expect, the unexcellent companies were considerably cheaper than the excellent companies. Most small investors naturally a.s.sume that good companies are good stocks, when the opposite is usually true. Psychologists refer to this sort of logical error as "representativeness."

The risk of a particular company, or of the whole market, is affected by many things. Risk, like p.o.r.nography, is difficult to define, but we think we know it when we see it. Quite frequently, the investing public grossly overestimates it, as occurred in the 1930s and 1970s, or underestimates it, as occurred with tech and Internet stocks in the 1960s and 1990s.

The Societal Discount Rate and Stock Returns The same risk considerations that operate at the company level are in play market-wide. Let's consider two separate dates in financial history-September 1929 and June 1932. In the fall of 1929, the mood was ebullient. Commerce and daily living were being revolutionized by the technological marvels of the day: the automobile, telephone, aircraft, and electrical power plant. Standards of living were rapidly rising. And just like today, the stock market was on everyone's lips. People had learned that stocks had much higher long-run returns than any other investment.

In Common Stocks as Long Term Investments Common Stocks as Long Term Investments, a well-researched and immensely popular book published in 1924, Edgar Lawrence Smith showed that stock returns were far superior to bank deposits and bonds. The previous decade had certainly proved his point. At the height of the enthusiasm in 1929, John J. Raskob, a senior financier at General Motors, granted an interview to Ladies Home Journal Ladies Home Journal. The financial zeitgeist was engagingly reflected in a quote from this piece: Suppose a man marries at the age of twenty-three and begins a regular savings of fifteen dollars a month-and almost anyone who is employed can do that if he tries. If he invests in good common stocks and allows the dividends and rights to acc.u.mulate, he will at the end of twenty years have at least eighty thousand dollars and an income from investments of around four hundred dollars a month. He will be rich. And because anyone can do that, I am firm in my belief that anyone not only can be rich but ought to be rich.

Raskob's frugal young man was a genius indeed; compounding $15 per month into $80,000 over 20 years implies a rate of return of over 25%. Clearly, the investing public could be excused for thinking that this was the best time to invest in stocks.

Now, fast forward less than three years to mid-1932 and the depths of the Great Depression. One in three workers is jobless, the gross national product has fallen by almost half, protesting veterans have just been dispersed from Was.h.i.+ngton by Major General MacArthur and a young aide named Eisenhower, and members.h.i.+p in the American Communist Party has reached an all-time high. Even economists have lost faith in the capitalist system. Certainly not a good time to invest, right?

Had you bought stock at one of the brightest moments in our economic history, in September 1929, and held on until 1960, you'd have earned an annualized 7.76%, turning each dollar into $9.65. Not a bad rate of return; but for a stock investment, nothing to write home about. But had you the nerve to buy stocks in June of 1932 and hold on until 1960, you'd have earned an annualized 15.86%, turning each dollar into $58.05. Few did.

Finally, we come to the World Trade Center bombing. Before it, the world was viewed as a relatively safe place to live and invest. In an instant, this illusion was shattered, and the public's perception of risk dramatically increased; the DR rose, resulting in a sharp lowering of price. It's likely that the permanency of this feeling of increased risk will be the primary determinant of stock prices in the coming years. The key point is this: if public confidence remains depressed, prices will remain depressed, which will increase subsequent returns. And if confidence returns, prices will rise and subsequent returns will be lower.

These vignettes neatly demonstrate the relations.h.i.+p between societal risk and investment return. The worst possible time to invest is when the skies are the clearest. This is because perceived risks are low, causing investors to discount future stock income at a very low rate. This, in turn, produces high stock prices, which result in low future returns. The saddest part of this story is that "pie-in-the-sky investing" is both infectious and emotionally effortless-everyone else is doing it. Human beings are quintessentially social creatures. In most of our endeavors, this serves us well. But in the investment arena, our social instincts are poison.

The best possible time to invest is when the sky is black with clouds, because investors discount future stock income at a high rate. This produces low stock prices, which, in turn, beget high future returns. Here also, our psychological and social instincts are a profound handicap. The purchase of stocks in turbulent economic times invites disapproval from family and peers. Of course, only in retrospect is it possible to identify what legendary investor Sir John Templeton calls "the point of maximum pessimism"; n.o.body sends you an overdue notice or a bawdy postcard at the market's bottom.

So even when you are courageous and lucky enough to invest at the low point, throwing money into a market that has been falling for years is a profoundly unpleasant activity. And, of course, you are taking the risk that the system may, in fact, not survive. This brings to mind an apocryphal story centering on the Cuban Missile Crisis of 1962, which has a young options trader asking an older colleague whether to make a long (bullish) bet or a short (bearish) one. "Long!" answers the older man, without a moment's hesitation. "If the crisis resolves, you'll make a bundle. And if it doesn't, there'll be n.o.body on the other side of the trade to collect."

Finally, at any one moment the societal DR operates differently across the globe. Nations themselves can take on growth and value characteristics. For example, 15 years ago, the j.a.panese appeared unstoppable. One by one, they seemed to be taking over the manufacture of automobiles, televisions, computer chips, and even machine tools-product lines that had been dominated by American companies for decades. Signature real estate like Rockefeller Center and Pebble Beach were being s.n.a.t.c.hed up like so many towels at a blue light special. The grounds of the Imperial Palace in Tokyo were said to be worth more than the state of California.

Such illusions of societal omnipotence carry with them a very low DR. Since the j.a.panese income stream was discounted to the present at a very low rate, its market value ballooned, producing very low future returns. The peak of apparent j.a.panese invincibility occurred around 1990. A dollar of j.a.panese stock bought in January 1990 was worth just 67 cents 11 years later, yielding an annualized return of minus 3.59%.

In the early 1990s, the Asian Tigers-Hong Kong, Korea, Taiwan, Singapore, and Malaysia-were the most fas.h.i.+onable places to invest. Their industrious populations and staggering economic growth rates were awesome to behold. Once again, the investment returns from that point forward were poor. The highest return of the five markets was obtained in Hong Kong, where a dollar invested in January 1994 turned into 93 cents by year-end 2000. The worst of the five was Malaysia, where you'd have wound up with just 37 cents.

And, finally, in the new millennium, everyone's favorite market is here at home. Which gets us right back where we started this chapter, with a low discount rate, high prices, and low expected future returns.

The most depressing thing about the DR is that it seems to be quite sensitive to prior stock returns. In other words, because of human society's dysfunctional financial behavior, a rising stock market lowers the perception of risk, decreasing the DR, which drives prices up even further. What you get is a vicious (or virtuous, depending on your point of view) cycle.

The same thing happens in reverse. Because of damage done to stocks in the 1930s, the high DR for stocks outlived the Great Depression, resulting in low prices and high returns lasting for more than a quarter of a century.

Real Returns: The Outlook It's now time to translate what we've learned into a forecast of the long-term expected returns of the major a.s.set cla.s.ses. Whenever you can, you should think about returns in "real" (inflation-adjusted) terms. This is because the use of real returns greatly simplifies thinking about the purchasing power of stocks, making financial planning easier. Most people find this a bit difficult to do at first, but after you get used to it, you'll wonder why most folks use "nominal" (before-inflation) returns.

Let's start with the historical 10% stock reward for the twentieth century. Since the inflation rate in the twentieth century was 3%, the real return was 7%. That's the easy part. The hard part is trying to use nominal returns for retirement planning. Let's say that you're going to be saving for 30 years before retiring. If you're using the 10% nominal return, you'll have to deflate that by the c.u.mulative inflation rate over 30 years. And then, for every year after you retire, you'll have to deflate your nest egg by 3% per year to calculate your real spending power.

It is much simpler to think the problem all the way through in real terms-a 10% nominal return with 3% inflation is the same as a 7% return and no inflation2; no adjustments are necessary. A real dollar in 50 years will buy just as much as it will now. (And before World War I, when money really was hard gold and silver, that's how folks thought. There's an old economist's joke: An academic is questioning a stockbroker about investment returns, and asks him, "Are those real returns?" The broker responds, "Of course they are, I got them from The Wall Street Journal The Wall Street Journal yesterday!") From now on, we're going to talk about real returns whenever possible. yesterday!") From now on, we're going to talk about real returns whenever possible.

For starters, the DDM tells us to expect cash to yield a zero real return, bonds to have an approximately 3% real return, and stocks in general to have about a 3.5% real return. In the current environment, is it possible to find a.s.sets with higher DRs and expected returns? Yes. As this is being written, except perhaps for j.a.pan, foreign stocks are slightly cheaper than U.S. stocks. But even in j.a.pan, dividend multiples are lower than in the U.S., so expected returns abroad may be slightly more than domestic expected returns. Small stocks also sell at a slight discount to large stocks around the globe, and so too have slightly higher expected returns.

Next, there's value stock investing. Value stock returns are impossible to estimate using the traditional methods, because most of the excess return arises from the slow improvement in valuations that occurs as doggy stocks become less doggy over time.

This is a difficult process to model, but a general observation or two are in order. As recently as five years ago, if you had sorted the S&P 500 by the earnings multiple ("P/E ratio": the number of dollars of stock needed to buy a dollar of current earnings), you would have found that the top 20% of stocks typically sold at about twice the multiple of the bottom 80%-at about 20 and 10 times earnings, respectively. As 2002 began, the top 20% and bottom 80% of companies sold at 64 and 20 times earnings, respectively-a more than threefold difference between top and bottom. This is not nearly as bad as the sevenfold difference at the market peak in the spring of 2000, but large nevertheless.

So, absent a permanent new paradigm, the historical 2% extra return from value stocks seems a good bet, yielding large-value real expected returns of about 5% and small-value real expected returns of about 7%.

Real Estate Investment Trusts (REITs) are the stocks of companies that manage diversified portfolios of commercial buildings. One example is the Was.h.i.+ngton Real Estate Investment Trust (WRE), which owns a large number of office buildings in the D.C. area. By law, WRE is required to pay out 90% of its earnings as income. Because of this enforced payment of dividends, REITs currently yield an average of about 7% per year. The downside is that because they can reinvest only a small portion of their profits, they usually carry a large amount of debt and, in the aggregate, do not grow well. Since 1972, they have increased their earnings by about 3% per year. This was about 2% less less than the inflation rate during the period. Add a 7% dividend to a negative 2% real earnings growth and the expected real return of REITs is about 5% per year. than the inflation rate during the period. Add a 7% dividend to a negative 2% real earnings growth and the expected real return of REITs is about 5% per year.

Stocks in many countries have been battered by the "Asian Contagion" of the late nineties, and their markets now yield 3% to 5% dividends. Most of the "Tiger" countries, as well as many South American stock markets, fall into this category. The future long-term dividend growth rate in these nations is anybody's guess, but it is quite possible that they will resume their earlier economic growth to produce healthy stock returns going forward.

The stocks of gold and silver mining companies are an intriguing a.s.set cla.s.s. They currently yield dividends of about 3%, and the most conservative a.s.sumption is that they will have zero real earnings and dividend growth, for a total real expected return of 3%-about the same as bonds and cash. In the long run, they offer excellent inflation protection. But because these stocks are very sensitive to even small changes in gold prices, they are extremely risky. We'll talk about why you might want a small amount of exposure to these companies in Chapter 4 Chapter 4, when we discuss portfolio theory.

From time to time, it makes sense to take credit risk. This is an area we've touched on earlier. The bonds of companies with low credit ratings carry high yields-these are the modern equivalent of the Greek bottomry loans discussed in the last chapter. At present, such "high yield," or "junk," bonds, carry coupons of approximately 12%, compared to only about 5% for Treasury bonds. Are these a worthwhile investment? Many of these companies will default on their bonds and then go bankrupt. (Default does not necessarily imply bankruptcy and total loss. Many companies-about 30%-will temporarily default, then resume payment of interest and princ.i.p.al. Bondholders frequently recover some of their a.s.sets from bankrupt companies.) The default rate on these companies is about 6% per year, on average, and the "loss rate"-the percent loss of capital each year from these bonds-appears to be about 3% to 4% per year. I cannot stress the word "average" enough in this context. In good times, the loss rate is near zero. And in bad times, it can be quite high-approaching 10% per year.

So, if you are earning 7% more in interest per year than with a Treasury bond, but you are losing an average of 4% per year on bankruptcies, then in the end you should still be left with 3% more return than Treasuries. Most investors would consider this to be an adequate tradeoff. But it's important to understand that during a recession, even the market value of the surviving bonds may temporarily decrease. For example, during the 19891990 junk bond debacle, price declines approaching 20% were common even in the healthiest issues.

If you're going to invest in junk bonds, you have to keep your eye on the yield spread between Treasuries and junk. In Figure 2-6 Figure 2-6, I've plotted this junk-Treasury spread (JTS) over the recent past. Note how the JTS is, more often than not, quite low-in fact, lower than even the historical loss rate! This irrational behavior is explained by investors "reaching for yield": unhappy with low bond and bill rates, they take on more credit risk than they had bargained for in a foolish attempt to get a few bits of extra return. When the JTS is below 5%, don't even think about buying junk. (You can find the high-yield and Treasury yields in the "Yield Comparisons" table in the back section of The Wall Street Journal The Wall Street Journal. You'll have to subtract the Treasury yield from the junk yield yourself.) Treasury bills are the ultimate "risk-free investment." Their expected real return is very difficult to predict, as the yield can change quite quickly and dramatically, ranging from a low of nearly zero in the late 1930s to briefly more than 20% in the early 1980s. Currently, the T-bill yield is less than 2%, or about the same as the inflation rate, for a real zero return. And, as we saw in Chapter 1 Chapter 1, their actual long-term real return is not much greater than zero.

Lastly, there are TIPS (Treasury Inflation Protected Securities). For those investors who are risk-averse, it's tough to beat them, as they provide a 3.4% real yield. You can design the amount of inflation protection you want by balancing maturities; the maximum comes with the 3.375% TIPS of April 2032, the cost of which is 30 years of "real interest rate risk," the possibility that real real interest rates will rise after you have bought them. This is not the same thing as (and certainly much less scary than) the inflation risk experienced by conventional bonds, where the fixed interest payments can be seriously eroded by sustained inflation. After all, with TIPS, inflation is what you're protecting against. interest rates will rise after you have bought them. This is not the same thing as (and certainly much less scary than) the inflation risk experienced by conventional bonds, where the fixed interest payments can be seriously eroded by sustained inflation. After all, with TIPS, inflation is what you're protecting against.

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Figure 2-6. Junk-treasury spread, 19882000. ( Junk-treasury spread, 19882000. (Source: Grant's Interest Rate Observer.) In Table 2-2 Table 2-2, I've summarized reasonable expected real returns, derived from the DDM. Understand that "expected" returns are just that. In finance, as in life, there is often a huge chasm between what is expected and what actually transpires. The estimation of foreign stock returns is particularly perilous. Between the breakdown of the 1944 Bretton Woods agreement, which fixed currency exchange rates among the major developed nations, and the advent of increasingly active foreign-currency-denominated futures and options markets, the currencies have grown increasingly volatile. This means that the gap between expected versus realized returns for foreign stocks is liable to be especially large.

The "Realized-Expected Disconnect"

In the first chapter we talked about the history of past stock returns-what economists call "realized returns." These realized returns were quite high. In fact, in the past decade, a small industry has arisen that thrives on the promotion and sale of this optimistic data. The message of this happy band of brothers is that past is prologue: because we have had high returns in the past, we should expect them in the future.

Table 2-2. Expected Long-Term Real Returns Expected Long-Term Real Returns [image]

The ability to estimate future stock and bond returns is perhaps the most critical of investment skills. In this chapter, we've reviewed a theoretical model that allows us to compute the "expected returns" of the major a.s.set cla.s.ses on an objective, mathematical basis. The message from this approach is not nearly as agreeable. Which should we believe: the optimism of historical returns, or the grim arithmetic of the Gordon Equation?

It should be obvious by now where my sympathies lie. Warren Buffett famously said that if stock returns came from history books, then the wealthiest people would be librarians. There are numerous examples of how historical returns can be highly misleading. My favorite comes from the return of long Treasury bonds before and after 1981. For the 50 years from 1932 to 1981, Treasury bonds returned just 2.95% per year, almost a full percent less than the inflation rate of 3.80%. Certainly, the historical record of this a.s.set was not encouraging. And yet, the Gordon Equation told us that the bond yield of 15% was more predictive of its future return than the historical data. Over the next 15 years, the return of the long Treasury was in fact 13.42%-slightly lower than the predicted return because the coupons had to be reinvested at an ever-falling rate.

The fundamental investment choice faced by any individual is the overall stock/bond mix. It seems more likely that future stock returns will be closer to the 3.5% real return suggested by the Fisher DDM method than the 7% historical real gain. If, as we calculated earlier, stock and bond returns are going to be similar going forward, then even the most aggressive, risk-tolerant individual should have no more than 80% exposure to stocks.

Unfortunately, although the DDM informs us well about expected returns, it tells us nothing about future risk. We are dependent on the pattern of past returns to inform us of the potential risks of an a.s.set. And in this regard, I believe that the historical data serve us well. Although anything is possible in finance, it is hard to imagine the stock markets of the next century throwing anything our way that would surpa.s.s the 19291932 bear market.

In the coming chapters, we'll explore how to use the lessons we've learned to construct portfolios that give us the best chance of reaping the most reward with the minimum necessary risk.

CHAPTER 2 SUMMARY.

1. The ability to estimate the long-term future returns of the major a.s.set cla.s.ses is perhaps the most important investment skill that an individual can possess.2. A stock or bond is worth only the future income it produces. This income stream must be reduced in value, or "discounted," to the present, to reflect the fact that it is worth less than currently received income.3. The rate at which that income is discounted is inversely related to the a.s.set's value; a high discount rate (DR) lowers the a.s.set's value.4. The DR is the same as the a.s.set's expected return; it is determined by the a.s.set's perceived risk. The higher the risk, the higher the DR/expected return.5. In the long term, the a.s.set's DR/expected return is approximately the sum of the dividend yield and the growth rate. The current high price and low dividend rate of stocks suggest that they will have much lower returns in the future than they have had in the past.6. The above considerations pertain only to long-term returns (more than 20 years). Over shorter periods, a.s.set returns are almost exclusively related to speculative factors and cannot be predicted.7. The methods we discussed in this chapter suggest that the returns of stocks and bonds will be similar over the coming decades. This means that even the most aggressive investors should not have more than 80% of their savings in stocks.

3.

The Market Is Smarter Than You Are I know what you're thinking: "Okay, you've convinced me. Future market returns will not be that high. But that doesn't matter, because I can beat the market. Or, I may not be able to beat the market myself, but I'm sure I can find a mutual fund/stock broker/financial advisor who can."

Pretend, just for a moment, you live in an obscure tropical country called "Randomovia." It's really quite a wonderful place-lush, prosperous, with universal high-speed Internet access. But it has one serious problem: a rampant chimpanzee population. In order to keep the chimps happy, the Randomovians periodically round them up, dress them in expensive suits, place them in luxurious offices, and allow them to manage the nation's investment pools. And since chimps are very jealous creatures, humans are not allowed to manage money. Further, it's a well-known fact that chimps love playing darts; they pick stocks by hurling these projectiles at the stock page.

This means three things about Randomovia: * Over any given period of time, some of the chimpanzees will be lucky and obtain high returns.* The past performance of a chimp at selecting stocks has no bearing on his future performance. Last year's, or last decade's, winner will just as likely be a loser as a winner next time.* The average performance of all the chimpanzees will be the same as the market's, since chimps are the only ones who can buy and sell.

The chimps each have about a 50% chance of beating the market. There's only one problem: The investment pools they manage charge the Randomovians 2% of a.s.sets each year in expenses. In any given year, the differences in performance are great enough that the 2% expense doesn't matter that much. But because of the 2% drag, instead of 50% of the chimps beating the market each year, only about 40% of them do. With the pa.s.sage of time, however, the law of averages catches up with all but the luckiest chimps. After 20 years, only about one in ten beats the market by more than their 2% annual expenses. So, the odds of your picking that winning chimpanzee are . . . one in ten.

Well, dear readers, I have very bad news. For the past several decades, financial economists have been studying the performance of all types of investment professionals, and their message is unambiguously clear: Welcome to Randomovia!

Better Living Through Statistics Although the modern scientific revolution started with the mathematical modeling of the physical world by Copernicus, Kepler, Galileo, and Newton, it was not until the nineteenth century that social scientists-sociologists, economists, and psychologists-began the serious mathematical study of social phenomena. In Chapter 1 Chapter 1, we saw that a dramatic improvement in the quality of financial data occurred at the beginning of the twentieth century. This was the result of a ma.s.sive collaborative effort to collect and a.n.a.lyze stock and bond prices. As researchers began to examine the aggregate performance of stocks and bonds, it was only natural that they began by looking at the behavior of money managers.

Until relatively recently, no one questioned the notion that investing was a skill, just like medicine, law, or professional sports. Ability, training, and hard work should should result in superior performance. The best pract.i.tioners result in superior performance. The best pract.i.tioners should should excel year after year. A skilled broker or money manager excel year after year. A skilled broker or money manager should should be worth his weight in gold. In this chapter, we'll examine the utter demolition of that belief system and the emergence of a powerful new theory for understanding stock and bond market behavior-the efficient market hypothesis. be worth his weight in gold. In this chapter, we'll examine the utter demolition of that belief system and the emergence of a powerful new theory for understanding stock and bond market behavior-the efficient market hypothesis.

Alfred Cowles III Gets Burned Most great financial innovators come from humble circ.u.mstances-nothing arouses fascination with financial a.s.sets quite like their absence. Or, as someone born to great wealth once explained to me, if you are raised in the desert, all you think about is water. But the average Western citizen, who can get it from the tap at will, hardly considers it at all. Those raised with great wealth think about money the way most of us think about water-if you want some, just turn on the faucet! Which is why Alfred Cowles III was a most unlikely financial pioneer; his family owned a large chunk of the Chicago Tribune company and was extremely wealthy. After duly graduating from Yale in 1913, he started working as a reporter, but developed tuberculosis and was sent to a sanatorium in Colorado Springs to recover. With time on his hands, he began involving himself in the family finances.

He subscribed to many financial newsletters and by the mid-1920s was regularly reading about two dozen of them. He was stunned at the abysmal quality of advice. The ferocious bear market of 192932 was completely unforeseen by all of them, and Cowles's family suffered as a consequence. He also found that the newsletters' recommendations during the 1920s bull market had been nothing to write home about either.

Cowles's signature characteristic was his love of collecting and a.n.a.lyzing data. He began recording the newsletters' recommendations and a.n.a.lyzing their predictive value. Eventually, he found his way to none other than Irving Fisher, who happened to be the president of a small impoverished academic organization dedicated to the study of financial data-the Econometric Society. With his family wealth, Cowles was a G.o.dsend to the struggling group, and in 1932, he endowed the Cowles Foundation, dedicated to the statistical study of financial a.s.sets.

The importance of his generosity and research cannot be overstated. He was directly responsible for the collection and a.n.a.lysis of most of the nation's stock and bond data from 1871 to 1930, and, more importantly, he provided the inspiration for most of the security research that followed. Without Cowles, we would still be financial cave dwellers, stumbling around blindly in the dark.

Cowles's first organized research project, predictably enough, studied financial newsletters. His report, published in the first edition of Econometrica, Econometrica, the foundation's journal, was simply t.i.tled, "Can Stock Market Forecasters Forecast?" The article had an introductory abstract consisting of just three words: "It is doubtful." He evaluated the recommendations of the most prestigious financial newsletters and financial services and a.n.a.lyzed the stock purchases of the largest group of inst.i.tutional investors at the time-fire insurance companies. the foundation's journal, was simply t.i.tled, "Can Stock Market Forecasters Forecast?" The article had an introductory abstract consisting of just three words: "It is doubtful." He evaluated the recommendations of the most prestigious financial newsletters and financial services and a.n.a.lyzed the stock purchases of the largest group of inst.i.tutional investors at the time-fire insurance companies.

His results were stunning. The stock-picking abilities of the financial services and insurance companies were awful-only about one-third equaled or beat the market. And the performance of the market-timing newsletters, as he had suspected for years, was even worse. In almost all cases, investors would have been better off flipping coins than following their advice. Cowles found that the very best newsletter results could easily be obtained by random choice. But what was truly stunning was that the results of the worst newsletters could not not be explained purely by chance. In other words, although there was no evidence of skill among the best newsletter writers, the worst seemed possessed of a special inept.i.tude. This is a pattern that we shall encounter repeatedly: among finance professionals, the best results can easily be explained by chance, but the worst performers seem to maintain an almost uncanny incompetence. be explained purely by chance. In other words, although there was no evidence of skill among the best newsletter writers, the worst seemed possessed of a special inept.i.tude. This is a pattern that we shall encounter repeatedly: among finance professionals, the best results can easily be explained by chance, but the worst performers seem to maintain an almost uncanny incompetence.

It is no coincidence that the explosion of knowledge regarding investment management occurred when it did. The statistical computations involved in Cowles's study could not have been done by hand. He was the first financial economist to make use of the new punch card machines being produced by the Hollerith Corporation. (Another investment giant, Benjamin Graham, also had a connection with Hollerith. As a young a.n.a.lyst in the 1920s, he almost lost his first job by recommending that his conservative employer purchase stock in the company. A few years later, Hollerith decided that a more modern-sounding name would be appropriate: International Business Machines.) But it was not until the commercial availability of electronic computers that things really got going. In 1964, academic Michael Jensen decided to look at the performance of mutual fund managers, testing for evidence of stock selection skill. Because most of the funds he examined held a significant portion of cash, almost all of them underperformed the market. But, of course, with their lower returns came greater safety. So he used sophisticated computer-based statistical methods to correct for the amount of cash and test the significance of his results.

Figure 3-1 is a plot of how the funds did relative to the market, adjusted for risk. It displays the performance of the funds on a gross basis, that is, before the funds' management fees are subtracted. The thick vertical black line in the middle of the graph represents the market performance. The bars on the left represent the number of funds underperforming the market, and the bars on the right represent funds outperforming it. is a plot of how the funds did relative to the market, adjusted for risk. It displays the performance of the funds on a gross basis, that is, before the funds' management fees are subtracted. The thick vertical black line in the middle of the graph represents the market performance. The bars on the left represent the number of funds underperforming the market, and the bars on the right represent funds outperforming it.

Only 48 funds out of 115 outperformed the market; 67 underperformed it. As predicted, the average performance was close to that of the market (actually, 0.4% less, annualized).

Figure 3-2 demonstrates fund performance on a net basis-that is, after the funds' management fees have been subtracted. This is the return that the shareholders actually see. demonstrates fund performance on a net basis-that is, after the funds' management fees have been subtracted. This is the return that the shareholders actually see.

Essentially, this s.h.i.+fted fund performance about 1% to the left, so that only 39 outperformed, versus 76 underperforming. Even more interesting, while only one fund outperformed the market by more than 3% per year, 21 underperformed it by more than 3%! Again, we find the pattern seen in Cowles's original work: no evidence of skill at the top of the heap, but at the bottom of the heap, the strong suggestion that some managers possess a special inept.i.tude.

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Figure 3-1. Mutual funds 19461964: gross returns relative to market.0 = market return, average fund = 0.4% per year. ( Mutual funds 19461964: gross returns relative to market.0 = market return, average fund = 0.4% per year. (Source: Michael Jensen, Michael Jensen, Journal of Finance, Journal of Finance, 1965.) 1965.) And it goes downhill from there. All of the mutual funds studied carried sales loads (a fee, typically 8.5% of the purchase amount), which Jensen did not take into account. So the funds' investors actually obtained even lower returns than shown in Figure 3-2 Figure 3-2. Except at the bottom end, the distributions found in Figures 3-1 Figures 3-1 and and 3-2 3-2 are precisely what you'd expect from a bunch of dart-throwing chimpanzees: are precisely what you'd expect from a bunch of dart-throwing chimpanzees: * The average fund produces a gross gross return equal to the market's. return equal to the market's.* The average investor receives a net net return equal to the market's minus expenses. return equal to the market's minus expenses.* The "best" managers produce returns that are easily explained by the laws of chance.

Are we in Randomovia yet? Almost. If we actually were in Randomovia, we would find that above-average performance does not persist, primarily due to the chimpanzees' random stock picking methodology (throwing darts). In fact, subsequent researchers soon found this to be the case in the real world as well.

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Figure 3-2. Mutual funds 19461964: net returns relative to market .0 = market return, average fund = 1.1% per year. ( Mutual funds 19461964: net returns relative to market .0 = market return, average fund = 1.1% per year. (Source: Michael Jensen, Michael Jensen, Journal of Finance, Journal of Finance, 1965.) 1965.) Since Jensen's study, literally dozens of studies have duplicated his findings and verified the last prediction: past superior performance has almost no predictive value. Unfortunately, almost none of the subsequent studies are understandable to the lay reader. The mid-1960s, when Jensen's study was published in the Journal of Finance, Journal of Finance, was about the last time that the average college-educated person could get through an academic finance article without falling asleep. Vast improvements in statistical and computational sophistication in financial research meant that, in most cases, the results were impossible to translate into plain English. In Twain's words, financial research had become "chloroform in print." was about the last time that the average college-educated person could get through an academic finance article without falling asleep. Vast improvements in statistical and computational sophistication in financial research meant that, in most cases, the results were impossible to translate into plain English. In Twain's words, financial research had become "chloroform in print."

Typically, these studies show that there is some brief persistence in performance; last year's top performers will beat the average fund by perhaps 0.25% to 0.5% the next year. But after that, nothing. And excellent past performance over longer periods is of no benefit at all. Since a 0.25% to 0.50% return boost is much lower than the expenses incurred in fund management, this is not a game worth playing. this is not a game worth playing.

Of the dozens of studies done on mutual fund performance persistence, the most optimistic found that if you invested in the top 10% of last year's funds, you would match, but not exceed, the performance of an index fund with low expenses. This "strategy" requires a near-total fund turnover each year. This is the best-case scenario for actively managed mutual funds-turn your portfolio over once a year, and you might-just might-match the index. And that's before taxes. In a taxable account, this strategy would eat you alive with short-term capital gains, which are penalized at your full marginal federal and state rates.

One delightful exception to the tedium of this research is an ongoing study by Dimensional Fund Advisors and S&P/Micropal, which looks at what happens to the investor who picks a mutual fund with excellent past performance. For each five-year period, they select the 30 best-performing domestic mutual funds. They then follow the performance of these best performers forward.

I've displayed their data in Figure 3-3 Figure 3-3.

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Figure 3-3. Subsequent performance of top-30 funds. ( Subsequent performance of top-30 funds. (Source: Standard and Poor's/Mieropal/Dimensional Fund Advisors.) Standard and Poor's/Mieropal/Dimensional Fund Advisors.) In order to understand this graph, take a look at the first group of bars on the left. The first (solid) bar represents the subsequent performance of the top 30 domestic stock funds from 1970 to 1974. In other words, the funds were selected for their superior performance from 1970 to 1974; then their performance from 1975 to 1998 was followed and compared to that of the average mutual fund (checkered bar) and the S&P 500 (gray bar). Note that for some of the periods, the previous best-performing funds did slightly better than average, and for some, worse than average. But in each instance, the previous winners underperformed the S&P 500 index going forward, sometimes by a large margin. But in each instance, the previous winners underperformed the S&P 500 index going forward, sometimes by a large margin. This is cla.s.sic Randomovian behavior; we are once again looking at chimps, not skilled operators. This is cla.s.sic Randomovian behavior; we are once again looking at chimps, not skilled operators.

Actually, because of "survivors.h.i.+p bias," these studies understate the case against active management. We've already come across survivors.h.i.+p bias in Chapter 1 Chapter 1 when we discussed the differences in stock and bond returns among nations. In this case, when you look at the prior performance of all the funds in your daily newspaper, or even a sophisticated mutual fund database like Morningstar's Principia Pro, you are not looking at the complete sample of funds; when we discussed the differences in stock and bond returns among nations. In this case, when you look at the prior performance of all the funds in your daily newspaper, or even a sophisticated mutual fund database like Morningstar's Principia Pro, you are not looking at the complete sample of funds; you're looking only at those that have survived. you're looking only at those that have survived. The funds that were recently put out of their misery because of poor performance do not make it into the record unless you go out of your way to find them. It's estimated that including these defunct funds decreases the actual average active fund performance by about 1.5% per year. So, actively managed funds are even worse than they look. The funds that were recently put out of their misery because of poor performance do not make it into the record unless you go out of your way to find them. It's estimated that including these defunct funds decreases the actual average active fund performance by about 1.5% per year. So, actively managed funds are even worse than they look.

In plain English, an actively managed fund exposes you to the risk that its return may be so bad that the fund company will want to obliterate its record. In other words, you may wind up owning a fund that, like so many of Comrade Stalin's unlucky colleagues, wound up having its face airbrushed out of official photographs.

More Bad News: Market Impact The dominance of the investment market by mutual funds is a relatively recent phenomenon. Before the 1960s, mutual funds were largely ignored by the investing public because of the high sales fees, usually 8.5%, and uninspiring performance. Further, 40 years ago, mutual funds were still a.s.sociated in the public's mind with the "investment trusts" of the 1920s. These were the equivalent of today's closed-end mutual funds, except that they made extensive use of leverage (borrowed funds). Because of this leverage, many declared bankruptcy in the first stages of the 1929 crash.

All that changed in the 1960s. In 1957, Fidelity put a young manager named Gerald Tsai in charge of its Capital Fund. Tsai's specialty was growth-stock investing, and in the mid-1960s, growth companies-Xerox, IBM, LTV, Polaroid-came very much into vogue. The Go-Go Years, as they were called, were almost a carbon copy of today's tech/Internet binge. Exciting new technologies were being brought to market, and the companies at the cutting edge zoomed, eventually selling at prices approaching those seen in the more recent bubble.

Tsai was the prototypical "gunslinger," as this type of fund manager became known-aggressively buying and selling stocks at a rapid pace and ringing up attention-getting returns in the process. In the aftermath of the 1962 downturn, his Fidelity Capital Fund gained 68%, and in 1965 it gained another 50%, versus only 15% for the market. After being told by Fidelity's founder, Edward Crosby Johnson II, that he was not in line to succeed him, he left to found the high-octane Manhattan Fund.

Unfortunately for Tsai, just at that point, he was struck with a fatal case of chimpanzee syndrome. The years 19661967 were mediocre for Manhattan and in 1968, the patient crashed. In the first half of the year, Manhattan lost 6.6% of its value while the market gained 10%, ranking 299th among the 305 funds tracked by mutual fund expert Arthur Lipper. At that point, Tsai cashed in his chips and abandoned his shareholders, selling Manhattan to C.N.A. Financial Corporation for $30 million.

Why had things gone so horribly wrong at the Manhatttan Fund? The nation's senior financial writers spun a tale of speculation and hubris, followed by the inevitable rough justice. (At least for the shareholders. In addition to his golden parachute, Tsai eventually went on to a distinguished business career, ultimately becoming chairman of Primerica.) But the financial press missed something far more important: the Manhattan Fund was the first example of what later became an all-too-common phenomenon in the world of mutual funds-a.s.set bloat, with its corrosive effect on returns.

In order to understand a.s.set bloat, we'll have to step back and examine the relations.h.i.+p between portfolio size and investment results. Let's say that you think that the stock of XYZ company is a good buy. You call your broker and, without too much fuss, you purchase $1,000 worth. It is unlikely that anyone has noticed your order-millions of dollars worth of company stock are traded every day, and your purchase produces not a ripple in the stock's activity.

But suppose that you have $25 million to invest in the stock. Now you have a very big problem. You will not be able to complete your purchase without dramatically inflating the stock price. Another way of saying this is that at today's price, there is not nearly enough stock available for sale to meet your needs-in order to bring sufficient shares out of the woodwork, the price must be raised. The amount you pay for your shares will be considerably higher than if you had only a small order, and your overall return will be commensurately smaller. The opposite will happen if you decide to sell a large block of stock: you will seriously depress the price, again lowering your return.

This decrease in return experienced by large traders is called "impact cost," and it goes straight to the bottom line of a fund's return. Unfortunately, it is almost impossible to measure. Now it becomes clear what happened to Manhattan's unfortunate shareholders. Tsai was the first person to attain the modern label of "superstar fund manager" and, in short order, suffered its inevitable consequence, a.s.set bloat.

In the first three months of 1968, Tsai's reputation attracted $1.6 billion into the fund-an enormous amount for the time. He was simply unable to invest that amount of cash without incurring substantial impact costs. In effect, Manhattan's shareholders paid a hefty "Tsai tax" each time he bought or sold, eventually destroying the fund's performance.

This scenario repeated itself innumerable times in the decades following Tsai's departure from the fund scene. One of the best examples of a.s.set bloat's ramifications happened to Robert Sanborn, who, until he "retired" at a fairly young age, ran Oakmark Fund. Mr. Sanborn was an undisputed superstar manager. From its inception in 1991 to year-end 1998, Oakmark's annualized return was 24.91% versus 19.56% for the S&P 500. In 1992, it beat the benchmark by an astonis.h.i.+ng 41.28%.

Mr. Sanborn's performance was extremely unusual in that even the most powerful statistical tests showed that this could not have been due to chance. (Unlike Tsai's record, which could easily be explained by his exposure to growth stocks and random variation.) A different story emerges when we examine the fund's performance and a.s.sets by individual year. The first row tracks the performance of Oakmark Fund relative to the S&P 500 (that is, how much better or worse it did relative to the S&P) and the second row tracks the fund's a.s.sets: [image]

What we see is the typical pattern of fund investors chasing performance, resulting in progressive a.s.set bloat, with more and more investors getting lower and lower returns. It can be clearly seen that Mr. Sanborn had significant difficulties once his fund grew beyond a few billion dollars in size.

There's another depressing pattern that emerges from the above story: relatively few of a successful fund's investors actually get its high early returns. The overwhelming majority hop onto the bandwagon just before it crashes off the side of the road. If we "dollar-weight" the fund's returns, we find that the average investor in the Oakmark Fund underperformed the S&P by 7.55% annually. Jonathan Clements, of The Wall Street Journal, The Wall Street Journal, quips that when an investor says, "I own last year's best-performing fund," what he usually forgets to add is, "Unfortunately, I bought it this year." quips that when an investor says, "I own last year's best-performing fund," what he usually forgets to add is, "Unfortunately, I bought it this year."

And finally, one sad, almost comic, note. As we've already mentioned, most of the above studies show evidence of performance consistency in one corner of the professional heap-the bottom. Money managers who are in the bottom 20% of their peer group tend to stay there far more often than can be explained by chance. This phenomenon is largely explained by impact costs and high expenses. Those mangers that charge the highest management fees and trade the most frenetically, like Mr. Tsai and his gunslinger colleagues, incur the highest costs, year-in and year-out. Unfortunately, it's the shareholders who suffer most.

How the Really Big Money Invests There is one pool of money that is even bigger and better-run than mutual funds: the nation's pension accounts. In fact, the nation's biggest investment pools are the retirement funds of the large corporations and governmental bodies, such as the California Public Employees Retirement System (CALPERS), which manages an astounding $170 billion. These plans receive a level of professional management that even the nation's wealthiest private investors can only dream of.

If you are a truly skilled and capable manager, this is the playground you want to wind up in. For example, a top-tier pension manager is typically paid 0.10% of a.s.sets under management-in other words, $10 million per year on a $10 billion pool-more than most "superstar" mutual fund managers. Surely, if there is such a thing as skill in stock picking, it will be found here. Let's see how these large retirement plans actually do.

I'm indebted to Piscataqua Research for providing me with the data in Figure 3-4 Figure 3-4, which shows the performance of the nation's largest pension plans from 1987 to 1999. The average a.s.set allocation for almost all of these plans over the whole period was similar-about 60% stocks and 40% bonds. So the best benchmark is a mix of 60% S&P 500 and 40% Lehman Bond Index. As you can see, more than 90% of these plans underperformed the 60/40 indexed mix. Discouraged by this failure of active management, these plans are slowly abandoning active portfolio management. Currently, about half of all pension stock holdings are pa.s.sively managed, or "indexed," including over 80% of the CALPERS stock portfolio.