entieth century. Yes, big losses occurredat times, such as the back-to-back losses of −28 percent and −44 percent in1930 and 1931, or the 10 years from 1970 to 1979 when stocks hardly budgedwhile the dollar lost 28 percent of its purchasing power.But overall, adjusted for inflation, the return on U.S. stocks amounted toabout 6 percent a year—better than any other class of securities. Moreover, theU.S. returns were comparable to those achieved in most other industrializednations. Sweden’s and Austria’s were even greater. These returns are shownin Figure 9.1.
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Annualized Percentage Return
8
7.06.2
6
5.54.3
43.32.3
3.5
4.4
4.7
7.5
5.6
4.7
3.62.6
2.4
2
5.5
7.4
6.5
2.81.9
1.5
1.3
1.1
1.2
1.3
2.31.6
1.5
1.1
0–0.4–1.0
–2
–1.5–2.1
–2.2
ItaBelGerSpaFraJapDenSwiIreNethWldUKCanUSSAfSweAus
–4
EquitiesBonds
Figure 9.1 Nominal and Real Returns, 1900–2001. Source: Elroy Dimsonet al., Triumph of the Optimists: 101 Years of Global Investment Returns,Princeton University Press, 2002. Used with permission.
The New ForecastersThe implications for market forecasting in the twenty-first century are immense. In ancient times, people traveled to Delphi to consult the Oracle onimportant questions. There, among mountains of awesome height, they reverently listened to mystic pronouncements on such weighty matters as thebest sites for colonies and the advisability of war. These pronouncements,muttered by a consecrated village woman of Delphi from a hidden roomwithin the temple, may have benefited from the intelligence gathered by apriest-operated spy network that extended throughout the known world. Evenmore important, many of the Oracle’s forecasts were ambiguous enough forDelphi’s priests to claim accuracy no matter what the outcome. But we willmake a bold prediction here: Future seekers of knowledge will make their wayto the 14-nation database of Dimson’s group at the London Business School.Indeed, imposing Greek columns give the school a certain resemblance to itsancient counterpart (see Figures 9.2 and 9.3).The London Oracle received one such important question through uswhen Frederick C. Scharack, a reader, asked: “But which particular company orcompanies would you have chosen back in 1900 to achieve your 1,500,000 percent return? Is there an actual company that survived over this period and had
208 Practical Speculation
Figure 9.2
London Business School
this kind of performance, or are the returns based on indexes where new winning firms regularly replace the losers until they, too, fall by the wayside?Wouldn’t this kind of substitution bias all security indexes upward?” Here isDimson’s response:If we choose a company that did survive over a specific interval, it will inevitablyhave different machines and different employees. The business has changed, butthat does not in itself matter to a stockholder. Similarly, a mutual fund that survivescontains a changing cast of constituent securities. All one can do is “follow themoney.” That is the investment strategy underpinning our indexes. The indexesrepresent the cumulative performance of a portfolio, for a strategy to perform wellover a long term. There is no need for any constituent company to survive.
Do Not Be Satisfied with 1,500,000 Percent ProfitWe have begun to make humble attempts to stand on the shoulders of Dimson and his colleagues in our own speculations. To start, we wonderedwhether one needs to be in the market all the time, or whether adroit timing,so useful in other areas, might improve returns. We devised three variationsthat may increase the effectiveness of a simple buy-and-hold long-term investment strategy. We invited a colleague, trader Alix Martin, to join in the improvisation, and we also report his variation.
Chapter 9 • The Future of Returns
Figure 9.3
209
Temple of Apollo at Delphi
Variation 1: A Stumble, a Skip, and a JumpIf Cole Porter had put the “Triumph” theme to the music of “Night and Day,”it might have gone like this:Like the steady support of a lifelong friendLike the flow of Victoria FallsLike the steady state of electric flow,Like the steady rise of the DowLike the ching, ching, ching of the cash flowAs the ships come into dockSo a voice within me keeps repeating, stocks, stocks, stocks.
210 Practical Speculation
Price Appreciation of $1 Investedat Start of 1899
100,000
10,000
1,000
100
10
118991915193119471963197919951907192319391955197119871999Start of the YearBillsEquity Total ReturnsInflationBonds
Figure 9.4 Nominal returns on U.S. Asset Classes. Source: Data from1899–2000 provided by Elroy Dimson et al., Triumph of the Optimists:101 Years of Global Investment Returns, Princeton University Press, 2002.Updated by Niederhoffer Investments.Some readers might object that, far from being steady, the stock markethas ups and downs. Yet on a graph showing what a dollar invested at the start of1899 would have come to by 2001, the declines look like little blips—even themomentous decline from 1929 to 1933. The crashes of 1987 and 2000–2002are barely visible (see Figure 9.4).Even so, the 1,500,000 percent return may be magnificently improved bybuying in the second year after any down year (see Table 9.1). From 1899through 2001, negative returns occurred in 26 years. The return two years
Table 9.1 Improvement of Returns2 Years + 12 YearsBack
1 YearBack
AnnualReturn
−−++
−+−+
1616139
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Table 9.2 Correlation of ReturnsCorrelations between current year and1 year back−2%2 years back−253 years back−44 years back−25 years back−176 years back−5
later averaged 16 percent, with 23 years up and just two years down. The standard deviation was a modest 19 percent.Table 9.2 shows the correlation of returns between past and future yearsfor all relevant periods. The pattern of mean reversion is amazingly consistent.The correlation between returns in one year and the return two years laterturns out to be negative 0.25. That is significant for 100 years of data, with aprobability of less than 1 in 100 of occurring by chance (see Table 9.3).As Porter might have put it:Up and down, that’s how to trade.You buy after a down year, sell after a gain.Just make sure you skip a yearWhether up or down when trading, dearWe’ve tested this every way.
Variation 2: Lucky 5Seasonality is always a suspect in stock returns. The authors of Triumph explore whether there are good months to buy and sell. They review whether January is a good month to buy and conclude that it might show a high return forU.S. small caps. They believe the market may tend to rise in the summer—theopposite of the conventional wisdom on the “summer slump.” Such issues,the authors suggest, will “continue to intrigue.”They certainly intrigued us enough to inspire a study of whether certainyears show higher-than-average returns. We explored whether years ending ina particular digit, such as 5, might be good times to buy, and whether yearsending in other numbers, such as 0 or 7, are not so favorable.As Table 9.4 shows, the average return for years ending in 5 is 32 percent.The average return for years ending in 0 or 7 is close to 1 percent.To test whether these intriguing results were nonrandom, we put all 100returns into an urn. Then we chose 10 groups of 10 returns. We repeated theprocess 1,000 times.
212 Practical SpeculationTable 9.3
Buy Stocks Second Year after a Fall
Year
TotalReturn(%)
TwoYearsLater
TotalReturn(%)
190319071910191319141917192019291930193119321937194019411946195719621966196919731974197719811990199420002001
−0.15−0.29−0.09−0.08−0.06−0.19−0.18−0.15−0.28−0.44−0.1−0.35−0.07−0.1−0.06−0.1−0.1−0.09−0.11−0.19−0.28−0.03−0.04−0.060−0.11−0.11
1905190919121915191619191922193119321933193419391942194319481959196419681971197519761979198319921996
0.220.20.070.390.060.210.31−0.44−0.10.580.040.030.160.280.020.130.160.140.180.380.270.260.230.090.21
Number of observationsAverage returnMedium returnSignificant deviationPercent up
250.160.180.1992%
Next, we computed the difference between the largest and the lowest returns. This turned out to be above 30 percent just 2 percent of the time.Thus, we conclude that years ending in 5 are great times to buy, and yearsending in 0 or 7 are bad times to buy.Studies of the best years to buy bonds, bills, and the Consumer PriceIndex showed completely random results.
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Table 9.4 Average ReturnYearEnding
PercentReturn
0123456789
16101012321102513
Variation No. 3: The Limits of LeverageAlix Martin, a Paris-based student of statistics and consultant to many European telecom companies, offered the following variation on the 1,500,000percent theme:Wall Street pundits typically recommend an asset allocation split between stocks,bonds, and cash. But over the past century, an investor who had 70 percent instocks, 20 percent in bonds, and the remaining 10 percent in T-bills would haveturned $1 into “only” $5,070, one-third of what one would have made by beingfully invested in stocks.Is it possible to improve on the “100 percent in stocks” strategy? It may nothave been in 1899, but it is today. One can buy stocks on margin, or buy futures,to increase exposure to stock returns beyond 100 percent. If an investor had had a200 percent exposure to stocks during the twentieth century, instead of turning$1 into $15,000, he would have made $1,723,781.
Is too much of a good thing possible? Yes: With a 300 percent exposure,our fictional investor would have lost everything in 1931. Even a winningblackjack player can go bust if his bet is too large relative to his bankroll. Thesame phenomenon is at work here: gambler’s ruin.Moreover, investors or funds trying to implement this strategy would faceadditional costs: They would have to pay margin rates to be allowed to holdmore stocks than they have the cash for, and would need to buy or sell stocksat the end of each period to maintain exposure at the desired level.To make the study more realistic, Alix subtracted T-bill returns fromstock returns for the part of the exposure that goes beyond 100 percent, as an
214 Practical Speculationapproximation of margin rates. Even with this more restrictive hypothesis, additional exposure—that is, leverage—improves the fully invested strategy. A150 percent exposure would have more than tripled the gains over the century,turning $1 into $47,228.With hindsight, Alex wrote, the best asset allocation would have been 164percent stocks. This turns a dollar into $50,950, nudging up the compoundedreturn from 10 percent to 11.3 percent. But that would have been a wild ride:from 1928 to 1932, one would have lost more than 90 percent. Anyone daringenough to muster more than 225 percent exposure would have gone bust. Ashe concluded, “Nobody said this was not risky.”
Will the Optimists Keep on Triumphing?While it is impossible for any rational person to dispute the returns that Dimson and his colleagues have so thoroughly documented, there is considerablecontroversy as to what future returns might be. From their Greek-columnedLondon fortress, the professors have kindly given us their view on this question. In a nutshell, they believe that the twentieth century benefited from anextraordinary coalescence of factors, and that returns in the next 50 years willnot be as good as those of 1900–2001.In particular, Dimson cautions against extrapolating from America’s favorable historical experience. “Should Belgians or Danes, with their muchpoorer historical returns, do the same and project much lower stock marketreturns than the United States? That would be odd. Compare a low Belgianstock market forecast with a high U.S. forecast. The investor who predictshigh American returns must explain to me why she thinks America isundervalued relative to other countries. The investor who predicts low Belgianreturns must explain why she thinks Belgium is overvalued relative to othercountries. The only sensible position is to project returns that appear to represent a reasonable reward for risks that may occur in the future. That is whatwe seek to do in Triumph of the Optimists.”
Second OpinionFor answers to truly hard questions, it was customary in the glory days ofGreece to consult the Oracle of Zeus at Olympia as well as the one at Delphi.Hewing to custom, we sought a second opinion from Richard Sears, our
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favorite U.S. oracle. A retired managing partner of a leading actuarial firm,Richard currently presides over his investments from the Palisades Mountains in New York. He also runs a Web site, www.gtindex.com, devoted totracking technology guru George Gilder’s stock picks. Richard wrote:It seems to me like fatal conceit to presume to explain something as complex asfree markets by reference to a few variables. With respect to the stock market, Idoubt anyone can say with confidence why what happened in the past happened.Or predict the future. Any more than one can predict future weather.
The term “fatal conceit” refers to a book of that title by Austrian economist Friedrich Hayek. In it, Hayek described why the highly dispersed natureof economic information dooms all attempts at central planning.1As we write in mid-2002, surrounded by pessimism, our view is that therequired return for holding stocks is at levels unseen since 1990, or 1980, or1950, when memories of depressions or crashes were still hanging in the air.If ever there were a time that investors would only buy risky investmentswhen the anticipated returns were in the 50 percent-and-over area, this timewould seem to be now. We see no reason that our expectations will be disappointed. Why shouldn’t an improvement in life span or the rules of the gameof business reap in the next 50 years the kind of results that greeted investorsin the past 50?As Dimson and his colleagues note, a remarkable number of positive influences converged in the twentieth century: technology, liquidity, diversification, free trade, and the victory of capitalism over socialism. But consider alsothat returns for U.S. stocks were about the same as those for the United Statesduring a period in which Britain went through two world wars, lost her empire, moved through times when her very survival looked like a long shot, andthen followed all that up with a variety of social policies including tax rates atthe margin of more than 100 percent—all of which presumably should havebeen quite negative for stock performance.Despite our differences on how much optimism is warranted for the market’s next century, we and the Dimson group reach similar conclusions as towhere we are going to end up in the future. “A typical real return for equitiesin most countries over the past century has been 4 percent to 6 percent ayear,” they wrote us. “Gazing into the future, a reasonable prediction to uswould be to take a percentage point or two from that.”Perhaps we would add 1 percent or 2 percent to that. Taking compounding into account, the difference is that we would look for 1.5 million percent inthe next century, and they might expect 1 million percent.
216 Practical SpeculationTo put things in a homely setting, consider two travelers who start fromLondon and head for California. One arrives in San Jose and the other in SanFrancisco. Whichever of us is right, the returns are superb. They are cause forgreat optimism. And they provide a beacon of light that should guide all investors to err on the side of optimism in planning their investments: Theyshould buy stocks at every reasonable opportunity to gain wealth for themselves and their heirs.
10
THE PERIODIC TABLEOF INVESTING
It is the accumulation of objective knowledge thatbrings the future in sight.—Gerard Piel, The Age of Science: What Scientists Learned in theTwentieth Century 1
I
n any field, the pursuit of knowledge starts with the accumulation of disconnected facts and properties. The nextstep is to uncover the one- and two-variable effects that explainthe properties. These efforts reduce the extent of uncertainty.The field then awaits a Copernicus, a Darwin, a Linnaeus, a Mendeleyev, aWatson, to come up with a classification scheme that fits the myriad properties and relations into a coherent whole.Take chemistry circa 1870, before Dmitri Ivanovich Mendeleyev and JuliusLothar Meyer independently came up with the periodic table of elements. JohnDalton had discovered the atomic structure of elements early in the century.Most of the elements had been discovered and analyzed. Methods for processing them were available, and procedures for combining them were known.Groups of elements had been observed to possess similar electrical properties.217
218 Practical SpeculationThe discovery of the periodic table simultaneously unified those disconnected facts and relations, and opened a new frontier. The ordering of the elements by atomic weight permitted the prediction not only of individualproperties but relations with other elements. The elements in each column ofthe table show similar properties. As you proceed along the “periods,” orrows, across the columns, the movements from metals to semimetals to gasesare also predictable. More than a century later, the periodic table is still on thewall of most laboratories around the world, used by practitioners and studentsto make sense of the behavior and properties of the elements and their multifarious molecular configurations.It is beautiful and reassuring for the chemist to know that an element’sproperties can be predicted based on its position in the periodic table. Butwhere is the comparable knowledge vis-à-vis the properties, let alone the predictive qualities, of individual stocks?Granted, stocks exhibit stochastic properties; that is, their movementsmay be analyzed statistically according to a random probability distribution,although not predicted precisely. Even these stochastic properties vary depending on the economy, world events, and the state of markets around the globe. The difficulty of acquiring knowledge iscompounded by the peculiar readiness of markets to follow theprinciple of ever-changing cycles: By the time an investor has identified thepayoffs, as well as the likelihood of the tendency’s continuation, they aremuch diminished.Moreover, in no field has such little advancement of knowledge been attained as in stock investing during the past century. Not only are most of theproperties of stock prices untested; they are often described in a prescientific manner not susceptible to testing, as we have shown. Onthose occasions where properties are stated in a testable fashion,other deficiencies are present. Invariably, neither a measure of variability nor the uncertainty attached to the estimate is given. Often the data areanalyzed in such a way that no investor could have acted in time to take advantage of the supposed relation. The influence of ever-changing cycles iseverywhere neglected.True, investments are a branch of the social sciences, not the physical sciences, and no immutable rules are to be expected. But the continual use of dubious methods and data, the avoidance of testing, the reliance on authority,the cultish reverence paid to celebrity investors, the pronouncementsof selective gurus, and the attempts to mislead with propaganda,are far more widespread than in any other field. Of course, thepropagation of these delusive approaches is merely a necessary and
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natural part of an ecological system in which the public provides the grist for the mill that makes the market wheels turn.But this does not excuse us from trying to rectify the situation by calling, “Statistics on the table!”
Begin with the FactsAs the current state of knowledge about investments—disconnected facts anda few relations—is on a par with what was known in chemistry before the discovery of the periodic table, we start with the disconnected facts we knowabout the market:• Stocks tend to go up at a rate of about 10 percent or 12 percent a yearover most long periods.• Insiders—the officers and directors of a company—tend to buy and sellat propitious times.• The higher a company’s expected growth rate, the higher the currentprice relative to current earnings.• The performance of stocks with higher or negative P/E ratios versusthose with lower P/Es is inconsistent.• Corporate assets available for activity are the result of and are restrictedby various amounts of debt, original ownership equity, and retainedearnings.Certain relations are also known about stocks:• The higher the risk, the higher the return.• Risk can be reduced by diversification. This risk reduction decreases asthe number of stocks in a portfolio increases. As much as 80 percent ofthe maximum risk reduction can be achieved with as few as 15 stocks.• In most periods, small companies tend to perform better than bigcompanies.• Certain kinds of stocks do better at certain times of the year than atother times.• Companies that innovate and spend proportionately large sums on research tend to be rewarded, prospectively and retrospectively, morethan companies that concentrate on relatively fixed and unchangingbusinesses.• Companies that have monopolies fixed by the government often performbetter for extended periods than do others (e.g., large pharmaceutical
220 Practical Speculationcompanies, with franchises essentially protected by the Federal Foodand Drug Administration bureaucracy, have tended to do well).The one characteristic that distinguished the periodic table from all previous attempts at classification was its astounding ability to predict. Mendeleyevleft spaces in his table for as-yet-undiscovered elements and described theirproperties in advance. Scandium, gallium, and germanium were discoveredshortly thereafter, with properties closely matching Mendeleyev’s predictions.In the field of finance, we find a far different situation. Financial predictionsare ridiculed with a contempt usually reserved for weather forecasts:• Isn’t it strange how the same people who laugh at gypsy fortunetellerstake economists seriously?• “Ask five economists and you’ll get five different answers (six if onewent to Harvard).”—John Kenneth Galbraith• “An economist is an expert who will know tomorrow why things he predicted yesterday didn’t happen today.”—Laurence J. Peter2Then there was Harry Truman, who said he wanted a one-armed economist “so the guy could never make a statement and then say, ‘On the otherhand, . . . ’ ”How helpful it would be if there existed a classification scheme for stocksas perfect as the periodic table of elements—one that would place companiesinto groups according to their properties regardless of their industries or balance sheets, one that had been scrutinized and tested over many years by academic and practical users, one not subject to the many ephemeral factors thataffect the moves of stock groups in different bullish and bearish environments, and most important, one that would enable reliable predictions.In addition to providing a rudder and base for further research, such anideal scheme should provide the same sense of order that standards providein such areas as building specifications, electrical wiring, and the diagnosisand treatment of disease.Incredibly, a parallel to the periodic table of elements does exist in thefield of stock selection. It has stood the test of time, made money for thosewho have used it, provided a method of predicting the performance of stocksfor 37 years, and has been thoroughly vetted and reproduced by academic andindustry evaluators. It is the Value Line stock ranking system.
A Classification System for StocksEvery week since the early 1970s, Value Line has been classifying companiesinto groups. The group or rank is Value Line’s expected price performance of
Chapter 10 • The Periodic Table of Investing
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the stock for the coming 6 to 12 months. Stocks ranked “1” are expected to dobest, and stocks ranked “5” are expected to underperform. The classification isbased mainly on the quarterly earnings comparisons of the individual companies compared with a cross-section of all companies, and the relative priceperformance of the companies.The elements in the higher period, or row, of the periodic table of elements tend to be lighter and more common than those in the bottom period.Similarly, Value Line notes: “Stocks ranked ‘1’ in timeliness are often morevolatile than the overall market and tend to have smaller capitalizations.” Thisis a key qualification that is crucial to the study of the validity and reliability ofthe classification scheme.Value Line’s timeliness classification system was invented by Sam Eisenstadt, who started as a proofreader at the firm in 1946, fresh out of the Armyafter World War II. Value Line was then a sleepy company with 15 employeesin offices in the Borden Building at 350 Madison Avenue. The founder,Arnold Bernhard, had become interested in a value standard for stocks as a result of the financial difficulties his family suffered in the 1929 crash.Bernhard felt that emotional extremes drove the market too high in thelate 1920s and too low in the early 1930s. He noticed that there was a relationship between annual earnings and stock prices and plotted them on a logarithmic scale. He would plot the annual earnings of an individual companyon a transparency and superimpose it over the price history, an early effort atvisual regression. This fitting process would produce a multiplier on the earnings, which could then be applied to an earnings forecast to arrive at a “normal value.”This line became known as the Value Line. Stock prices fluctuated aboveand below the line—evidence of over- and undervaluation. “I cannot say exactly where Bernhard got the inspiration for this procedure, but I consider it amajor achievement at that time, when stock selection was considered to be anart, not a science,” Eisenstadt said. “This was a pioneering effort in the attempt to separate stock prices from emotional extremes.”Mendeleyev, in trying to come up with the classification that would orderthe elements into groups with similar properties, put each element on a playing card. On train trips, he played Solitaire with the cards as he tried to sortthem into proper groups. Finally, he came up with the concept of atomicweights. It had already been observed by John A. R. Newlands—and dismissedas absurd by the English Chemical Society—that chemical groups repeatedevery eight elements, similar to the octave in a musical scale. (Today’s periodictable sorts by number of protons, instead of by weight.)As Eisenstadt proofread the records and got to know Value Line’s operations, it gradually occurred to him that companies might be fitted into rows
222 Practical Speculationand columns of performance by comparing their characteristics to each otherin a single time period. He came up with the idea of looking at companies incross-sections, rather than individually. “Almost like a crossword puzzle,” herecalled 55 years later in an interview.The problem was how to order the stocks.At City College, where Eisenstadt received his training as a statistician,the cutting-edge technique of regression was just then becoming practical toimplement. As discussed in Chapter 8, regression attempts to find the bestestimate of the linear effect of a group of explanatory variables on a dependentvariable. The method of least squares is usually used to come up with theseestimates. In simple terms, the equation minimizes the sum of squares of thedeviations between predicted and actual values.Eisenstadt reasoned that he could use least squares regression analysis tofind how all the stock returns in a six-month period were fitted by their mostrecent quarterly earnings and price comparisons as well as by their long-termhistories of prices and earnings.In practice, regression analysis requires large-scale computer power.Such computers were just then starting to become widely available. Eisenstadtpersuaded Value Line to let him rent time on an IBM 7094—a machine thatcomputed with one-hundredth the speed of today’s personal computers andcost about 10,000 times as much.With five or more variables providing the explanation and hundreds ofstocks to consider, it often took more than one week on a computer as big as adouble-haul truck to come up with the results. Whenever the computer wasturned on, the lights in the entire building dimmed to half their normalpower. Nevertheless, the computer allowed Eisenstadt to analyze companiesin relation to each other, and thereby develop the foundation for the ValueLine classification system.
How Valuable Is Value Line?How does the system stack up relative to its predictive accuracy? Does it refute in any way the proverbs about the gross errors in forecasting?Because Value Line publishes each week a timeliness andtechnical ranking for each of the stocks it covers (currently about 1,700), theconstant churning required for a portfolio to use all the ranking changes eachweek would be impractical. Many of the stocks are small and relatively illiquid, and commission costs would eat up most of the gains in a small account.
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A good test of Value Line’s practical value is to take the stocks classified intoeach group, using the information that would have been available to subscribers as of the end of each calendar quarter, to look at the performance ofthese companies for the next quarter without any rebalancing, and then to repeat the process for each subsequent quarter. The results of this test areshown in Figure 10.1.The record of the timeliness rankings is stellar. There is a perfect directrelation between predicted group performance and actual. The average returnof 4.3 percent a quarter for the Group 1 stocks is highly superior to the 1.0 percent average for the Group 5 stocks.Although a difference of a few percentage points a quarter does not looklike much in isolation, the power of compounding makes the differenceshighly significant by the end of the period. One hundred dollars invested inthe Group 1 stocks at the end of the second quarter of 1983 would have grownto $1,319 at the end of the second quarter of