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This PDF is a selection from an out-of-print volume from the National Bureau of Economic Research Volume Title: Expectations and the Structure of Share Prices Volume Author/Editor: John G. Cragg and Burton G. Malkiel Volume Publisher: University of Chicago Press Volume ISBN: 0-226-11668-9 Volume URL: http://www.nber.org/books/crag82-1 Publication Date: 1982 Chapter Title: Nature and Sources of Data Chapter Author: John G. Cragg, Burton G. Malkiel Chapter URL: http://www.nber.org/chapters/c11288 Chapter pages in book: (p. 1 - 52)

Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

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Page 1: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

This PDF is a selection from an out-of-print volume from the NationalBureau of Economic Research

Volume Title: Expectations and the Structure of Share Prices

Volume Author/Editor: John G. Cragg and Burton G. Malkiel

Volume Publisher: University of Chicago Press

Volume ISBN: 0-226-11668-9

Volume URL: http://www.nber.org/books/crag82-1

Publication Date: 1982

Chapter Title: Nature and Sources of Data

Chapter Author: John G. Cragg, Burton G. Malkiel

Chapter URL: http://www.nber.org/chapters/c11288

Chapter pages in book: (p. 1 - 52)

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1 Nature and Sources of Data

This study involves a number of interrelated topics concerned with theformation of expectations and with the pricing of capital assets. Ourobjective is to develop and test realistic models of common stock pricesand returns based on expectations held by participants in the market. Inorder to provide tests of security-price models that are more satisfactorythan those previously published, we have collected a unique body ofexpectations data over the decade of the 1960s.1 These data are also ofinterest in their own right and worthy of detailed study. After a briefoutline of the plan of the book and an indication of the study's majorfindings, this chapter describes these data.

1.1 Outline of the Study

Our first major area of research interest is the expectations datathemselves, which are discussed in the present chapter.

Among the issues we will be considering in chapter 2, the followingsorts of questions are indicative of our focus:

1. What is the extent of consensus among forecasters? Do the datasuggest that models of capital-asset pricing based on homogeneous ex-pectations are likely to provide a valid description of reality?

2. How accurate are the forecasts? A variety of tests will be usedcomparing the accuracy of the forecasts with a number of predictionsderived from historical data.

1. Some partial results using a portion of the data from the first two years of the samplewere published in Cragg and Malkiel (1968) and Malkiel and Cragg (1970). Most of the testsreported in this study are new, however.

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2 Chapter One

3. Are the forecasts consistent with the rational-expectations hypoth-esis?

4. Is there information in the forecasts that is not reflected in marketprices and that might be profitably exploited?

5. To what extent do the forecasts seem to arise from the forecasters'first predicting a few key variables (such as national income) and thenestimating the effect of these variables on each company?

To summarize some of the major findings of chapter 2, we found that acommon-factor model seemed consistent with the data. For most years,at least two factors are indicated, and we interpret this finding as suggest-ing that the forecasts do rest on qertain economic variables such as realgrowth, inflation, etc. Despite the apparent applicability of the common-factor model, however, we did find considerable lack of consensus in theforecasts. Forecast accuracy can be described as poor. While the forecastswere superior to extrapolations from past observations (which were ofessentially no use at all), we found no information in the forecasts thatwas not already impounded in market prices. Finally, our investigation ofthe rationality of the forecasts produced mixed results. While certainnarrow implications of the rational-expectations hypothesis could berejected, we could not reject the broader implications of the hypothesis;i.e., there was no evidence of readily available information that was notcontained in the forecasts and no information in the forecasts that was notcontained in market prices.

The next major focus of the study is on developing a restatement ofcapital-asset pricing theory so that we can use the expectations data wehave collected to test the model. Chapter 3 is devoted to the developmentof that model and to problems of its empirical implementation using ourdata.

Following the seminal contributions of Markowitz (1959) and Tobin(1958) in formulating a model for portfolio selection, a considerable bodyof theory has developed concerning the pricing of capital assets in orga-nized securities markets. Some of the most important early contributionswere made by Sharpe (1964), Lintner (1965), and Mossin (1966). Themain feature of the theory is that the values of all securities are deter-mined simultaneously. In this general-equilibrium framework, using amean-variance approach, a very simple structure of capital-asset prices isderived in which the expected returns of individual securities are a simplelinear function of the security's systematic or nondiversifiable risk (usu-ally called the security's beta).

The original capital-asset pricing model has now been widely ques-tioned on the basis of empirical evidence and a large number of modifiedtheories has been proposed. While the evidence points to a reasonablylinear long-run relationship between risk and return, where risk is taken

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to be a security's nondiversifiable risk, actual and theoretical rela-tionships do not correspond, with the measured relationship being muchflatter than the theoretical relationship. Moreover, the risk-return rela-tionships over different time periods have been erratic and the estimatesof the so-called riskless market rate of return seem unrealistic. Finally,estimated betas are quite sensitive to the index against which they aremeasured and some researchers have doubted whether the tests support-ing the theory are statistically valid. Thus serious questions have beenraised about the actual relationship between risk and return as well asabout the underlying theory generating the relationship.

Since the theory does not appear fully supported by the data, it islegitimate to look closely at the assumptions of the underlying model.The critical assumptions upon which the capital-asset pricing model restsinclude the absence of transaction costs, identical beliefs among investorsabout the distribution of future returns, the ability to borrow or sell shortat going market rates, and the existence of a risk-free security. Not onlyare these assumptions unrealistic, but some of them are in fact contra-dicted by expectations data we have collected from security analysts thatimply considerable differences of opinion regarding future returns. Thus,in order to arrive at a theoretical structure suitable for empirical testing, itis necessary to alter the capital-asset pricing model to account for avariety of market imperfections.

Our approach is to develop a diversification model of security valuationusing the return generation process suggested by Ross (1976, 1977). Weneed not rely on all the assumptions of the traditional capital-asset pricingmodel but rather on the common observation that many portfolios con-taining the securities of major corporations can be considered to bewidely diversified. Within the assumed return generation process, thisobservation yields the same kind of valuation formula as the Ross arbi-trage pricing model, though on somewhat different grounds. Specifically,investors can be assumed to regard the covariances of the various returnsas stemming from their linear dependence on a limited number of ran-dom factors. These "factors" might represent the stock market as awhole, the level of economic activity as represented by national income,interest rates, inflation, and so on. In addition to considering models ofsecurity returns, we examine some valuation models that are explicitlyformulated with respect to security prices.

Chapter 4 presents an empirical analysis of the various models ofsecurity prices and returns. To our knowledge, there has been onlylimited empirical testing of asset pricing models that has employed properexpectations measures. The availability of a continuous set of anticipa-tions data permits the substitution of ex ante for ex post measures of ratesof return. We are aware of one other major study, that by Friend,

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4 Chapter One

Westerfield, and Granito (1978), that has used anticipations data in testsof asset pricing models, but this study was done only for four time periodsand only for the simple capital-asset pricing model (CAPM).

In performing our tests, we use the expectations data we have collectedto generate a series of expected returns during the 1960s for a large crosssection of companies. We then test the simple CAPM as well as a varietyof multifactor models. Not only the expected returns data but also therisk proxies represent expectational measures. A major strength of ourempirical tests is that we are able to generate both ex ante risk and ex antereturn measures directly from our data.

We conclude that the security returns implied by our expectations dataare related to "systematic" risk elements appropriately defined. Particu-larly important are risk measures derived from the expectations data wehave collected. We also find that security prices can be explained farbetter by our expectational measures than with historical data. More-over, a multif actor model of security returns seems more satisfactory thanthe simple CAPM. It seems clear that risk should not be considered aone-dimensional variable as became popular after the initial develop-ment of the CAPM. We find moreover that valuation relationships arenot stable over time and that different systematic risk influences vary inimportance over time. For example, early in the 1960s inflation andinterest-rate risk played little role in security valuations, yet later in thedecade they played a far more important role than the traditional riskmeasure based on the simple CAPM. Finally, we find that the expecta-tions data together with the estimated valuation relationships cannot beused to isolate "undervalued" or "overvalued" securities. There is evi-dence that our expectations data are fully impounded in current prices,leaving no opportunity for earning excess returns. In the final analysis,then, our study confirms the existence of efficient markets.

One of the most intriguing of our findings concerns a new risk proxythat appears to be particularly useful in explaining both expected returnsfor securities and actual stock prices. We found that the best single riskmeasure available for each company was the extent to which differentforecasters were not in agreement about that company's future growth. Itis possible to interpret this measure as representing specific risk, in whichcase the finding might be taken to be inconsistent with recent models ofsecurity valuation including our own. On the other hand, our risk vari-able may indirectly measure the sensitivity of different securities tounderlying common factors and thus serve as a most effective proxy for avariety of systematic risks. At the very least, our results suggest that riskundoubtedly has dimensions not fully captured by the covariances withmarket indexes or by other variables that have dominated recent work onvaluation. They also suggest that the variance of analysts' forecasts mayrepresent the most effective risk proxy available.

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1.2 The Participating Security Analysts and the Company Sample

The major task of professional security analysts is to forecast the futureearnings and dividends of the companies they study. These forecasts areof particular interest because in them it is possible to observe divergenceof opinion among different individuals dealing with the same quantities.But expectations regarding earnings (and dividend) growth are not theonly important variables that they must calculate. Current accountingconventions are so far from uniform that estimates of precisely what afirm may have earned in a prior accounting period may also be consideredto be an expectational variable.

The data used in this study were collected from nineteen investmentfirms. The participants were recruited through requests to three organiza-tions. The first was a group of firms which used computers for financialanalysis and met periodically to discuss mutual problems. The second wasthe New York Society of Financial Analysts. The third was the Institutefor Quantitative Research in Finance, an organization of investmentfirms formed to encourage the development of quantitative techniques infinance.2 From these groups, twenty-five firms agreed initially to partici-pate in the study.

Unfortunately, not all volunteers were able to supply data useful to thisstudy, either because the actual supplying of data would have been tooburdensome (the data being kept for internal records in a form that madetheir extraction difficult) or because the data supplied were not compara-ble to other data being used by us (usually because the expectations wereformulated at different dates). Because one of our main objectives was toexamine differences and similarities in predictions of the same quantities,such data were not used in the present study. As a result the expectationsdata from only nineteen of these firms were finally used. Even amongthese nineteen firms there was far from complete overlap either in thecorporations for which the predictions were available or in the particulartype of expectations data that they were able to provide.3 Moreover, onlyone firm supplied both long- and short-term growth rates for the sameyears.4 Typically, the firms published (or made available) for their clientseither long- or short-term growth rates but not both. Thus we can con-sider that, in effect, we have two samples, one of long-term, the other ofshort-term forecasts.

Of the nineteen participating firms, five were large money-centerbanks heavily involved in trust management, five were mutual-fund

2. This same organization provided financial support to the authors during the data-gathering phase.

3. We are deeply grateful to the participating firms, which wish to remain anonymous.4. Two additional firms supplied both long- and short-term growth rates but not in the

same years.

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6 Chapter One

management companies responsible for the portfolio selections of severalmutual funds, five were brokerage houses involved in servicing institu-tional clients as well as the general public, two were investment advisoryfirms, and two were pension-fund managers.

We would not argue that these estimates necessarily give an accuratepicture of general market expectations. It would, however, seem reason-able to suggest that they are representative of opinions of some of thelargest professional investment institutions and that they may not bewholly unrepresentative of more general expectations. Since investorsconsult professional investment institutions in forming their own expecta-tions, individuals' expectations may be strongly influenced—and soreflect—those of their advisers. That several of our participating firmsfind it worthwhile to publish these projections and provide them to theircustomers provides prima facie evidence that a certain segment of themarket places some reliance on such information in forming its ownexpectations. Also, insofar as other security analysts and investors followthe same sorts of procedures as those used by our sample analysts informing expectations, general investors' expectations would resemblethose of the analysts. Consequently, these predictions may well serve asacceptable proxies for general expectations and surely seem worthy ofdetailed analysis.

It should be noted that security analysts are not limited to publisheddata in forming their expectations. They frequently visit the companiesthey study and discuss the corporations' prospects with their executives.These discussions cover such matters as the accounting conventions of thefirms, their current and planned capital expenditures, their marketingprograms, their projections, etc. As a result these analysts are usuallyable to form opinions about the quality of corporate management andthese opinions often strongly influence their forecasts.

The basic company sample consisted of the 175 companies listed in theAppendix. Data were collected from 1961 through 1969, though the datawere very sparse in the last years, especially 1969. As noted above, datawere not always available for each company for each of the years cov-ered. As we shall see below, this hindered us in doing some of theempirical tests we would have liked to have done.

The sample of 175 companies was not selected at random but rather onthe basis of data availability. The companies covered by the data we havecollected represent only a small fraction of those whose shares are tradedon organized securities markets. Furthermore, it was not the case that allforecasters supplied data for the same set of companies; instead, therewas considerable variation in which companies any particular forecastercovered. This varied coverage reflected the practices of the financial firmsinvolved. Our procedure was to obtain the forecasts that the firms hadalready made rather than to solicit forecasts for a specific list of com-

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panies. We then selected our sample to cover only those companies forwhich there was overlap in the predictions made. For a company to beincluded in the sample at least three securities firms had to furnishexpectations estimates in each of two years. We lost a few companiesfrom our original sample through subsequent merger, which made itimpossible to track the accuracy of the predictions made.

These aspects of the data gethering raise questions about the possibilityof sample-selection biases arising from our use of an availability sample.There is no doubt a bias toward large companies. Most firms did tend tomake forecasts for the large-capitalization companies in which invest-ment interest is centered. This is especially so since the clients of theadvisers and brokers in the sample were typically institutional investors,which tend to specialize in larger firms. Our sample does thereforerepresent most of the trading volume on organized exchanges and most ofthe total capitalization of listed shares even though it contains only asmall fraction of the total listed companies.

Whether there are other biases is less clear, or what their nature mightbe. It is not the case that the predictions were formed to support "buy"recommendations or that they represent only those predictions whichgive rise to such recommendations. We understand that all companies forwhich detailed forecasts were made were included in our data. But justwhat criteria were used for selecting the companies to be investigated by aparticular firm is not entirely obvious. Primarily, we suspect that itrepresents past interest especially as expressed in prior inclusion ininstitutional and individual portfolios, and it is not apparent how thiswould bias the sample except for the size bias already noted.

One might worry that our forecasts do not really represent the expecta-tions on which the values of securities actually depend. Instead, they mayonly reflect a paper trail created to give the illusion of responsible actionwhich in fact has quite other bases. This possibility cannot be ruled out apriori, but two points should be made. First, much of the empirical workis designed to investigate whether our data do represent the expectationson which valuation depends. Second, it would be strange if firms ex-pended considerable resources to lay a paper trail without also trying toobtain the most useful and relevant information to be had for the cost.

It is possibly worth noting that the pattern of data availability should beconsidered a substantive finding of our studies. Even among professionalsecurity managers, equally precise and well-formed expectations are notmade for every company. Different investment firms often had clearlyformed opinions about different companies. This is an aspect of expecta-tions in securities markets that has as yet received virtually no theoreticalattention.

As noted above, the sample of the short-term forecasters was essen-tially a different sample from the long-term one, with only one overlap-

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8 Chapter One

ping predictor. We were, however, able to use the same 175 companiesincluded in the long-term sample. Thus we again find the same large-company bias in the short-term sample. But we did have some additionalshort-term forecasts available for a maximum of 85 companies. Theseforecasts were used in our study of the accuracy of the short-term predic-tions (where we used a 260-company sample) but not in the later valua-tion work.

1.3 The Data Collected

1.3.1 Normalized Earnings

It is well known that the market does not necessarily capitalize thereported earnings for a firm during the preceding year. Instead, it is likelythat investors employ some concept of normal earnings for each firm.Consider, for example, the hypothetical case of a firm that has beenearning $5 per share for a number of years. Suppose that during one year,as a result of damage caused by a severe hurricane, earnings decline to $3per share, the $2 difference being a nonrecurring loss. Will the marketcapitalize the $3 per share earnings? It is more likely that investors willrecognize that this is a temporary dip in earnings. In evaluating the stock,they will tend to apply an appropriate price-earnings multiple to theamount they consider represents the normal earning power of the com-pany and not to the actual earnings figure. This belief about the appropri-ate figure receives support from the fact that one of the first jobs of asecurity analyst is to adjust the firm's accounting earnings to arrive at anindication of true earning power (see Graham et al. 1962, chapter 34).

The problem of evaluating earnings is particularly acute for cyclicalcompanies. The market does not apply a constant multiplier to cyclicallyvarying earnings. Earnings multiples tend to fall as earnings rise, and riseas earnings fall, because of the cyclical path of the earnings. Thus theprice-earnings ratios that are relevant for valuation may be the ratios ofprices to normalized rather than reported earnings. These normalizedearnings are estimated to be the earnings that would occur at a normallevel of economic activity if the company were experiencing normaloperations—that is, operations not affected by such nonrecurring itemsas strikes, natural disasters, and so forth.

There is an additional problem in using published accounting earningsfigures as the basis of a valuation study. Reported earnings depend on anumber of variable accounting procedures and management decisions insuch areas as depreciation and inventory policy. Consequently, the use ofreported earnings figures would not be likely to put companies on acomparable basis. Thus one of the most important reasons for usingnormalized earnings figures is to ensure that the same accounting conven-

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tions are applied to all companies. Particular care was taken to ensurethat those which furnished normalized earnings adopted uniform conven-tions with respect to consolidation of subsidiaries and accounting fordepreciation and investment tax credits. For example, the conventionapplied to the normalized utility earnings figures used in the current studyis that all earnings were adjusted (by the analysts) to a "flow through"basis. Thus, for example, all tax savings resulting from the investment taxcredit were allowed to "flow through" directly to corporate earnings.Similar conventions had to be adopted with respect to such factors as theearnings of nonconsolidated subsidiaries—particularly foreign ones—thetreatment of some nonrecurring items, and so forth. We then took theaverage of the normalized earnings figure (NE) to be the relevant earn-ings variable for valuation.

1.3.2 Expected Growth Rates

Two types of expected growth rates were furnished, short-term (for thefollowing year) and long-term. The long-term growth rates were esti-mated by nine securities firms.5 Each long-term growth-rate figure wasreported as an average annual rate of growth expected to occur in thenext five years. At first thought, such a rate of growth depends on whatearnings are expected to be in five years' time and on the base-yearearnings figures. However, this dependence need not be very great if thegrowth rate is regarded more as a parameter of the process determiningearnings than as an arithmetic quantity linking the current level of earn-ings to the expected future level. Discussion with the suppliers of the dataindicated that all firms were attempting to predict the same future figure,the long-run average ("normalized") earnings level, abstracting fromcyclical or special circumstances. The bases used were less clear. Somefirms explicitly used their estimates of "normalized" earnings during theyear in which the prediction was made. Others provided different figuresas bases: in one case the firm estimated actual earnings; in another aprediction of earnings for the future two and trailing two quarters wasused as a base. These differences in bases did not seem to be reflected inthe growth rates, however, since attempts to adjust the rates for differ-ences in base figures introduced rather than removed disparities amongthe predictions. In dealing with long-term growth, therefore, we use thegrowth rates as supplied by each participant and not some adjustedfigures.

These growth rates were used individually in the study of forecastaccuracy reported in chapter 2. They were averaged across predictorseach year for use in the valuation studies reported in chapter 4. The

5. Not all nine firms provided growth-rate estimates for each of the companies in thesample during each of the years covered.

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10 Chapter One

figures reported in the appendix of this chapter are averages of theavailable forecasts supplied by those of the nine predictors which didsupply data for a particular company in a particular year. When we needto refer to individual long-term predictors, we use the numerals 1-9.

In addition to these expectations of long-term growth rates, we alsocollected estimates of the following year's earnings from eleven securitiesfirms.6 These earnings projections were converted into growth rates bydividing the estimates by present-year average "normalized" earningsestimates and subtracting unity.7 As we discuss at more length in chapter2, we found, somewhat to our surprise, that the implicit forecasts ofshort-term (one-year) growth were not highly correlated with the long-term anticipations and we were able to use both sets of data in some of theempirical valuation work presented in chapter 4. As in the case of thelong-term expectations, the individual predictions were used in the studyof forecast accuracy presented in chapter 3. Averages were used in thevaluation work and are reported in the appendix to this chapter. We referto predictors of short-term earnings growth by the letters A-K to distin-guish readily these forecasts from the long-term ones.

1.3.3 Estimates of Past Growth Rates

Two of the participating firms provided estimates of past growth ratesas well as future predictions. The figures represented perceived growthover the past eight to ten years, the past four to five years, the past sixyears, and the last year. It may seem unnecessary to rely on securityanalysts for estimates of historic growth rates. However, the past growthof a company's earnings is not, in any meaningful sense, a well-definedconcept. Earnings—being basically a small difference between two largequantities—can exhibit large year-to-year fluctuations. They also can benegative, which creates problems for most mechanical calculations. In-deed, no mechanical method for calculating past growth rates can be fullysatisfactory.

To illustrate the difficulty which underlies such an approach, supposewe simply take as the expected growth rate the (compounded) per shareearnings growth rate over the past five years. The base year may repre-sent a cyclical trough or may have been a particularly poor year for otherreasons. The resulting large growth rate could be completely mislead-ing—cyclical companies could appear to be "rapid-growth" stocks atcertain times. While this difficulty can be lessened by calculating thegrowth rate from a least-squares trend line fitted to the earnings or byincreasing the number of years included in the calculations, these tech-

6. Three of these eleven firms also supplied long-term forecasts. However, in only onecase did we have the same firm supplying both long- and short-term predictions in the sameyears.

7. The result of this calculation is the short-term growth forecast.

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11 Nature and Sources of Data

niques cannot eliminate the problem. Moreover, several technical diffi-culties could be enumerated which make the use of calculations of growthrates from historical data an inherently treacherous affair.

In addition, the accounting definition of earnings is not in exact con-formity with the economically relevant concept of profits or return oninvestors' capital. For these reasons, calculated growth rates are sensitiveto the particular method employed and the period chosen for the calcula-tion. Consequently, such calculations may be a poor reflection of whatgrowth is generally considered to have been, and may not be useful inassessing the past performance of corporations. Furthermore, it may besupposed that in assessing security analysts' predictions of growth, theirown estimates of past growth are more likely to be relevant than objec-tively calculated rates. The extent of agreement among the two types ofmeasures is among the subjects considered in the next chapter. The pastgrowth rates we collected were used in our analysis, but we do not presentthe individual figures here since they are less important than the futuregrowth forecasts.

1.3.4 Extent of Consensus among the Forecasters

While we are unable to publish the individual data, researchers maywell find that the extent of consensus among our forecasters represents apromising expectational measure in valuation studies. As we shall showbelow, this variable was extremely useful in our own empirical work.Consequently, in the appendix we list the variance of the (long-term)forecasted growth rates. In calculating the variances of the predictedlong-term growth rates, we divided by N — 1 observations (using theusual formula giving an unbiased estimate for independent quantities).As a consequence, in the last years of our survey when we very often hadonly two forecasters, there is a tendency to observe some very largenumbers for the variances of the growth rates since the sampling error ofthe variance estimates can be expected to be large. While there wouldindeed seem to be a greater dispersion in the growth estimates later in the1960s compared with the earlier part of the decade, a substantial part ofthe increase in the dispersion of the estimates of the variances of thepredictors is the result of the smaller number of the predictions. Thedifficulties associated with having different numbers of predictions forseparate companies and the small numbers of predictors made it seemunprofitable to use statistics such as the range or interquartile range tomeasure dispersion. No variances were reported for 1969 since in a verylarge number of instances we had only one predictor per company.Whenever only one predictor (or none) furnished a growth estimate, thevariance was not calculated and a line of asterisks is given in the appen-dix. A zero variance represents perfect agreement among those which didsupply a forecast.

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12 Chapter One

1.3.5 Industrial Classification

All our participating firms also supplied an industrial classification.While other classifications are available, the concept of industry is notreally precise enough to get a fixed, unquestionable assignment of cor-porations to industries. Particular problems are presented by conglomer-ate companies. Perceived industry may be more relevant than any othergrouping in an investigation of anticipations. The classification we userepresents a consensus about industry among our participants. Wheredisagreements occurred (as was often the case with conglomerates), thecorporation was simply classified as "miscellaneous." The classificationrepresented considerable aggregation by us over finer classifications, andonly eight industries were distinguished. These were

1. electricals and electronics,2. electric utilities,3. metals,4. oils,5. drugs and specialty chemicals,6. foods and stores,7. "cyclical"—including companies such as automobile and steel

manufacturers, and meat packers,8. "miscellaneous."

The first column of the appendix tables gives the company's industrialclassification.

1.4 Concluding Comments

This study utilizes a body of expectations data in order to shed light onthe nature of expectations formation in the securities markets and to testtheoretical propositions concerning the nature of capital-asset pricing.This chapter has described the expectations data that will be utilized andhas indicated the method by which these data have been collected.

In view of the unique8 nature of these data, the considerable effortinvolved in their collection, and the relevance of such data in manyaspects of securities research, we have endeavored to gain permissionfrom our survey participants to publish these data for use by otherresearchers. Unfortunately, we do not have permission to release the.individual predictions. As we shall indicate in the next chapter, theover-all quality of these estimates as useful forecasters is generally ratherpoor and individual firms feared that their identity might be ascertained if

8. We know of no comparable data available during the 1960s. Some short-term fore-casts were published and analyzed during the 1970s, however. In 1980, one firm beganpublishing long-term growth forecasts of a number of securities firms. The publication,called the Institutional Brokerage Evaluation Service, if continued, should begin to provide awide variety of both short- and long-term forecasts.

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the individual forecasts were made public. We do, however, have permis-sion to publish the average predictions of our survey participants as wellas the standard deviation of the forecasts, and these data are presented inthe appendix below.

AppendixThis appendix contains data on the expectational variables used in thestudies of valuation and forecast accuracy. Five variables are presented.The first is the ratio of price to normalized earnings {PINE) (table 1. A.I).The ratio for each firm was calculated by dividing end-of-year marketprice from the Standard & Poor's compustat tape by the average of thenormalized-earnings estimates of two securities firms. The second vari-able is the average predicted future long-term growth rate (gp) (table1.A.2). This variable represents the anticipated long-term (five-year)growth rate of earnings per share. The figures presented in the table areaverages of up to nine predictors. Not all of the nine predictors, however,made forecasts for each company in each of the surveyed years.

The third variable, presented in table 1.A.3, is the analysts' predictionsof short-term growth. The numbers in the table represent the ratios of theanticipated earnings per share for the next year divided by averagenormalized earnings less unity, [{Et+1l77E)-l]. Thus the predictionsare, in effect, the expected short-term growth rate. Estimates are basedon the forecasts of eleven predictors, although—as in the case of thelong-term growth rates—not all eleven predictors made forecasts for eachof the companies in each of the years covered. None was available in1969.

The fourth variable represented the dividend-payout ratio {DINE)(table 1.A.4). The ratio was calculated by dividing the indicated dividendrate per share as of the end of the year (as estimated by the predictorwhich furnished data in all years) by the average normalized earningsestimate {aj,). The final variable shown is the variance of the long-termgrowth forecasts (table 1. A. 5). In the calculation, division was made by N- 1, with N being the number of predictors. These figures are notcalculated for 1969.

In the first column of each table, the sample companies are categorizedby industry group. The classifications used represented a consensus aboutindustrial affiliation among the survey participants. Where disagree-ments occurred among our respondents about the appropriate industrialclassification, the corporation was classified as miscellaneous.

The sample of 175 companies was selected on the basis of data availa-bility. Nine years of data are included, covering the years 1961 through1969. Where data were not available for a particular company in a specificyear, the cell has been filled with several asterisks.

Page 15: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1 .A.I Ratio of Price to Normalized Earnings

IndustryCode

718283345258838833748218376251867224262246812282

A.C.F. Industries, Inc.Addressograph-Multigraph (AM Corp.)Air Reduction Co. (B.O.C. Fin. Corp.)Allegheny Power System Inc.Allied Chemical Corp.Alcan Aluminum Ltd.Aluminum Company of AmericaAmerada Pet. (Amerada Hess)American Cyanamid Co.American Electric Power Co.American Home Products Corp.Amer. Mach. & Foundry Co. (AMF Ind.)Amer. Nat. Gas Co. (Amer. Nat. Res.)Amer. Smelt. & Refin. (UV Ind.)American Telephone & Telegraph Co.American Tobacco (Amer. Brands, Inc.)Anaconda Co.Armco Steel Corp. (ARMCO Inc.)Armour & Co. (Esmark)Atlantic Richfield Co.Atlas Chem. Ind. Inc. (Imperial Ch.)Baltimore Gas & Electric Co.Beckman Instruments, Inc.Beneficial Finance Co.Bethlehem Steel Corp.Boeing Co.Borden Inc.Boston Edison Co.Bristol-Myers Co.Burroughs Corp.C.I.T. Financial Corp. (RCA Corp.)Campbell Soup Co.Caterpillar Tractor Co.Central & Southwest Corp.Cincinnati Gas & Electric Co.Cities Service Co.Cleveland Electric Illuminating Co.Colgate Palmolive Co.Consolidated Edison Co.Consumers Power Co.Continental Oil Co. (CONOCO)Corn Products Co. (CPC Intl. Inc.)Crown ZellerbackCutler-Hammer Inc. (Eaton Corp.)Dayton Power & Light Co.Detroit Edison Co.Dow ChemicalDuquesne Light Co.

(PINE)

1961

45.617017.7740

22.250023.125028.681022.178018.967026.731036.744026.016020.5000

24.4170

12.9590******10.900018.3650

46.615020.196014.6980

24.605019.224037.3470

19.792029.130017.791029.266019.574013.185022.149020.377020.030022.020020.182031.486018.849019.0620

28.676019.6090

1962

16.323022.955014.762019.118017.700014.636021.214020.200019.363025.000022.880013.667019.138012.667020.304011.40808.9011

11.657015.174010.184012.766020.391032.008019.20609.54179.0000

18.629020.139029.016016.544017.677022.114016.989025.462018.821012.364018.963014.625020.060020.422016.679024.518018.200014.172020.849021.810021.814019.0150

1963

22.963025.815015.414018.843021.683020.000026.442021.758021.384027.280025.000013.929018.333012.776023.305011.17609.7396

14.639015.733011.649018.462021.154024.385019.870011.182010.250019.961021.538030.064014.538015.495027.619020.870026.429018.182011.422018.873017.368018.771020.862017.794026.889020.467014.805019.492021.048025.794018.6230

Page 16: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968 1969

19.3900 16.8750 10.9000 11.3000 17.0000 10.700019.1750 22.2170 15.2000 31.6000 23.3000 16.900015.5040 17.8440 13.2000 12.5000 17.3000 *******20.1790 17.8230 16.5000 12.2000 ******* *******18.4370 16.5130 11.8000 13.3000 20.0000 11.400021.3890 18.6570 6.5000 5.2000 6.0000 11.300021.7700 25.5420 37.1000 35.2000 38.5000 14.800021.3140 16.3060 15.4000 16.2000 21.8000 10.900021.5620 21.6250 14.8000 14.7000 16.8000 13.300026.8940 24.3060 17.5000 16.4000 17.6000 12.500025.2400 27.7460 21.8000 26.4000 23.7000 27.200014.0380 15.7000 11.7000 ******* ******* *******18.8270 18.2570 12.3000 10.9000 ******* *******14.5960 14.8960 11.1000 10.9000 12.7000 *******21.8400 18.0000 15.7000 13.2000 14.6000 11.300012.9900 13.0930 10.0000 ******* ******* *******10.8850 13.6080 11.4000 7.8000 25.3000 8.200011.9440 14.6110 9.8000 9.8000 10.5000 10.500013.1870 ******* ******* ******* ******* *******12.0790 13.3860 11.6000 10.8000 29.3000 18.500017.0000 14.2740 10.7000 ******* ******* *******21.7860 20.4550 17.5000 13.1000 14.8000 10.700054.5280 27.1640 25.6000 32.6000 41.5000 33.600018.6940 16.5650 11.1000 9.4000 12.2000 10.200010.3310 14.2920 10.4000 9.4000 10.2000 9.300011.8750 14.9430 32.4000 18.2000 13.1000 28.000022.8420 19.1760 14.1000 15.9000 19.4000 11.000022.8490 18.8300 16.8000 13.9000 ******* *******30.6670 33.9380 32.4000 37.0000 34.4000 28.800015.7810 26.6000 25.1000 35.6000 44.2000 36.900013.0290 11.8100 10.7000 11.0000 15.1000 10.400026.2710 21.5150 15.9000 17.5000 17.6000 18.500027.5000 21.8680 15.9000 18.7000 22.0000 16.900026.4940 23.1760 20.4000 18.8000 17.9000 14.500021.4040 18.5710 15.0000 13.5000 14.5000 10.400014.4550 12.5370 11.2000 10.4000 20.3000 9.300020.8550 19.5180 16.4000 12.9000 14.9000 10.700019.3630 15.4170 11.4000 17.6000 19.2000 16.100020.2090 16.9000 11.5000 11.9000 13.1000 10.200023.7910 21.2260 17.0000 14.3000 16.2000 10.600017.9410 14.8440 12.5000 12.3000 13.6000 8.300022.0200 20.9310 16.8000 15.8000 17.4000 12.800020.7340 16.0330 12.2000 13.9000 16.1000 13.200018.2020 20.2170 12.6000 18.5000 25.0000 16.800021.4520 18.9130 15.3000 12.9000 15.2000 10.900021.9700 19.6050 15.0000 11.8000 15.3000 10.200025.5000 22.5180 16.3000 19.3000 17.1000 15.500020.0000 17.2080 15.5000 13.6000 ******* *******

Page 17: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table l.A.l (continued)

IndustryCode

876822677166772888664268118227273173817336386851

Eastman Kodak Co.Ex-Cell-O Corp.Federated Dept Stores Inc.Firestone Tire & Rubber Co.Florida Power Corp.Florida Power & Light Co.Food Fair, Inc.Ford Motor Co.General Amer. Transp. Corp. (GATX)General Electric Co.General Foods Corp.General Mills Inc.General Motors Corp.General Portland Cement Co.General Public Utilities Corp.General Telephone & ElectronicsGoodrich (B.F.) Co.Goodyear Tire & Rubber Co.Grand Union Co. (Cavenham Ltd.)Great Atlantic & Pacific Tea Co.Gulf Oil Corp.Gulf States Utilities Co.Heinz (H. J.) Co.Hercules Inc.Hewlett Packard Co.Honeywell Inc.Household Finance Corp.Houston Ltg. & Pow. Co. (Hous. Inds.)Idaho Power Co.Ideal Cement (Ideal Basic Ind. Inc.)Illinois Power Co.Ingersoll-Rand Co.Inland Steel Co.International Business MachinesInternational Harvester Co.Intl. Nickel Co. Canada (INCO)International Paper Co.Intl. Telephone & Telegraph Corp.Johns-Manville Corp.Jones & Laug. Steel Corp. (LTV Corp.)Kaiser Aluminum & Chemical Corp.Kellogg Co.Kennecott Copper Corp.Kimberly-Clark Corp.Kroger Co.Liggett & Myers (Liggett Group)Lilly Eli Co.Litton Industries, Inc.

1961

34.5350

25.000017.427032.500034.885022.643014.597026.172025.726033.816020.530018.537014.562020.859028.293018.914018.936020.682022.243012.576028.036023.458035.042061.667033.677019.608034.111025.3450

24.414019.598015.444064.3330

28.941020.068027.035018.2400

12.846022.355019.194016.769027.903051.9170

1962

26.078012.937018.750014.789029.417028.368012.761011.074020.584021.620025.120017.329015.604010.515020.141019.565010.854013.883011.071015.048011.903022.063016.384024.559037.992019.566016.726029.615022.373014.180022.500015.465011.984036.279012.839018.382014.108018.370014.333011.407020.507021.226010.875015.730015.40309.3486

25.118037.8170

1963

29.634011.732023.138015.842027.385028.627012.769011.875020.552025.254026.630020.064018.500013.731018.824024.804013.618017.606013.491014.857013.723024.308017.087022.500027.518035.298018.520028.833021.583015.917023.286018.743013.828040.158014.634020.333017.133021.881016.250013.408019.589028.983011.096019.607016.286011.523033.819033.3510

Page 18: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968 1969

29.005012.812027.381017.549027.071027.591014.500012.083021.250027.226022.089022.126018.732012.647020.890027.455013.276017.573018.136016.584015.705026.714016.147024.400028.822011.338015.458031.667025.238014.098022.885017.000011.892033.429016.263021.000017.467019.426016.336011.152017.319029.242014.154015.862020.200012.791035.797025.1640

36.115016.000021.680016.376024.474026.375013.258011.097022.235030.256021.154021.161016.560010.446018.608025.556012.473017.431013.553014.946014.146026.585014.113019.368038.682026.847017.070026.049019.667013.000020.460018.644012.570033.603015.041020.511015.375019.178014.108012.511019.533021.218016.242014.314014.694011.225035.638038.2040

29.5000 33.1000 31.5000 28.8000

15.300015.300022.700022.10008.20007.400014.200019.800017.600016.70009.70009.000015.500020.500012.000013.20008.000011.300010.900022.50008.600015.700031.900016.500013.000022.700015.5000

18.3000*******9.7000

29.80009.500016.600010.000016.200010.70007.900014.000016.800014.100010.70008.800012.000027.000027.9000

18.800013.300019.200020.800010.70009.800015.000021.300016.300016.200013.700013.000013.300017.500012.600014.200011.100012.700012.700020.000012.000015.500045.000035.200011.100020.900013.6000

17.8000 16.800013.7000 12.700017.9000 16.700019.7000 16.6000

9.500020.500024.900019.300019.400025.2000

14.400018.100016.800015.000013.500018.900014.300019.200014.600019.200048.200034.900014.000020.500015.8000

14.8000*******9.700045.500010.900019.500013.500021.100013.80008.600014.000017.900010.000013.300016.0000

15.9000*******9.5000

40.100013.800018.600017.100021.200021.800019.000014.600017.400015.200018.000012.5000

9.600012.600020.500010.700016.700013.3000

10.400012.800011.000013.200010.600012.00009.800014.200012.800014.800043.800028.400011.900016.000012.4000

******* ******* ******* *******12.1000*******8.3000

36.500011.600018.700015.400017.900013.6000

14.100015.20008.200016.3000*******

28.1000 31.6000 36.100036.2000 39.1000 16.4000

Page 19: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table l.A.l (continued)

IndustryCode

724885288161688322772527826538418886221338584686

Lockheed Aircraft Corp.Long Island Lighting Co.Marathon OilMcGraw Hill Inc.Mead CorporationMerck & CompanyMiddle South Utilities Inc.Minnesota Mining & Manufacturing Co.Moore Corp.Motorola, Inc.National Biscuit Co. (NABISCO)National Cash Register Co. (NCR)National Dairy Prods. (Kraft Inc.)National Distillers & Chemical Corp.National Lead Co. (NL Industries)National Steel Corp.New York State Electric & Gas Co.Niagara Mohawk Power Corp.No. Amer. Aviation (Rockwell Intl.)North Amer. Car Corp. (Flying Tiger)Northern States Power Co.Norwich Phar. Co. (Morton-Norwich)Oklahoma Gas & Electric Co.Otis Elevator Co. (United Tech.)Owens-Corning Fiberglass Corp.Pacific Gas & Electric Co.Penney (J.C.) Co., Inc.Pfizer (Chas & Co.) Inc.Phelps Dodge Corp.Philip Morris Inc.Phillips Petroleum Co.Pitney-Bowes, Inc.Pittsburg Plate Glass (PPG Ind.)Polaroid Corp.Prentice Hall Inc.Procter & Gamble Co.Public Service of ColoradoPublic Service Electric & Gas Co.Radio Corp. of America (RCA Corp.)Republic Steel Corp.Reynolds Metals Co.Reynolds (R.J.) Tob. Co. (Rey. Ind.)Richardson-Merrell Inc.Rohm/Haas Co.Royal Dutch Petroleum Co.Safeway Stores, Inc.Scott Paper Co.Sears, Roebuck & Co.

1961

24.8890

34.2500

34.563024.333044.016025.6330*******22.179038.168019.658013.036022.9590

19.767019.5110

26.800022.078036.462027.866026.757036.848022.750023.647028.500015.250019.558017.765042.414016.667095.652047.083035.980025.789018.8240

22.985026.583031.157030.1640

20.474036.277032.2070

1962

13.416021.737014.833018.333014.951027.000022.656031.642019.830021.207020.353021.184017.248012.125014.918013.585018.202018.827017.533017.368021.846024.306026.000018.697023.081020.238018.750024.545013.742012.436014.624024.692012.986051.250032.093025.000022.400019.574024.21108.6563

14.615013.175019.174024.864010.610015.593025.588022.1580

1963

9.827622.364018.293021.731017.427033.435022.464035.903019.892025.280024.677022.754017.105013.264016.053015.520017.812019.630010.787017.155021.250019.931026.974015.339026.632018.382021.124023.735014.527012.111014.270027.101013.631048.152027.907026.625022.600019.097031.680011.321019.104013.307014.618025.459011.293017.500027.593027.1870

Page 20: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968 1969

8.644123.707016.842026.964016.500038.173026.133029.145022.374022.604021.869021.413021.358014.521016.236010.907017.921018.59609.4956

20.000022.123021.329028.636013.555022.211019.296028.817022.000015.299011.767015.286020.733015.537031.207028.846025.077022.778019.753025.09309.659118.355011.962017.148025.622011.635020.764023.362030.7740

10.446020.714013.265033.857014.574039.167023.764030.909025.250035.761018.504021.369017.347015.000014.560015.892018.535019.01809.916018.417017.949022.368023.529015.979022.521018.481022.308027.248012.802012.967014.423022.184015.078093.300031.176020.709019.561017.841032.034011.097020.789013.037021.510022.477010.759014.706023.906026.9390

13.200010.000012.600025.20009.800028.900019.200026.000020.800014.300016.600017.400013.100013.300011.00009.500015.000013.10008.700010.000016.500019.700019.300010.900017.400015.700016.400022.100010.000013.100011.100022.900010.8000

23.600019.200016.000015.000015.90004.200015.20009.700017.600014.40007.500011.400015.000017.3000

10.800014.200014.400031.300010.500030.000018.600031.700035.500026.000013.000031.700013.300010.800014.00009.200012.800011.8000

11.7000 8.5000

10.900013.200027.100019.300014.300023.000014.400019.400022.70009.0000

14.800028.400013.000055.800026.900020.900013.100012.700021.2000

20.000030.800015.300032.500017.700035.6000

10.900023.200011.400034.800014.200029.7000

26.7000 22.900015.6000 15.100031.4000 33.200015.8000 13.0000

17.9000 *******10.9000 9.6000

14.2000 9.1000

24.8000 20.6000

17.800028.900014.000022.400024.300017.0000

14.9000

11.200018.800026.40009.1000

17.500028.100015.900063.000030.700020.200014.700013.200019.6000

12.600025.0000

50.000027.000022.000010.60009.600013.9000

15.2000 26.7000

19.3000

10.200012.600016.900023.8000

21.700019.100011.700011.800020.000023.0000

12.0000

22.9000

8.9000*******19.400021.9000

Page 21: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table l.A.l (continued)

IndustryCode 1961 1962 1963

485422144457824812847783521211

Shell Oil Co.Singer Co.Smith Kline & French (Smithkline)Socony (Mobil Oil Corp.)Southern Co.Southwestern Public Service Co.Sperry Rand Corp.Standard Oil Co. of CaliforniaStandard Oil Co. of IndianaStandard Oil of N.J. (Exxon)Sterling Drug Inc.Swift & Co. (Esmark)Talcott Nat. (Assoc. Fst. Cap. Corp.)Tampa Electric Co.Texaco Inc.Texas Gulf Sulphur Co. Inc.Texas Instruments, Inc.Texas Utilities Co.Union Carbide Corp.Union Oil Co. of CaliforniaUnited Aircraft Corp. (United Tech.)U. S. Gypsum Co.U. S. Rubber (Uniroyal, Inc.)U. S. Steel Corp.Upjohn Inc.Virginia Electric & Power Co.Westinghouse Electric Corp.Wisconsin Electric Power Co.Xerox Corp.Zenith Radio Corp.

15.7500

39.1890.10.485026.446027.2000

12.303012.571013.904030.000012.684027.171034.118017.256016.635037.538030.923023.454014.8890*******

20.950013.000016.526033.258029.524017.6140

*******

38.4210

15.350021.083030.714012.500023.466026.923014.730014.302010.977014.875023.968014.685019.634029.397016.611010.088024.660028.151019.214014.028013.926015.31409.81829.9714

19.627026.484014.884019.083043.993026.3860

18.029025.714028.500014.621023.351026.579025.000012.660013.447017.778023.696015.442014.013031.719017.500018.269028.564028.734022.212016.000011.176016.884010.680014.167029.041026.343015.756017.937077.273032.7420

Table 1.A.2 Average Predicted Future Long-Term Growth Rateof Earnings Per Share (gp) (percent)

IndustryCode 1961 1962 1963

7 A.C.F. Industries, Inc.1 Addressograph-Multigraph (AM Corp.)8 Air Reduction Co. (B.O.C. Fin. Corp.)2 Allegheny Power System Inc.8 Allied Chemical Corp.3 Alcan Aluminum Ltd.3 Aluminum Company of America4 Amerada Pet. (Amerada Hess)5 American Cyanamid Co.2 American Electric Power Co.

*******10.00004.0000

3.000010.00007.25004.50004.00005.7500

5.66677.60004.6667

4.33333.00008.00008.20006.00004.75006.0000

6.00007.83334.1667

4.87504.00007.75008.40005.00004.00006.0000

Page 22: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968 1969

19.5080 17.5170 13.0000 11.0000 14.5000 9.500019.2730 13.9230 9.8000 13.8000 17.4000 16.000028.5150 27.3250 17.6000 26.7000 17.9000 16.700016.3110 15.6050 11.8000 10.5000 14.1000 10.200026.2500 23.8390 13.2000 17.5000 16.3000 13.300027.1540 24.6970 18.9000 17.5000 16.7000 14.100013.5370 20.0000 18.8000 26.7000 21.4000 14.800015.6120 15.0000 10.7000 11.1000 11.9000 10.000016.3460 15.9240 12.3000 12.3000 13.4000 10.700019.0740 15.6830 11.3000 11.5000 13.2000 10.700023.7250 28.7720 22.8000 27.9000 27.2000 27.700019.2500 ******* ******* ******* ******* *******11.6430 10.3620 8.8000 13.8000 ******* *******32.3450 28.7990 24.2000 19.3000 24.1000 16.400019.8020 17.1010 13.1000 13.8000 13.2000 10.200018.5910 26.0360 10.6000 ******* ******* *******29.1540 38.2320 28.6000 36.0000 40.8000 36.800028.0460 25.6770 21.9000 20.7000 20.0000 16.900021.5250 20.1470 13.1000 14.0000 17.0000 13.700017.8480 17.2880 11.3000 12.1000 12.8000 10.000011.9630 16.1030 18.8000 15.8000 12.7000 9.800015.6310 13.7820 14.7000 15.7000 14.3000 19.000013.1750 30.3680 13.0000 12.3000 21.1000 10.500010.2000 12.7440 10.0000 9.1000 12.9000 9.300025.6790 29.5100 23.4000 21.7000 24.3000 19.300027.3240 25.3850 22.9000 19.1000 17.6000 11.900020.2380 23.2710 13.4000 20.6000 19.4000 16.100017.7690 17.1230 13.8000 11.9000 ******* *******51.2340 56.1110 33.0000 55.1000 49.5000 41.600021.7670 39.1130 14.5000 21.9000 20.8000 13.2000

1964 1965 1966 1967 1968 1969

5.66677.42862.25004.40004.41674.83336.07147.66675.58336.5000

4.66677.42863.80005.30004.71435.83337.00007.50006.16676.5625

7.00008.33304.00005.00004.00004.33304.33305.50006.33307.1670

7.00008.33305.50005.00004.33305.00004.66705.00006.33307.3330

7.100010.13008.60005.00004.86708.96708.20009.65005.76707.3670

7.00008.0000**************2.00003.00000.000010.00002.00007.0000

Page 23: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.2 (continued)

IndustryCode

5883883374821837625186722426224

168122828768226771

American Home Products Corp.Amer. Mach. & Foundry Co. (AMF Ind.)Amer. Nat. Gas Co. (Amer. Nat. Res.)Amer. Smelt. & Refin. (UV Ind.)American Telephone & Telegraph Co.American Tobacco (Amer. Brands, Inc.)Anaconda Co.Armco Steel Corp. (ARMCO Inc.)Armour & Co. (Esmark)Atlantic Richfield Co.Atlas Chem. Ind. Inc. (Imperial Ch.)Baltimore Gas & Electric Co.Beckman Instruments, Inc.Beneficial Finance Co.Bethlehem Steel Corp.Boeing Co.Borden Inc.Boston Edison Co.Bristol-Myers Co.Burroughs Corp.C.I.T. Financial Corp. (RCA Corp.)Campbell Soup Co.Caterpillar Tractor Co.Central & Southwest Corp.Cincinnati Gas & Electric Co.Cities Service Co.Cleveland Electric Illuminating Co.Colgate Palmolive Co.Consolidated Edison Co.Consumers Power Co.Continental Oil Co. (CONOCO)Corn Products Co. (CPC Intl. Inc.)Crown ZellerbackCutler-Hammer Inc. (Eaton Corp.)Dayton Power & Light Co.Detroit Edison Co.Dow ChemicalDuquesne Light Co.Eastman Kodak Co.Ex-Cell-O Corp.Federated Dept Stores Inc.Firestone Tire & Rubber Co.Florida Power Corp.Florida Power & Light Co.Food Fair, Inc.Ford Motor Co.General Amer. Transp. Corp. (GATX)General Electric Co.

1961

7.33339.50007.0000

4.7500

2.5000*******

1.00004.0000

18.66705.50002.0000

4.00003.0000

11.0000*******

4.00007.66675.50006.50005.00003.00004.66677.00004.00004.50004.66677.66674.00007.0000

7.00005.50004.00007.2000

*******

6.00004.33338.2500

10.00005.00005.00005.50007.0000

1962

6.25005.00006.00003.33334.91674.00001.66672.50004.00002.00004.66675.2500

14.16706.33333.00005.33334.66673.5000

10.66709.66674.40007.00007.00006.70004.66673.00005.25005.00004.12504.75004.75007.60003.33336.66675.33335.00005.33333.66677.00005.00006.20003.75007.90008.91673.00005.00004.66678.0000

1963

5.20004.25005.12502.75004.83333.00002.25003.60003.25002.25003.00004.9000

12.33306.00003.50005.00004.50004.6667

11.28604.66673.80006.57146.00006.64295.00003.00003.75006.00004.60005.12504.60007.80003.75004.66675.50004.37505.50003.50006.85713.66675.66674.20007.60008.42863.00004.25004.50006.5000

Page 24: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964

6.00003.40005.20002.41674.94442.50001.20002.50003.25004.50003.33334.857111.00006.56251.80004.20005.16675.125011.75003.60002.83336.37507.25006.77785.12503.70004.40004.91675.21435.58336.50007.28574.40006.40005.10004.80006.16673.83337.16673.60006.87504.57148.21437.62502.75004.66675.28575.5625

1965

7.50003.80005.33333.91674.93753.50002.33333.28573.50005.07144.66674.714311.00006.75003.58335.00006.37505.100012.87507.33332.78576.00007.25006.66675.10004.58334.91675.41674.35715.75006.31256.50004.33336.25005.41675.00007.42863.87508.33333.50007.11114.85718.21437.75003.20004.60005.83336.6875

1966

7.00003.50006.50004.33305.00004.00004.50004.50005.00005.66707.00004.833011.00006.00004.500011.33006.33305.500014.00007.75002.50006.50009.00007.00005.50004.16705.66705.83304.66706.00005.00006.33305.33306.00005.25005.33306.33304.50009.33305.00007.66705.00008.50008.50003.50003.50006.00006.5000

1967

8.00007.00006.50005.33304.66704.00007.00004.50005.00008.333010.00005.167013.33005.50004.500011.00006.00006.000014.330016.50003.75006.500011.00007.00005.50006.66705.66706.50004.66705.83306.33306.33305.50007.33305.25005.33306.33304.500010.00005.00007.00005.33308.50008.33303.000010.00005.00006.5000

1968 1969

9.5330 8.00009.0000 *******6.7500 *******13.3300 *******5.3330 5.75004.0000 *******14.4000 1.50007.4500 1.50005.0000 *******11.1700 11.500010.0000 *******5.8000 5.750012.2000 8.50006.8500 6.75007.5500 2.000013.5000 4.25006.4670 5.25006.0000 *******15.0700 11.750024.7500 18.50003.9000 5.25005.3000 6.250012.0300 8.25006.9330 6.75007.2500 6.00007.9330 9.25007.0670 6.00008.6000 7.75004.4330 4.25007.2000 5.75007.0330 7.50005.2330 5.00005.5000 6.50006.9670 6.00007.3000 6.25006.1000 5.25009.7000 3.25004.0000 *******14.6300 10.50008.0000 *******9.3330 6.25007.6330 4.75008.0000 7.25008.1330 7.75004.0000 *******5.5000 6.7500******* 4.50006.6000 8.2500

Page 25: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.2 (continued)

IndustryCode

667728886642681182272731738173363868517248852881

General Foods Corp.General Mills Inc.General Motors Corp.General Portland Cement Co.General Public Utilities Corp.General Telephone & ElectronicsGoodrich (B.F.) Co.Goodyear Tire & Rubber Co.Grand Union Co. (Cavenham Ltd.)Great Atlantic & Pacific Tea Co.Gulf Oil Corp.Gulf States Utilities Co.Heinz (H. J.) Co.Hercules Inc.Hewlett Packard Co.Honeywell Inc.Household Finance Corp.Houston Ltg. & Pow. Co. (Hous. Inds.)Idaho Power Co.Ideal Cement (Ideal Basic Ind. Inc.)Illinois Power Co.Ingersoll-Rand Co.Inland Steel Co.International Business MachinesInternational Harvester Co.Intl. Nickel Co. Canada (INCO)International Paper Co.Intl. Telephone & Telegraph Corp.Johns-Manville Corp.Jones & Laug. Steel Corp. (LTV Corp.)Kaiser Aluminum & Chemical Corp.Kellogg Co.Kennecott Copper Corp.Kimberly-Clark Corp.Kroger Co.Liggett & Myers (Liggett Group)Lilly Eli Co.Litton Industries, Inc.Lockheed Aircraft Corp.Long Island Lighting Co.Marathon OilMcGraw Hill Inc.Mead CorporationMerck & CompanyMiddle South Utilities Inc.Minnesota Mining & Manufacturing Co.Moore Corp.Motorola, Inc.

1961

8.25002.00003.00004.00004.33336.00003.00004.33336.33335.50003.66676.66676.50008.0000

17.50007.80005.00007.25007.0000

6.00004.00002.3333

17.0000*******6.66672.5000

10.00002.0000

8.00002.00005.25003.50005.00008.0000

20.7500*******

7.0000

8.5000

8.40005.5000

12.80008.00008.0000

1962

7.66674.33334.20002.00004.50006.37502.66674.00003.12504.30005.00006.75006.33337.5000

15.33306.33335.33337.80006.00004.66676.50003.33333.0000

15.50002.66677.20004.00009.75002.75004.00008.66676.50001.00004.30002.50001.66675.3333

17.83307.00006.33334.66677.66673.66677.00005.3333

11.00008.00007.5000

1963

7.50004.25003.80002.83335.00006.10003.25004.40002.33333.75004.40006.62505.00006.7500

14.50007.42864.75008.41676.00003.50006.20003.33332.8000

15.00002.87504.20004.25008.80002.75003.00009.00007.25001.25004.40003.60000.75006.6250

15.14305.25006.83333.75007.71435.00008.71435.9000

10.14307.75007.0000

Page 26: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968 1969

7.33334.80004.43753.50005.14296.93753.60004.87502.62503.00006.00006.75004.25007.142912.00006.78575.56258.50006.50003.80005.64293.25002.500015.11103.10005.35714.16679.00003.20001.50004.16678.33332.50004.41673.41671.00006.750013.12503.20006.80005.58338.00003.87509.00006.50009.12507.40007.7143

6.77786.66674.50002.75005.28577.00004.00005.37504.20002.57145.68757.35714.75007.000012.00007.87506.11118.75006.58333.60005.78573.60003.285714.88904.33335.64294.16679.14293.66672.91675.91678.00003.66674.28574.57141.00008.642913.50005.00006.60006.08338.25004.30009.88897.07149.37507.40008.8750

6.66709.00003.16705.00004.75008.66704.50005.16705.50002.00005.75007.50005.80006.333013.50007.66705.00008.50006.5000*******6.16704.50004.000015.00005.33307.33304.333011.00004.00002.66705.50007.00003.66704.50004.00003.00009.750017.00009.00006.50005.16708.66705.250010.33007.833010.25008.000010.6700

6.33309.00004.66705.00004.75008.66706.16705.33305.00003.00007.00007.16707.00006.333015.67008.66705.25008.50006.6670*******6.16704.00004.000016.00005.33306.33304.333011.33004.33302.66707.00007.00006.00004.83303.50003.000011.500017.00007.33304.50008.333011.00005.500010.67007.833010.83007.500012.0000

6.267011.65004.700016.00004.850010.70005.10007.267011.00001.10007.00008.100010.60008.067018.90009.700011.10008.80008.06709.00006.80008.00002.200015.37008.60005.96705.633011.70008.36705.200012.50008.95007.63304.83304.85004.000015.000014.93007.10006.50009.500012.03006.300014.73008.067010.50007.000014.7700

6.250011.00006.5000*******5.00009.25005.25007.25007.25004.00007.50007.25007.50004.000012.500013.25009.75008.00006.5000*******6.5000*******1.250014.25004.50009.00004.500011.75003.2500*******4.00006.50003.50004.5000**************13.00005.75001.2500*******10.50007.75006.000010.75007.500010.0000*******4.7500

Page 27: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.2 (continued)

IndustryCode

616883227725278265384188862213385846864854221444

National Biscuit Co. (NABISCO)National Cash Register Co. (NCR)National Dairy Prods. (Kraft Inc.)National Distillers & Chemical Corp.National Lead Co. (NL Industries)National Steel Corp.New York State Electric & Gas Co.Niagara Mohawk Power Corp.No. Amer. Aviation (Rockwell Intl.)North Amer. Car Corp. (Flying Tiger)Northern States Power Co.Norwich Phar. Co. (Morton-Norwich)Oklahoma Gas & Electric Co.Otis Elevator Co. (United Tech.)Owens-Corning Fiberglass Corp.Pacific Gas & Electric Co.Penney (J.C.) Co., Inc.Pfizer (Chas & Co.) Inc.Phelps Dodge Corp.Philip Morris Inc.Phillips Petroleum Co.Pitney-Bowes, Inc.Pittsburg Plate Glass (PPG Ind.)Polaroid Corp.Prentice Hall Inc.Procter & Gamble Co.Public Service of ColoradoPublic Service Electric & Gas Co.Radio Corp. of America (RCA Corp.)Republic Steel Corp.Reynolds Metals Co.Reynolds (R.J.) Tob. Co. (Rey. Ind.)Richardson-Merrell Inc.Rohm/Haas Co.Royal Dutch Petroleum Co.Safeway Stores, Inc.Scott Paper Co.Sears, Roebuck & Co.Shell Oil Co.Singer Co.Smith Kline & French (Smithkline)Socony (Mobil Oil Corp.)Southern Co.Southwestern Public Service Co.Sperry Rand Corp.Standard Oil Co. of CaliforniaStandard Oil Co. of IndianaStandard Oil of N. J. (Exxon)

1961

4.00009.00004.00003.00005.5000

6.00003.0000

9.00006.0000

10.75006.00007.50009.00005.66673.50008.66672.00005.00004.00009.00002.0000

17.200015.50009.00006.00005.00008.0000

7.500012.000011.00007.7500

5.00006.75006.33333.3333

9.40003.00006.25007.0000

*******3.50002.50004.3333

1962

4.25008.33333.83333.33334.25003.66675.83334.00007.00008.75005.00009.00006.33336.75007.40005.75004.00008.00002.66674.33333.33339.60002.6667

16.167013.60007.50007.40005.66678.25003.0000

10.25007.33338.00007.16674.75002.83336.50006.50003.25007.25009.33334.33336.50006.62503.66674.50001.66675.0000

1963

5.40007.00003.87503.33332.62502.87505.33334.37505.00005.25004.75008.00006.50004.90006.80005.40003.75008.21432.25004.00003.25009.40002.2500

17.333012.00006.28576.60005.66677.40002.75009.50004.75006.00007.20004.25004.60006.33336.50003.20006.33338.71433.75006.50006.62504.25003.75003.33334.8000

Page 28: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968 1969

6.4286 6.4286 6.3330 6.0000 6.5670 6.50007.2222 7.1111 7.3330 8.0000 9.8670 10.00004.2857 4.7143 5.6670 5.6670 6.9670 8.00001.7500 2.2000 4.3330 5.3330 6.0000 *******3.2857 3.5000 3.5000 5.0000 6.3000 *******1.9000 3.2500 4.0000 4.6670 6.1670 1.25005.0000 5.0000 5.0000 5.0000 ******* *******4.7500 4.6667 4.8330 4.8330 5.0330 4.25002.8000 1.9000 3.6670 4.0000 4.0000 *******6.0000 7.0000 5.0000 5.0000 ******* *******4.7000 4.7500 4.7500 4.7500 4.5000 *******6.8000 7.8000 8.0000 8.5000 11.8500 6.00007.0000 7.3333 6.8330 6.8330 6.5000 *******3.8000 4.6000 5.0000 5.0000 6.0000 6.0000******* 6.5714 9.0000 7.5000 8.3500 *******5.5000 5.4286 5.6670 5.6670 7.0000 5.50004.9286 6.0625 7.7500 8.0000 9.9330 8.75007.4444 7.8889 8.3330 9.0000 9.3330 9.00001.9167 2.5833 2.6670 4.6670 7.1000 6.50003.5000 4.3000 5.2500 7.0000 8.0000 *******4.2143 5.2143 4.5000 7.3330 6.9670 8.25007.5833 7.5833 9.0000 8.6670 8.2000 10.00003.2000 4.0000 4.5000 4.5000 8.6500 *******17.3330 18.5000 16.5000 19.3300 27.2300 16.750010.8000 10.4000 13.5000 15.0000 21.0500 12.00006.5000 6.3125 7.1670 7.5000 8.9500 7.00006.7857 6.5000 6.0000 6.0000 6.9000 5.75005.7500 5.7500 5.8330 5.8330 6.3330 6.00005.3333 6.8333 7.6670 8.0000 13.1000 7.50001.2000 2.6667 2.6670 3.0000 3.0000 *******4.3000 5.7500 5.0000 5.6670 11.1000 3.75004.3333 4.1667 4.6670 4.5000 6.0000 *******5.3333 6.1429 7.0000 7.5000 8.4000 9.25008.1429 8.5714 8.0000 11.0000 8.2500 *******4.5000 4.6667 4.6670 6.3330 5.5330 6.50005.3333 5.0000 4.7500 4.5000 5.7000 *******6.3333 6.3333 6.6670 5.8330 4.8000 4.50008.0000 8.5556 8.6670 7.0000 9.5330 8.00004.8125 5.5625 5.6670 7.6670 9.1330 6.00007.6000 6.4000 5.3330 8.0000 7.9000 8.75008.3333 8.6250 8.1670 7.1670 6.9670 4.00004.5000 5.2857 5.1670 6.5000 7.2670 6.25006.5000 6.8125 6.3330 6.8330 6.5670 6.50007.2000 7.4167 7.7500 7.7500 5.3500 7.00004.2000 4.5000 11.0000 11.0000 23.7000 8.00004.7143 5.3571 5.5000 5.1670 6.1330 7.25004.0714 4.3571 4.5000 7.0000 8.2330 4.55006.5625 5.9375 5.0000 5.1670 5.8670 5.0000

Page 29: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.2 (continued)

IndustryCode

57824812847783521211

Sterling Drug Inc.Swift & Co. (Esmark)Talcott Nat. (Assoc. Fst. Cap. Corp.)Tampa Electric Co.Texaco Inc.Texas Gulf Sulphur Co. Inc.Texas Instruments, Inc.Texas Utilities Co.Union Carbide Corp.Union Oil Co. of CaliforniaUnited Aircraft Corp. (United Tech.)U. S. Gypsum Co.U. S. Rubber (Uniroyal, Inc.)U. S. Steel Corp.Upjohn Inc.Virginia Electric & Power Co.Westinghouse Electric Corp.Wisconsin Electric Power Co.Xerox Corp.Zenith Radio Corp.

1961

7.00003.0000

10.50009.50005.66673.0000

15.00008.00005.50006.0000

*******5.00002.50001.66678.20007.50007.0000

25.000012.0000

1962

5.33332.50009.00009.12506.20002.00009.00007.90004.80003.33337.33334.75002.50001.66676.16678.00006.25004.0000

22.66709.0000

1963

6.66672.50006.80008.87505.40001.3333

10.00007.60005.00002.66675.00004.30002.66673.00008.28577.58335.20004.3333

22.42909.2500

Table 1.A.3 Average Predicted Earnings per Share for the Next YearDivided by Average Normalized Earningsfor Current Year [(El+ XIWE) - 1 ]

IndustryCode 1961 1962 1963

A.C.F. Industries, Inc. ******* 0.1429 0.4506Addressograph-Multigraph (AM Corp.) 0.0963 -0.0409 -0.0598Air Reduction Co. (B.O.C. Fin. Corp.) -0.0247 -0.0476 0.0069Allegheny Power System Inc. ******* ******* *******Allied Chemical Corp. 0.1120 -0.0400 0.2178Alcan Aluminum Ltd. 0.1083 -0.0969 0.1943Aluminum Company of America -0.0055 -0.0704 0.1218Amerada Pet. (Amerada Hess) -0.0895 -0.0027 0.1380American Cyanamid Co. 0.0783 0.1129 0.1506American Electric Power Co. 0.0577 0.0596 0.1374American Home Products Corp. 0.0930 0.0565 0.0791Amer. Mach. & Foundry Co. (AMF Ind.) ******* ******* *******Amer. Nat. Gas Co. (Amer. Nat. Res.) -0.0296 0.0728 0.0581Amer. Smelt. & Refin. (UV Ind.) ******* -0.1111 -0.1445American Telephone & Telegraph Co. 0.0365 0.0534 0.0408American Tobacco (Amer. Brands, Inc.) ******* -0.0291 -0.0118Anaconda Co. ** -0.0110 -0.0556Armco Steel Corp. (ARMCO Inc.) -0.1219 -0.2570 0.0000Armour & Co. (Esmark) ******* ******* *******

Page 30: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968 1969

7.16672.25004.60009.20007.000018.75008.87507.91675.50005.62504.20003.68753.87501.83337.62507.38894.6000

4.666723.87508.1667

7.25002.66674.66679.08336.562518.80009.50008.08335.94446.33336.60003.57144.40002.83338.71437.22227.0000

4.625025.33309.5000

7.16705.00005.00009.50007.167011.500012.00008.16705.50005.667012.00003.66705.75002.33308.33307.33306.6670

4.000022.670010.6700

7.33305.00004.75009.50007.500014.000015.33008.16705.50008.000010.00005.33308.75002.33308.00007.33307.0000

6.500022.330010.0000

9.33305.00005.000011.10008.33308.000018.13007.86705.233012.300012.170011.65004.90003.53307.80007.433011.5700

27.730012.8700

8.7500

8.50004.7500*******15.50008.25002.25009.75003.50002.75002.00001.50007.00007.00007.5000

19.00009.0000

1964 1965 1966 1967 1968

0.7073 0.4464 0.4290 0.0000 0.0960-0.0309 0.0896 0.0150 0.4000 0.07600.1187 0.2395 -0.0100 0.0360 0.1350

******* ******* -0.0294 0.0000 *******0.2292 0.1261 0.0000 0.0000 0.23600.3651 0.2623 0.2330 -0.5800 0.01100.1221 0.3867 0.1430 0.9570 0.00000.2372 0.1130 -0.0200 -0.0200 0.06000.2396 0.1458 0.0000 0.1050 0.03900.0636 0.0463 0.0000 0.0000 0.0850

******* 0.1124 0.0000 0.0000 0.0930******* ******* 0.0830 ******* *******0.0612 0.0826 -0.0161 0.0000 *******0.1691 0.1458 0.2080 -0.1791 0.02400.0660 0.0584 0.0430 0.0000 0.08100.0784 0.1186 -0.0161 ******* *******0.2917 0.5823 0.7140 0.0000 0.1630

-0.0595 0.2228 0.0420 0.0000 -0.1364

Page 31: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.3 (continued)

IndustryCode 1961 1962 1963

0.0100 0.0211 -0.0412

-0.0102 0.1010 -0.20980.0588 0.0704 0.0377

-0.0063 -0.3033 -0.2286******* -0.2121 -0.06790.0457 0.0043 0.0581

0.1020 0.1541 0.0812******* -0.0221 -0.22310.0435 0.0332 0.02690.0186 -0.0629 0.00890.0785 0.0471 0.29810.1035 0.0820 0.09390.0780 0.0623 0.0145

4 Atlantic Richfield Co.8 Atlas Chem. Ind. Inc. (Imperial Ch.)2 Baltimore Gas & Electric Co.1 Beckman Instruments, Inc.8 Beneficial Finance Co.3 Bethlehem Steel Corp.7 Boeing Co.6 Borden Inc.2 Boston Edison Co.5 - Bristol-Myers Co.1 Burroughs Corp.8 C.I.T. Financial Corp. (RCA Corp.)6 Campbell Soup Co.7 Caterpillar Tractor Co.2 Central & Southwest Corp.2 Cincinnati Gas & Electric Co.4 Cities Service Co.2 Cleveland Electric Illuminating Co.6 Colgate Palmolive Co.2 Consolidated Edison Co.2 Consumers Power Co.4 Continental Oil Co. (CONOCO)6 Corn Products Co. (CPC Intl. Inc.)8 Crown Zellerback1 Cutler-Hammer Inc. (Eaton Corp.)2 Dayton Power & Light Co.2 Detroit Edison Co.8 Dow Chemical2 Duquesne Light Co.8 Eastman Kodak Co.7 Ex-Cell-O Corp.6 Federated Dept Stores Inc.8 Firestone Tire & Rubber Co.2 Florida Power Corp.2 Florida Power & Light Co.6 Food Fair, Inc.7 Ford Motor Co.7 General Amer. Transp. Corp. (GATX)1 General Electric Co.6 General Foods Corp.6 General Mills Inc.7 General Motors Corp.7 General Portland Cement Co.2 General Public Utilities Corp.8 General Telephone & Electronics8 Goodrich (B.F.) Co.8 Goodyear Tire & Rubber Co.6 Grand Union Co. (Cavenham Ltd.)

0.0942

0.03310.09350.0876

-0.1349-0.1125

0.0073

0.02270.01800.03570.0437

0.13710.09060.01490.08520.02270.1789

-0.06880.09380.09270.08950.0426

0.0293

0.06830.06650.07950.0133

-0.1043

0.0756

-0.0087-0.04960.06670.0400

-0.04470.0190

-0.13560.05370.04790.1644

-0.17060.13640.0783

-0.2025-0.0691

0.0610

0.21260.19300.11560.0494

-0.0260

0.1268

0.10340.02370.06660.0728

0.04170.0621

-0.03700.03150.12820.2235

-0.02690.06860.1725

-0.14470.0733

Page 32: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968

-0.0099 0.1061

0.98110.1351******0.07760.1087

0.1037-0.08330.02850.06780.72590.09090.0760

0.16480.1294

-0.02700.23240.1910

0.1952

-0.01490.09010.05310.24760.0235

0.08260.49330.02860.03030.37140.04820.1154

0.0965 0.1406

0.1038******0.04710.11570.3217

0.1178

0.0870-0.0333-0.0250-0.0278-0.02780.10700.03800.00000.0000

-0.02940.1710

-0.0185-0.05880.1820

-0.02170.00000.01200.0000

-0.02270.0000

-0.01670.0180

-0.0179-0.04050.0000

-0.0263-0.0227-0.01320.00000.0000

-0.0206 0.3290

0.00000.15800.0000-0.14290.00000.04500.03600.0000-0.1923-0.13330.00000.08700.00000.0000-0.02170.00000.00000.00000.00000.00000.07700.03000.23100.00000.00000.00000.00000.0000

0.0650-0.04470.0650

-0.1429-0.13790.1710

0.10300.28100.0660

-0.05880.08500.06400.07500.13200.07300.08200.04800.12500.05800.12800.02800.26600.04300.06600.0940

0.1280

0.24350.14710.09530.0987

0.12500.23950.06890.01370.20110.2584-0.18380.04110.2485-0.09960.1391

0.14280.17250.04380.0390

0.15890.23290.17180.00000.13930.1060-0.11610.02910.13490.01100.2073

-0.02780.2330

-0.02270.0000

-0.1471-0.10380.1880

-0.1333-0.0366-0.0278-0.1912-0.20000.00000.00000.07800.12900.0000

0.0000-0.14290.00000.00000.0000-0.09090.08300.00000.0000-0.0476-0.0500-0.10000.0000-0.04170.0000-0.07890.0560

0.12500.03600.03600.0510******-0.09090.13600.12200.04200.2290-0.0948******0.04700.11600.11100.06600.0750

Page 33: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.3 (continued)

IndustryCode 1961 1962 1963

6 Great Atlantic & Pacific Tea Co.4 Gulf Oil Corp.2 Gulf States Utilities Co.6 Heinz (H. J.) Co.8 Hercules Inc.1 Hewlett Packard Co.1 Honeywell Inc.8 Household Finance Corp.2 Houston Ltg. & Pow. Co. (Hous. Inds.)2 Idaho Power Co.7 Ideal Cement (Ideal Basic Ind. Inc.)2 Illinois Power Co.7 Ingersoll-Rand Co;3 Inland Steel Co.1 International Business Machines7 International Harvester Co.3 Intl. Nickel Co. Canada (INCO)8 International Paper Co.1 Intl. Telephone & Telegraph Corp.7 Johns-Manville Corp.3 Jones & Laug. Steel Corp. (LTV Corp.)3 Kaiser Aluminum & Chemical Corp.6 Kellogg Co.3 Kennecott Copper Corp.8 Kimberly-Clark Corp.6 Kroger Co.8 Liggett & Myers (Liggett Group)5 Lilly Eli Co.1 Litton Industries, Inc.7 Lockheed Aircraft Corp.2 Long Island Lighting Co.4 Marathon Oil8 McGraw Hill Inc.8 Mead Corporation5 Merck & Company2 Middle South Utilities Inc.8 Minnesota Mining & Manufacturing Co.8 Moore Corp.1 Motorola, Inc.6 National Biscuit Co. (NABISCO)1 National Cash Register Co. (NCR)6 National Dairy Prods. (Kraft Inc.)8 National Distillers & Chemical Corp.8 National Lead Co. (NL Industries)3 National Steel Corp.2 New York State Electric & Gas Co.2 Niagara Mohawk Power Corp.7 No. Amer. Aviation (Rockwell Intl.)

*******0.0417 -0.0112 0.1062

0.1675 0.0834 0.07840.0417 0.1181 0.0551

-0.0193 -0.1237 .0.22180.2549 0.0856 0.08720.0933 0.0769 0.14000.0230 0.0169 0.0917

******* 0.0098 0.01330.0250 0.0588 0.0953

0.1532 -0.0476 0.0677******* ******* ************** -0.0484 0.1057

0.3941 0.0018 0.07650.0270 -0.1316 -0.04340.1209 0.1652 0.18020.0640 -0.0389 0.1048

******* _ 02515 0.0746******* -0.0821 0.0045******* 0.1368 0.13560.0000 -0.0557 -0.1346

-0.0348 -0.0365 0.0309-0.0323 0.0430 0.0762

-0.0040 0.0354 0.07580.0333 0.2169 0.1402

******* 0.3078 0.2023******* ******* ************** 0.0417 0.26180.1750 0.0294 *******

******* -Q.0162 0.10030.0706 0.0580 0.15070.1000 0.0737 0.05700.1093 0.0547 0.0710

******* 0 1 3 3 0 01383

0.0256 0.0745 0.12550.0576 -0.1408 -0.14350.0214 0.0168 -0.0105

******* ******* *******0.0982 -0.0601 0.0146

******* -Q.0503 0.3440******* ******* *******

0.2171 0.1208

Page 34: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968

******* ******* -0.0435 0.0000 0.08600.0992 0.0805 -0.0093 0.0000 0.0830

******* ******* -0.0417 0.0000 0.1400******* ******* -0.0143 -0.0250 0.07500.1771 0.0246 -0.3750 0.0000 0.03800.1146 0.2520 0.0000 0.1250 0.1590

-0.4447 0.1959 -0.2375 0.2900 0.13400.0870 0.1740 0.1520 -0.1071 0.08800.1406 0.0568 -0.0227 0.0000 0.08500.1429 0.0667 -0.0227 0.0000 0.0700

-0.0902 0.0000 ******* ******* **0.0684 0.0575 0.0000 0.0000 0.0710

0.0051 0.0814 -0.0156 -0.0571 -0.0976******* ******* -0.1840 0.0140 0.10600.5914 0.2230 -0.0135 0.0610 0.03200.1680 0.2197 -0.0094 -0.1667 0.07100.1166 0.0812 -0.1200 0.0870 0.04800.1148 0.1041 0.0000 0.0000 0.11800.2341 0.0340 -0.1333 0.0000 0.08800.0617 0.2115 0.1810 -0.0769 0.03800.0725 0.3067 0.1330 -0.1143 -0.00360.1970 0.0385 0.0000 0.0000 0.06400.1246 0.4965 0.3700 -0.1489 0.37100.0207 -0.0163 -0.1111 0.0000 0.10600.2400 0.0918 -0.1600 0.0670 0.0570

******* 0.0090 ******* *******0.2101 0.2500 -0.0152 0.0000 0.11600.0951 0.1912 -0.0345 0.2070 0.4800

-0.0079 -0.0321 0.2000 0.1400 0.0710******* ******* -0.4138 0.0000 *******0.1947 0.0824 0.0400 0.0180 0.12700.2071 0.2343 0.0000 0.1330 0.00000.1818 0.1628 0.0000 0.0540 0.04700.2638 0.2187 -0.0185 0.0000 0.09400.1493 0.0966 -0.0385 0.0000 0.07700.1082 0.0783 ******* 0.0000 0.1440

******* ******* -0.0641 0.0000 *******0.2978 0.4692 -0.0769 0.1110 0.17400.0841 0.0199 0.0000 0.0000 0.0420

-0.0200 0.0069 -0.0128 0.0240 0.22200.1531 0.0204 0.0000 0.0370 0.0850

******* ******* 0.0000 —0.0278 *******0.1348 0.0777 -0.0500 0.0640 0.09200.0535 0.3358 0.0000 -0.1400 -0.0756

******* ******* o.OOOO 0.0000 ************** ******* o.OOOO 0.0000 0.1130-0.0205 -0.0280 0.0910 ******* *******

Page 35: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.3 (continued)

IndustryCode

7252

78265384188862213385846864

8542

214445

78

24

81284

North Amer. Car Corp. (Flying Tiger)Northern States Power Co.Norwich Phar. Co. (Morton-Norwich)Oklahoma Gas & Electric Co.

Otis Elevator Co. (United Tech.)Owens-Corning Fiberglass Corp.Pacific Gas & Electric Co.Penney (J.C.) Co., Inc.Pfizer (Chas & Co.) Inc.Phelps Dodge Corp.Philip Morris Inc.Phillips Petroleum Co.Pitney-Bowes, Inc.Pittsburg Plate Glass (PPG Ind.)Polaroid Corp.Prentice Hall Inc.Procter & Gamble Co.Public Service of ColoradoPublic Service Electric & Gas Co.Radio Corp. of America (RCA Corp.)Republic Steel Corp.Reynolds Metals Co.Reynolds (R.J.) Tob. Co. (Rey. Ind.)Richardson-Merrell Inc.Rohm/Haas Co.Royal Dutch Petroleum Co.Safeway Stores, Inc.Scott Paper Co.Sears, Roebuck & Co.Shell Oil Co.

Singer Co.Smith Kline & French (Smithkline)Socony (Mobil Oil Corp.)Southern Co.

Southwestern Public Service Co.Sperry Rand Corp.Standard Oil Co. of CaliforniaStandard Oil Co. of IndianaStandard Oil of N.J. (Exxon)Sterling Drug Inc.

Swift & Co. (Esmark)Talcott Nat. (Assoc. Fst. Cap. Corp.)

Tampa Electric Co.Texaco Inc.

Texas Gulf Sulphur Co. Inc.Texas Instruments, Inc.Texas Utilities Co.Union Carbide Corp.Union Oil Co. of California

1961

0.18000.05520.15900.1040

0.07830.03610.05410.08570.07190.06190.05550.16090.18590.46900.25920.13240.0329

-0.0147

-0.10940.08750.06200.1068

0.03450.05290.10430.0000

0.1027-0.0656

0.0859

0.0202-0.0057

0.0152-0.0195

0.0789

0.0902

-0.10150.07950.06040.0296

1962

0.03510.06150.01590.1047

-0.06670.07460.00870.1039

-0.0629-0.0042-0.0175

0.0154-0.0088

0.38260.1318

-0.00700.03000.05670.2337

-0.3625-0.2103

0.0079-0.0041

0.10360.04550.03390.0028

-0.03420.0514

0.09050.07450.0735

-0.18920.07260.03780.04440.0279

0.0634

0.0772

-0.04850.0763

-0.00140.0383

1963

0.13790.13240.01110.2105

-0.05260.02210.01120.0940

-0.02370.0464

-0.02680.06280.00000.22950.0853

-0.01670.09000.10110.3292

-0.00710.00640.0425

-0.02290.18780.06170.07840.09260.09380.1995

0.09330.14810.0729

0.05880.00360.09080.18480.0261

-0.1184

0.1194

0.21630.13290.03940.1980

Page 36: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968

0.32200.00680.1038

0.1364

0.10320.06340.22580.08890.1739

0.02810.04760.11110.1186

-0.06120.15380.00620.07410.07320.1481

- 0.07570.1754

-0.01230.0222

0.14700.00640.13890.09910.10050.1557

0.12870.09000.1200

0.14630.03900.14180.13760.0667

-0.0714

0.0634

0.26920.09660.14500.2969

0.26960.00860.0611

0.0980

0.00840.07340.10540.10090.2371

0.04030.06780.02680.1615

0.96660.21570.00600.05260.07050.3898

0.10540.4281

0.03700.0604

0.06510.0253

-0.03530.11110.00410.1262

0.09940.09520.0714

0.11360.06100.13540.02260.0877

-0.0580

0.0819

0.34810.04950.18090.2915

0.0530-0.02380.0000

-0.0333-0.0714-0.0526-0.0217-0.0303-0.01470.1490

0.11500.0220

-0.2222-0.0500

0.0000-0.01320.00000.0000

-0.0185

0.13300.1670

-0.02860.0000

0.0000-0.01140.14300.0000

-0.03850.0000

- 0.06380.00000.0000

-0.3182

-0.05560.09400.00000.0130

-0.0179-0.0278

0.0000

0.00000.0090

-0.32500.00000.00000.000

-0.0111

-0.08700.00000.0000

0.00000.10000.00000.00000.02900.0000

-0.1250

0.00000.12000.0000

0.04400.07700.00000.00000.00000.0400

0.0610

0.0000

0.00000.10500.06300.12500.0000

0.0400-0.35480.00000.0000

0.00001.37500.00000.0230

-0.03390.0000

0.00000.0000

0.33300.00000.00000.0000

*******

0.1520

0.07400.03700.06000.04800.08200.3170

0.23100.12800.0200

0.18800.19200.03500.05900.03800.0850

0.4700

0.0600

0.06800.11900.04500.06700.11100.0580

0.14300.06900.09800.0630

0.02600.13600.08400.06300.06400.3800

0.16400.0670

0.18800.09300.13200.0980

Page 37: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.3 (continued)

IndustryCode

7783521211

Table 1.

IndustrjCode

7182833452588388337482183762518

United Aircraft Corp. (United Tech.)U. S. Gypsum Co.U. S. Rubber (Uniroyal, Inc.)U. S. Steel Corp.Upjohn Inc.Virginia Electric & Power Co.Westinghouse Electric Corp.Wisconsin Electric Power Co.Xerox Corp.Zenith Radio Corp.

1961 1962

-0.0513 -0.1765 -0.1053 -0.06060.0286

0.16110.04970.13130.37800.02350.1077

-0.2216 -0.2064*******

0.86000.1009

0.04930.53120.0883

1963

-0.09020.0229

-0.0947-0.0584

0.10370.0697

-0.25250.06670.60000.2258

A.4 Dividend-Payout Ratio Based on Normalized Earnings (DINE)

j

A.C.F. Industries, Inc.Addressograph-Multigraph (AM Corp.)Air Reduction Co. (B.O.C. Fin. Corp.)Allegheny Power System Inc.Allied Chemical Corp.Alcan Aluminum Ltd.Aluminum Company of AmericaAmerada Pet. (Amerada Hess)American Cyanamid Co.American Electric Power Co.American Home Products Corp.Amer. Mach. & Foundry Co. (AMF Ind.)Amer. Nat. Gas Co. (Amer. Nat. Res.)Amer. Smelt. & Refin. (UV Ind.)American Telephone & Telegraph Co.American Tobacco (Amer. Brands, Inc.)Anaconda Co.Armco Steel Corp. (ARMCO Inc.)Armour & Co. (Esmark)Atlantic Richfield Co.Atlas Chem. Ind. Inc. (Imperial Ch.)Baltimore Gas & Electric Co.Beckman Instruments, Inc.Beneficial Finance Co.Bethlehem Steel Corp.Boeing Co.Borden Inc.Boston Edison Co.Bristol-Myers Co.Burroughs Corp.C.I.T. Financial Corp. (RCA Corp.)

1961

0.44440.6849

0.72000.50000.52750.53470.69560.73080.66980.55000.5333

0.6188

*******0.5505

*******0.44000.4615

*******0.36470.8276

*******0.52720.68970.4898

*******0.5833

1962

0.52910.40910.68030.71760.72000.43640.46600.53330.66670.70880.66960.60000.55170.51110.62610.58250.54940.67420.48700.50530.51060.7000

*******0.41120.72670.48480.54840.71670.49180.58820.6061

1963

0.55560.43480.68970.71480.71290.48000.46150.57810.64290.72300.65980.64290.62370.41070.60250.58820.52080.66670.48280.49480.61540.7077

*******0.41740.54540.57140.55190.67690.46150.61540.6337

Page 38: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968

-0.1111-0.01190.0317

-0.20250.08640.03480.1508

0.02620.44940.0489

0.0784-0.13371.38570.03050.09800.04030.3040

0.15070.10420.4328

0.2790-0.14470.25000.0140

-0.01720.0000

-0.1429

0.0000-0.1667-0.1212

0.00000.0000

-0.1500-0.15560.00000.00000.0590

0.00000.10900.0380

-0.06250.09500.1580

-0.08090.07400.09100.0810

0.19000.1080

1964 1965 1966 1967 1968 1969

0.65370.45360.71940.72860.64290.48150.42480.53850.62500.71510.65390.69230.65310.61760.62400.62740.52080.55560.35000.47530.60000.7200

0.42160.44120.34480.54800.68840.46670.62500.6154

0.56430.49060.59880.69680.63870.49550.46670.55560.53750.70000.62300.72000.62380.58330.59260.55930.63290.6218

0.44840.45160.7013

0.44270.53100.28570.51770.68090.46020.53330.6095

0.60000.45000.60000.70000.65000.50000.45000.55000.65000.70000.65000.50000.65000.50000.65000.55000.50000.6000

0.60000.40000.60000.70000.60000.50000.40000.60000.60000.80000.6000

0.66000.52000.8100

0.67000.23000.90000.60000.66000.77000.6000

0.60000.50000.6000

0.89000.6500

0.50000.6000

0.58000.5500

0.40000.50000.70000.15000.50000.55000.50000.55000.75000.50000.40000.6000

0.70000.10000.50000.50000.30000.50000.80000.50000.40000.6000

0.70000.41000.42000.51000.28000.6900

0.62000.23000.5900

0.60000.4200

0.54000.56000.35000.12000.62000.74000.5900

0.6500

0.44000.5300

0.3000 0.4900 0.4700

0.64000.40000.38000.56000.24000.6600

0.53000.18000.5700

Page 39: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.4 (continued)

IndustryCode

67224262246812282876822677166772888664268

1182272

Campbell Soup Co.Caterpillar Tractor Co.Central & Southwest Corp.Cincinnati Gas & Electric Co.Cities Service Co.Cleveland Electric Illuminating Co.Colgate Palmolive Co.Consolidated Edison Co.Consumers Power Co.Continental Oil Co. (CONOCO)Corn Products Co. (CPC Intl. Inc.)Crown ZellerbackCutler-Hammer Inc. (Eaton Corp.)Dayton Power & Light Co.Detroit Edison Co.Dow ChemicalDuquesne Light Co.Eastman Kodak Co.Ex-Cell-0 Corp.Federated Dept Stores Inc.Firestone Tire & Rubber Co.Florida Power Corp.Florida Power & Light Co.Food Fair, Inc.Ford Motor Co.General Amer. Transp. Corp. (GATX)General Electric Co.General Foods Corp.General Mills Inc.General Motors Corp.General Portland Cement Co.General Public Utilities Corp.General Telephone & ElectronicsGoodrich (B.F.) Co.Goodyear Tire & Rubber Co.Grand Union Co. (Cavenham Ltd.)Great Atlantic & Pacific Tea Co.Gulf Oil Corp.Gulf States Utilities Co.Heinz (H. J.) Co.Hercules Inc.

Hewlett Packard Co.Honeywell Inc.Household Finance Corp.Houston Ltg. & Pow. Co. (Hous. Inds.)Idaho Power Co.Ideal Cement (Ideal Basic Ind. Inc.)Illinois Power Co.

1961

0.49690.46510.69630.63830.57140.62810.52830.73170.68870.61820.64860.57140.5000

0.60780.73750.6977

0.50000.38060.64290.48740.50290.38710.70310.68380.56140.72730.81300.67500.73120.74150.57890.37450.36360.47480.32730.71430.37380.4370

0.51610.47060.47410.6552

0.6875

1962

0.49140.45460.66460.58490.52170.59260.46670.71860.67470.53430.62650.72000.49080.70940.75860.62740.75150.55090.49210.51300.41260.65330.49680.53730.44170.66860.56340.57600.65750.80540.70590.72100.66960.55700.40430.42860.63620.43280.65400.35710.4412

0.46240.45310.43590.67800.52460.6941

1963

0.52380.50000.67430.64730.51380.61970.48840.72180.68050.55880.62220.67290.51950.70510.77420.59070.74200.62190.50390.54470.41260.65230.49410.55380.42860.67030.57970.59260.61540.94120.71640.71760.65880.57890.42550.45280.56760.46710.68920.38840.4412

0.47620.44800.46000.70000.66670.6857

Page 40: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968 1969

0.52880.50000.66490.64560.48180.63160.47060.69110.70330.49410.60610.67890.44940.72260.72730.5833

0.75490.53400.50000.55240.43140.65140.4982

0.60000.44440.67110.64230.54800.59770.8517

0.70590.71230.68360.50580.43110.40000.59010.45640.70860.36700.5333

0.19340.46720.47270.7302

0.65570.7179

0.53330.43960.64940.63490.42060.63610.47220.72000.67170.50000.58820.66120.38260.69560.68420.5197

0.72730.51690.45330.49600.44040.64210.4767

0.54540.42860.64940.58970.53850.50000.8400

0.71430.69370.58890.48350.44040.31050,64090.45120.69270.38710.4598

0.19900.39640.43310.45430.6667

0.66670.6667

0.55000.50000.65000.75000.45000.70000.50000.95000.70000.50000.65000.60000.55000.70000.75000.5500

0.85000.6500*******0.55000.40000.65000.5500

0.60000.45000.65000.70000.55000.55000.7500

0.60000.85000.70000.50000.45000.50000.65000.45000.70000.40000.5000

0.10000.40000.50000.50000.6500

0.7000

0.50000.50000.60000.80000.40000.70000.50000.90000.70000.50000.60000.60000.50000.70000.80000.5000

0.80000.6000*******0.40000.40000.60000.5000

0.60000.40000.60000.70000.50000.50000.8000

0.80000.80000.70000.50000.40000.50000.60000.50000.70000.40000.5000

0.10000.40000.40000.50000.6000

0.7000

0.65000.59000.72000.70000.53000.74000.49000.69000.73000.53000.72000.62000.75000.66000.74000.5300

0.4900*******0.53000.37000.61000.4400

0.44000.73000.70000.57000.46000.7400

0.74000.69000.55000.39000.30000.74000.50000.70000.36000.4500

0.12000.33000.39000.55000.7400

0.7300

0.71000.45000.67000.67000.51000.74000.49000.70000.71000.52000.69000.65000.60000.72000.71000.5500

0.5000*******0.50000.39000.55000.5300

0.48000.66000.86000.59000.47000.7400

0.80000.67000.56000.38000.37000.63000.48000.68000.40000.5200

0.19000.28000.35000.50000.7400

0.7400

Page 41: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.4 (continued)

IndustryCode

731738173363868517248852881616883227725278265384

Ingersoll-Rand Co.Inland Steel Co.International Business MachinesInternational Harvester Co.Intl. Nickel Co. Canada (INCO)International Paper Co.Intl. Telephone & Telegraph Corp.Johns-Manville Corp.Jones & Laug. Steel Corp. (LTV Corp.)Kaiser Aluminum & Chemical Corp.Kellogg Co.Kennecott Copper Corp.Kimberly-Clark Corp.Kroger Co.Liggett & Myers (Liggett Group)Lilly Eli Co.Litton Industries, Inc.Lockheed Aircraft Corp.Long Island Lighting Co.Marathon OilMcGraw Hill Inc.Mead CorporationMerck & CompanyMiddle South Utilities Inc.Minnesota Mining & Manufacturing Co.Moore Corp.Motorola, Inc.National Biscuit Co. (NABISCO)National Cash Register Co. (NCR)National Dairy Prods. (Kraft Inc.)National Distillers & Chemical Corp.National Lead Co. (NL Industries)National Steel Corp.New York State Electric & Gas Co.Niagara Mohawk Power Corp.No. Amer. Aviation (Rockwell Intl.)North Amer. Car Corp. (Flying Tiger)Northern States Power Co.Norwich Phar. Co. (Morton-Norwich)Oklahoma Gas & Electric Co.Otis Elevator Co. (United Tech.)Owens-Corning Fiberglass Corp.Pacific Gas & Electric Co.Penney (J.C.) Co., Inc.Pfizer (Chas & Co.) Inc.Phelps Dodge Corp.Philip Morris Inc.Phillips Petroleum Co.

1961

0.91950.51610.2556

*******0.54240.55680.46510.6400

*******0.76920.51010.70970.76920.8065

*******

0.6578*******0.6300

0.62140.70000.42620.4304

0.71790.34780.54800.57140.7692

*******0.59540.7826

0.56000.76620.64610.76430.54050.43480.61330.70590.48570.75000.63720.5152

1962

0.93020.50790.27910.61940.55880.54070.43480.66670.59880.52170.56600.83330.54010.70970.70420.7874

*******0.29810.66530.52670.50980.66020.62610.66870.47760.45460.34480.69650.31580.55030.60000.71040.60380.62020.75510.52630.54740.75690.58330.73140.53780.40400.62220.65220.49350.75470.61020.5564

1963

0.91430.51560.33660.58540.66670.54930.39600.66670.49750.49310.57630.61540.57140.62860.78130.7289

*******0.35860.61820.54630.53850.66020.61070.64930.50000.44300.32000.67960.34780.57890.66670.76020.52800.59580.74070.44940.55170.77650.58330.73680.61020.42110.58820.67420.50600.71010.59020.5781

Page 42: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968 1969

0.84210.50000.38780.58060.68750.61870.34430.61070.41150.52170.60610.61540.55170.60270.77520.7652

0.36160.62760.52630.57140.61820.72310.61870.52630.45660.23670.62800.34780.59260.65750.73030.40420.60590.70170.40350.56270.75620.54680.70910.57190.42110.60840.64520.51110.67390.57830.5714

0.67800.56340.40400.48520.69320.62500.32880.52230.44930.48000.56410.62910.52290.50200.79050.5957

0.35710.62220.50590.57140.52710.66670.55730.50000.42670.21740.60860.31530.53060.60870.67360.54270.65860.77140.45380.56430.73850.49680.64310.53990.43700.59750.59140.47710.68970.52750.5256

0.5500 0.5000 0.4900 0.57000.4000 0.4000 0.3400 0.48000.6000 0.6000 0.6700 0.78000.6000 0.6000 0.6000 0.88000.6000 0.6000 0.7100 0.60000.4000 0.4000 0.3700 0.36000.6500 0.6000 0.6000 0.48000.6500 0.6000 0.6800 *******0.5000 0.5000 0.3600 0.35000.5500 0.5000 0.6400 0.64000.6000 0.6000 0.6100 0.48000.6000 0.6000 0.5500 0.47000.6000 0.6000 0.4900 *******0.7500 ******* ******* *******0.6500 0.6000 0.4700 0.48000.0000 0.0000 0.0000 0.00000.4300 0.4000 0.5200 0.48000.7500 0.8000 ******* *******0.5000 0.4000 0.5100 0.53000.5500 0.5000 0.5800 0.60000.6000 0.6000 0.5300 0.55000.6000 0.6000 0.7500 0.78000.7000 0.7000 0.6800 0.66000.5000 0.5000 0.4900 0.50000.4000 0.4000 ******* *******0.3000 0.2000 0.2200 0.18000.6500 0.6000 0.6800 0.81000.4000 0.4000 0.3300 0.28000.5500 0.5000 0.6000 0.61000.6000 0.6000 ******* *******0.7500 0.8000 0.8600 *******0.5000 0.5000 0.5800 0.56000.7500 0.8000 ******* *******0.9500 0.9000 0.7100 0.73000 5000 ******* ******* *******0.5000 0.5000 ******* *******0.7000 0.7000 ******* *******0.6000 0.6000 0.4800 0.49000.7000 0.7000 ******* *******0.6000 0.6000 0.7400 0.68000.4500 0.4000 0.5200 *******0.7000 0.7000 0.6000 0.55000.5500 0.5000 0.4800 0.45000.5000 0.5000 0.5400 0.53000.6500 0.6000 0.6300 0.46000 5500 ******* ******* *******0.5500 0.5000 0.6500 0.7600

Page 43: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.4 (continued)

IndustryCode

18886221338584686485422144457824812847783521211

Pitney-Bowes, Inc.Pittsburg Plate Glass (PPG Ind.)Polaroid Corp.Prentice Hall Inc.Procter & Gamble Co.Public Service of ColoradoPublic Service Electric & Gas Co.Radio Corp. of America (RCA Corp.)Republic Steel Corp.Reynolds Metals Co.Reynolds (R.J.) Tob. Co. (Rey. Ind.)Richardson-Merrell Inc.Rohm/Haas Co.Royal Dutch Petroleum Co.Safeway Stores, Inc.Scott Paper Co.Sears, Roebuck & Co.Shell Oil Co.Singer Co.Smith Kline & French (Smithkline)Socony (Mobil Oil Corp.)Southern Co.Southwestern Public Service Co.Sperry Rand Corp.Standard Oil Co. of CaliforniaStandard Oil Co. of IndianaStandard Oil of N.J. (Exxon)Sterling Drug Inc.Swift & Co. (Esmark)Talcott Nat. (Assoc. Fst. Cap. Corp.)Tampa Electric Co.Texaco Inc.Texas Gulf Sulphur Co. Inc.Texas Instruments, Inc.Texas Utilities Co.Union Carbide Corp.Union Oil Co. of CaliforniaUnited Aircraft Corp. (United Tech.)U. S. Gypsum Co.U. S. Rubber (Uniroyal, Inc.)U. S. Steel Corp.Upjohn Inc.Virginia Electric & Power Co.Westinghouse Electric Corp.Wisconsin Electric Power Co.Xerox Corp.Zenith Radio Corp.

1961

0.49660.56410.08700.44440.52160.54740.6029

0.29850.46670.31070.1611

0.52760.63830.54050.4400

0.67570.45920.72290.6960

0.42700.32000.63010.61540.54410.48950.59610.46620.7692

0.62770.69560.4422

0.60000.51770.63160.44850.61910.5454

0.20000.6158

1962

0.49230.55210.07140.37210.50880.60000.63830.41260.62500.30770.50790.33060.19630.37810.54240.62740.47480.44000.51670.64290.50000.69550.74620.00000.43130.41380.62500.57140.57660.48780.56550.49660.38600.23300.60270.68570.44220.53690.62830.53330.62860.47760.61540.55810.64330.15280.5783

1963

0.46380.53570.05800.37210.51670.64000.63230.42620.57140.29850.51970.30530.24690.40000.49250.61480.48610.50000.51130.66670.52530.69360.73680.00000.42550.40000.64330.55650.56640.52630.58750.52500.30770.27230.59750.66360.43710.52290.62310.52070.53330.48220.60300.55810.63490.18180.5806

Page 44: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968 1969

0.48000.54240.04080.41350.51690.57040.65180.4074

0.45460.2632

0.55380.2963

0.23450.4436

0.51670.62070.47620.49180.48480.61390.49780.69200.71390.00000.42550.51150.63490.5412

0.58330.57140.56500.4949

0.14540.24620.57930.61020.42290.36530.62140.46560.40000.49380.61970.5714

0.65230.22340.5345

0.45060.52080.10400.43920.53730.60350.63180.4610

0.51610.3116

0.54820.2685

0.22190.4658

0.47060.58130.46120.46260.48620.64910.49190.65360.72120.00000.42820.52100.61460.5333

0.57970.50980.5213

0.11430.22100.55830.58820.35590.27450.66320.87480.48780.47060.60510.4673

0.61370.16670.6452

0.50000.5500

0.40000.55000.75000.80000.4500

0.60000.3000

0.55000.3000

0.20000.4500

0.50000.60000.55000.45000.60000.60000.50000.70000.75000.00000.45000.50000.60000.6000

0.50000.60000.5000

0.40000.25000.60000.70000.35000.32000.65000.45000.65000.50000.70000.6500

0.70000.25000.5500

0.50000.50000.10000.40000.50000.80000.80000.3000

0.3000

0.3000

0.4000

0.50000.60000.50000.40000.60000.00000.50000.70000.80000.00000.40000.40000.60000.6000

0.60000.60000.5000

0.10000.60000.70000.30000.40000.80000.40000.60000.50000.70000.6000

0.70000.30000.5000

0.00000.57000.16000.52000.60000.62000.62000.4300

0.5500

0.3700

0.27000.4500

0.50000.67000.50000.48000.53000.69000.54000.71000.82000.18000.45000.52000.64000.5600

0.62000.4800

0.33000.59000.75000.30000.35000.33000.84000.71000.68000.65000.5300

0.30000.5500

0.5200

0.16000.43000.57000.64000.58000.4200

0.4000

0.3600

*******0.4600

0.60000.47000.53000.50000.71000.50000.70000.85000.21000.49000.64000.64000.5300

0.56000.5300

0.27000.56000.68000.47000.45000.98000.36000.60000.62000.64000.4800

0.29000.6500

Page 45: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.5 Variance of the Long-Term Growth Forecasts

IndustryCode 1961 1962 1963

7 A.C.F. Industries, Inc.1 Addressograph-Multigraph (AM Corp.)8 Air Reduction Co. (B.O.C. Fin. Corp.)2 Allegheny Power System Inc.8 Allied Chemical Corp.3 Alcan Aluminum Ltd.3 Aluminum Company of America4 Amerada Pet. (Amerada Hess)5 American Cyanamid Co.2 American Electric Power Co.5 American Home Products Corp.8 Amer. Mach. & Foundry Co. (AMF Ind.)8 Amer. Nat. Gas Co. (Amer. Nat. Res.)3 Amer. Smelt. & Refin. (UV Ind.)8 American Telephone & Telegraph Co.8 American Tobacco (Amer. Brands, Inc.)3 Anaconda Co.3 Armco Steel Corp. (ARMCO Inc.)7 Armour & Co. (Esmark)4 Atlantic Richfield Co.8 Atlas Chem. Ind. Inc. (Imperial Ch.)2 Baltimore Gas & Electric Co.1 Beckman Instruments, Inc.8 Beneficial Finance Co.3 Bethlehem Steel Corp.7 Boeing Co.6 Borden Inc.2 Boston Edison Co.5 Bristol-Myers Co.1 Burroughs Corp.8 C.I.T. Financial Corp. (RCA Corp.)6 Campbell Soup Co.7 Caterpillar Tractor Co.2 Central & Southwest Corp.2 Cincinnati Gas & Electric Co.4 Cities Service Co.2 Cleveland Electric Illuminating Co.6 Colgate Palmolive Co.2 Consolidated Edison Co.2 Consumers Power Co.4 Continental Oil Co. (CONOCO)6 Corn Products Co. (CPC Intl. Inc.)8 Crown Zellerback1 Cutler-Hammer Inc. (Eaton Corp.)2 Dayton Power & Light Co.2 Detroit Edison Co.8 Dow Chemical2 Duquesne Light Co.

*******2.30941.4142*******

1.4142*******

2.75382.12132.00000.50001.15472.1213**************

0.5000**************

2.1213

*********************

2.30940.7071**************

0.0000*******

1.7321*******

1.73210.57740.70710.5774**************

1.1547**************

0.70712.08171.1547****************************

2.3805*******

2.51661.67331.52750.57741.00007.21115.67451.73211.50000.70711.50001.00001.00004.93290.66460.00002.88682.3805

1.41421.00002.08170.50001.47201.52754.35892.30940.57740.57741.21115.50761.34160.63251.87080.44720.57742.00000.95741.00000.25000.95741.50000.89442.08173.51190.57740.70711.52750.5774

2.00001.47201.60730.85392.16027.63226.30871.41420.81650.63251.09541.89301.03082.87230.75280.00003.30403.7815

0.95740.50002.00000.74162.58200.81655.06623.36650.57740.57741.38011.52751.64320.78681.58110.47560.00000.00000.50001.82570.54770.62911.34160.83672.06161.52750.57740.47871.41420.5000

Page 46: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968

1.1547 2.5166 ******* ******* *******1.2724 1.3973 4.3330 5.3330 6.25301.7078 0.8367 0.0000 4.5000 5.12000.8944 0.9747 0.0000 0.0000 0.00001.3571 1.4960 1.0000 2.3330 1.05301.5055 3.3116 4.3330 4.0000 62.10001.7895 2.8284 4.3330 2.3330 43.32003.9328 2.0736 0.5000 0.0000 14.05001.5626 1.3292 0.3333 0.3333 1.16300.5976 0.6232 0.0833 0.0833 0.10331.2247 1.4142 0.0000 1.0000 8.05301.1402 0.8367 0.5000 ******* *******1.0368 0.9832 0.2500 0.2500 0.12501.7440 1.2813 0.3333 5.3330 *******0.6346 0.4173 0.0000 0.3333 0.33331.0488 1.0488 0.0000 0.0000 *******1.7889 1.3663 4.5000 2.0000 81.92001.3784 1.7995 0.5000 0.5000 12.01002 2174 2 3805 ******* ******* *******3.2787 2.5565 1.3330 12.3300 29.08002.0817 5.0332 18.0000 ******* *******0.6268 0.6986 0.0833 0.5833 3.37003.4641 2.8284 13.0000 33.3300 25.72001.2374 1.0351 0.0000 0.5000 1.44501.3038 1.7440 0.5000 0.5000 41.41002.9496 1.2247 57.3300 21.0000 *******0.9832 1.5059 0.3333 1.0000 0.25330.2500 0.7416 0.2500 0.0000 0.00001.6690 1.7269 1.0000 1.3330 12.81002.5100 4.3205 78.1300 4.5000 91.13000.4082 0.5670 0.5000 0.1250 0.02000.7440 1.0690 0.5000 0.5000 5.78001.2817 1.2817 7.0000 21.000 19.20000.6667 0.5000 0.0000 0.0000 0.01330.2500 0.2236 0.0000 0.0000 6.12500.6708 1.0206 0.0833 1.3330 6.41300.6519 0.8010 0.0833 0.0833 5.26301.3571 1.2007 3.0830 5.2500 0.72000.9940 1.1073 0.3333 0.3333 0.96330.6646 0.6124 0.2500 0.0833 4.32002.7124 2.0863 0.0000 1.3330 4.20300.4880 0.7559 0.3333 0.3333 5.06302.3022 1.6330 2.3330 1.7500 1.75002.5100 2.8723 4.0000 9.3330 6.80300.2236 0.4916 0.1250 0.1250 6.48000.5701 0.9487 0.0833 0.0833 2.23001.4720 1.5119 2.3330 2.3330 9.67000.2887 0.2500 0.5000 0.5000 *******

Page 47: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.5 (continued)

IndustryCode

876822677166772888664268118227273173817336386851

Eastman Kodak Co.Ex-Cell-O Corp.Federated Dept Stores Inc.Firestone Tire & Rubber Co.Florida Power Corp.Florida Power & Light Co.Food Fair, Inc.Ford Motor Co.General Amer. Transp. Corp. (GATX)General Electric Co.General Foods Corp.General Mills Inc.General Motors Corp.General Portland Cement Co.General Public Utilities Corp.General Telephone & ElectronicsGoodrich (B.F.) Co.Goodyear Tire & Rubber Co.Grand Union Co. (Cavenham Ltd.)Great Atlantic & Pacific Tea Co.Gulf Oil Corp.Gulf States Utilities Co.Heinz (H. J.) Co.Hercules Inc.Hewlett Packard Co.Honeywell Inc.Household Finance Corp.Houston Ltg. & Pow. Co. (Hous. Inds.)Idaho Power Co.Ideal Cement (Ideal Basic Ind. Inc.)Illinois Power Co.Ingersoll-Rand Co.Inland Steel Co.International Business MachinesInternational Harvester Co.Intl. Nickel Co. Canada (INCO)International Paper Co.Intl. Telephone & Telegraph Corp.Johns-Manville Corp.Jones & Laug. Steel Corp. (LTV Corp.)Kaiser Aluminum & Chemical Corp.Kellogg Co.Kennecott Copper Corp.Kimberly-Clark Corp.Kroger Co.Liggett & Myers (Liggett Group)Lilly Eli Co.Litton Industries, Inc.

1961

0.8367

1.41420.57740.95741.2247

0.70710.81651.7078

0.0000

1.15470.81650.00000.57741.15470.86600.57741.52750.70713.36654.94971.7889

0.5000

1.00001.41421.52750.7071

2.51662.12132.82841.4142

0.35360.7071

2.82842.9861

1962

0.89442.64580.83670.50000.74161.11431.00001.41420.57741.58111.03283.21462.16791.73211.00001.37690.57741.41421.31501.48321.00000.50000.57741.97482.42211.21111.52750.83671.00002.08170.57740.57742.00001.87081.15473.96232.00004.34931.25835.19627.37111.29101.00000.97470.50001.52751.52752.7869

1963

1.06902.08171.03281.09540.54770.53451.00001.25830.57741.04880.83672.06161.30381.25830.00001.59691.89302.07361.15471.78191.14020.47870.00001.60472.58841.71821.25830.66461.00001.73210.44720.57742.16791.63300.85390.44722.06161.92351.25834.00007.11810.95741.89300.54771.81660.95742.49581.9518

Page 48: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968

0.6124 1.8708 1.3330 4.0000 68.40001.1402 1.2910 ******* ******* *******0.8345 0.7817 0.3333 1.0000 6.33300.8381 0.9449 7.0000 8.3330 29.80000.8092 0.8092 2.0000 2.0000 0.00000.7440 0.4629 0.5000 0.3333 0.65330.9574 0.8367 0.5000 2.0000 *******0.7528 1.3874 9.7500 ******* 0.50001.1127 1.3292 ******* ******* *******1.1160 1.4865 1.7500 1.7500 2.28000.7071 1.2019 0.3333 0.3333 0.41331.9235 1.3663 2.0000 2.0000 14.05000.9039 1.0000 7.5830 20.3300 4.17001.0000 2.0616 ******* 12.5000 *******0.3780 0.4880 0.1250 0.1250 0.04501.0836 1.1547 1.3330 1.3330 9.67001.3416 1.2649 6.2500 13.5800 7.63001.6421 1.5980 8.0830 8.3330 24.41001.4930 1.3038 0.5000 0.0000 72.00001.2649 0.9759 2.0000 0.0000 7.22001.2247 1.0329 0.1250 3.0000 52.68000.7583 0.8522 0.7500 0.5833 1.33001.7078 1.2583 1.2800 2.0000 *******0.8522 0.8165 2.3330 2.3330 3.21303.1091 3.1091 4.5000 4.3330 29.23003.2642 1.1260 1.3330 8.3330 14.17001.2374 1.1667 0.0000 0.1250 74.42000.6455 0.6124 0.7500 0.7500 0.57001.0000 0.6646 0.7500 0.5833 5.76300.8367 0.8944 ******* ******* *******0.7480 0.9063 0.5833 0.5833 1.47000.5000 0.8944 4.5000 ******* *******1.7559 1.7762 0.0000 0.0000 1.28001.2693 1.2693 0.0000 3.0000 2.20300.7416 1.6330 4.3330 4.3330 25.48001.1073 1.2488 6.3330 1.3330 0.90331.3292 1.3292 2.3330 2.3330 9.00301.6330 1.4639 1.0000 1.3330 2.47001.4832 1.0328 1.0000 0.3333 20.30000.5000 1.6253 5.3330 5.3330 20.48003.0605 3.1689 4.5000 18.0000 60.50000.8165 0.6325 0.0000 0.0000 7.60501.6583 1.8619 4.3330 16.0000 24.00001.0206 0.9940 2.2500 2.5830 2.58301.0206 0.7868 0.0000 0.5000 1.44501.2247 1.2247 ******* ******* *******1.6047 2.6882 3.1250 0.5000 18.00001.8077 1.8516 13.0000 13.0000 2.8130

Page 49: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.5 (continued)

IndustryCode

724885288161688322772527826538418886221338584686

Lockheed Aircraft Corp.Long Island Lighting Co.Marathon OilMcGraw Hill Inc.Mead CorporationMerck & CompanyMiddle South Utilities Inc.Minnesota Mining & Manufacturing Co.Moore Corp.Motorola, Inc.National Biscuit Co. (NABISCO)National Cash Register Co. (NCR)National Dairy Prods. (Kraft Inc.)National Distillers & Chemical Corp.National Lead Co. (NL Industries)National Steel Corp.New York State Electric & Gas Co.Niagara Mohawk Power Corp.No. Amer. Aviation (Rockwell Intl.)North Amer. Car Corp. (Flying Tiger)Northern States Power Co.Norwich Phar. Co. (Morton-Norwich)Oklahoma Gas & Electric Co.Otis Elevator Co. (United Tech.)Owens-Corning Fiberglass Corp.Pacific Gas & Electric Co.Penney (J.C.) Co., Inc.Pfizer (Chas & Co.) Inc.Phelps Dodge Corp.Philip Morris Inc.Phillips Petroleum Co.Pitney-Bowes, Inc.Pittsburg Plate Glass (PPG Ind.)Polaroid Corp.Prentice Hall Inc.Procter & Gamble Co.Public Service of ColoradoPublic Service Electric & Gas Co.Radio Corp. of America (RCA Corp.)Republic Steel Corp.Reynolds Metals Co.Reynolds (R.J.) Tob. Co. (Rey. Ind.)Richardson-Merrell Inc.Rohm/Haas Co.Royal Dutch Petroleum Co.Safeway Stores, Inc.Scott Paper Co.Sears, Roebuck & Co.

1961*******

**************

1.2910*******

1.14020.70711.92350.0000

*******1.41422.12130.0000

*******1.9149

****************************4.2426

*******0.9574

*******0.70712.16020.57740.70711.1547

**************0.00000.00001.00005.11863.53551.58110.00000.0000

*******3.5355

*******1.82573.4034

*******1.41420.95742.3094

1962

2.64580.57743.78591.36632.51661.78890.57742.09761.00002.08170.95742.33810.28871.52751.70784.72581.25830.81652.16024.85630.00001.22471.52750.50001.51660.50001.00001.41423.05510.57740.57741.51661.52756.49361.34161.22471.67331.15474.57353.60567.54431.52751.82572.40141.50001.04081.04881.0488

1963

1.50000.28872.21741.49603.16231.49600.22362.41031.50001.63301.81661.91490.25002.51661.79703.42481.154?0.47871.82571.50000.50001.82570.50001.43181.30380.89440.95740.69862.63000.00000.50001.67332.50006.86051.89741.11271.51660.57741.81664.85636.85571.25831.22472.58840.50000.89441.21111.0408

Page 50: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968

1.9235 3.6056 28.0000 6.3330 4.03000.4472 0.5477 0.2500 15.2500 0.50003.5835 3.1689 0.5833 4.3330 14.25000.9258 1.1650 9.3330 21.0000 36.60002.0966 1.9235 1.1250 0.5000 3.38001.5119 1.6159 1.3330 2.3330 68.21000.6455 0.6075 0.0833 0.0833 1.21301.5526 0.9161 3.1250 2.5830 4.50000.5477 0.5477 1.0000 0.5000 *******1.3801 2.7484 9.3330 28.0000 17.76001.1339 1.1339 2.3330 1.0000 0.26332.1667 1.6915 4.3330 9.0000 12.65000.7559 0.7569 0.3333 0.3333 2.80301.5000 1.6432 2.3330 1.3330 *******1.3801 0.7638 0.5000 8.0000 27.38001.2450 1.8371 2.0000 2.3330 15.08001.0000 1.0000 ******* ******* *******0.7583 0.5164 0.0833 0.0833 0.00331.6432 1.7464 1.3330 ******* *******2.7080 2.4495 ******* ******* *******0.4472 0.4183 0.1250 0.1250 *******0.8367 0.4472 0.0000 0.5000 6.88501.0954 1.0328 0.0833 0.0833 0.50001 3038 1 8166 ******* ******* ************** 1 2 ? 2 4 2 0 0 0 0 0 5 0 0 0 26.65000.5000 0.5345 0.3333 0.3333 3.00001.6938 1.1476 0.1250 0.0000 6.81300.5271 0.7817 0.3333 3.0000 1.33301.2813 0.6646 0.3333 14.3300 22.23000.5774 1.3038 3.1250 ******* *******1.0746 1.1495 0.2500 6.3330 3.80300.9174 0.9174 9.0000 9.3330 10.92002.1679 1.7889 4.5000 4.5000 80.65006.0553 7.0071 84.5000 16.3300 *******1.7889 1.6733 4.5000 0.0000 73.20001.0351 0.9613 1.0830 0.2500 1.80500.4880 0.5000 0.0000 0.0000 1.62000.6124 0.6124 0.5833 0.5833 0.08333.1411 1.7224 4.3330 4.0000 82.03000.8367 1.5055 2.3330 ******* *******3.2326 2.5642 9.0000 9.3330 75.73000.8165 0.9832 0.3333 0.5000 *******0.5164 1.2150 2.0000 0.5000 0.32001.5736 1.8127 8.0000 ******* 15.13000.5477 0.8165 1.3330 2.3330 7.45301.3663 0.5774 0.1250 0.5000 0.98001.2247 1.0000 1.3330 0.0833 1.72001.0000 1.1304 0.3333 3.0000 4.8530

Page 51: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

Table 1.A.5 (continued)

IndustryCode

485422144457824812847783521211

Shell Oil Co.Singer Co.Smith Kline & French (Smithkline)Socony (Mobil Oil Corp.)Southern Co.Southwestern Public Service Co.Sperry Rand Corp.Standard Oil Co. of CaliforniaStandard Oil Co. of IndianaStandard Oil of N.J. (Exxon)Sterling Drug Inc.Swift & Co. (Esmark)Talcott Nat. (Assoc. Fst. Cap. Corp.)Tampa Electric Co.Texaco Inc.Texas Gulf Sulphur Co. Inc.Texas Instruments, Inc.Texas Utilities Co.Union Carbide Corp.Union Oil Co. of CaliforniaUnited Aircraft Corp. (United Tech.)U. S. Gypsum Co.U. S. Rubber (Uniroyal, Inc.)U. S. Steel Corp.Upjohn Inc.Virginia Electric & Power Co.Westinghouse Electric Corp.Wisconsin Electric Power Co.Xerox Corp.Zenith Radio Corp.

1961

0.5774*******

1.6733

0.9574

*******0.70710.70712.51660.0000

1.91490.70711.1547

3.55901.00001.9149

0.00000.70711.52751.30380.57740.0000

0.0000

1962

0.50002.06161.03282.30940.54770.47873.21461.73210.57741.58110.57740.70711.26490.62910.83671.73213.34660.74161.30382.51667.57191.70780.70711.52752.48330.70714.92440.00006.40831.4142

1963

0.44720.57741.60360.95740.54770.47873.30400.50002.30941.30382.08170.57740.83670.25001.14021.52753.26600.65190.89440.57744.08251.71760.57743.46412.49760.49161.92350.57743.99402.2174

Page 52: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast

1964 1965 1966 1967 1968

1.6890 1.3999 1.3330 0.3333 8.25301.5166 0.5477 1.3330 8.0000 2.42001.2247 1.3025 0.0833 3.5830 1.00301.0488 1.4100 0.5833 2.2500 4.01300.7559 0.3720 1.3330 0.0833 0.26330.7583 0.6646 1.1250 1.1250 19.85000.8367 1.3229 2.0000 2.0000 *******1.6036 1.2488 0.2500 1.0830 4.05301.3048 0.9449 0.2500 4.0000 11.26001.5222 1.2660 0.0000 1.0830 4.05301.6021 1.1726 4.0830 4.3330 6.33302.0616 2.5166 ******* ******* *******2.7928 1.1547 2.0000 0.1250 *******0.4472 0.4916 0.5000 0.5000 2.42001.4142 0.9797 1.0830 0.2500 1.3330

22.5000 23.9730 84.5000 ******* *******2.0310 2.1381 12.0000 6.3330 38.45000.8010 0.6646 0.0833 0.0833 0.50331.3844 1.2360 0.2500 0.2500 1.16303.0923 3.2146 0.3333 4.0000 *******3.0332 0.8944 52.0000 21.0000 96.58000.7039 0.7868 1.3330 6.3330 0.24501.7500 1.8166 3.1250 10.1300 *******1.3292 1.6021 1.3330 1.3330 8.05301.6850 1.7043 6.3330 0.0000 0.12000.4859 0.4410 0.3333 0.3333 0.26331.5166 2.3664 5.3330 7.0000 66.56000.5774 0.4787 ******* 12.5000 *******3.3991 4.7170 6.3330 6.3330 *******1.4720 3.2094 4.3330 4.0000 28.6500

Page 53: Nature and Sources of Data · Nature and Sources of Data 1.2 The Participating Security Analysts and the Company Sample The major task of professional security analysts is to forecast