Determinants of performance for growth mutual funds

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Authors Basist, Robert, 1927-

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DETERMINANTS OF PERFORMANCE FOR GROWTH MUTUAL FUNDS

. by .Robert Basist

A Thesis Submitted to the Faculty of theDEPARTMENT OF FINANCE, INSURANCE, AND

REAL ESTATEIn Partial Fulfillment of the Requirements

For the Degree ofMASTER OF SCIENCE

WITH A MAJOR IN FINANCEIn the Graduate College

THE UNIVERSITY OF ARIZONA

1 9 7 1

STATEMENT BY AUTHOR

This thesis has been submitted in partial fulfill­ment of requirements for an advanced degree at The University of Arizona and is deposited in the University Library to be made available to borrowers under rules of the Library.

Brief quotations from this thesis are allowable without special permission, provided that accurate acknowl­edgment of source is made. Requests for permission for ex­tended quotation from or reproduction of this manuscript in whole or in part may be granted by the copyright holder.

SIGNED:

APPROVAL BY THESIS DIRECTOR This thesis has been approved on the date shown below:

alter K. Kirk ~T DateProfessor of Finance, Insurance,

and Real Estate

COPYRIGHTEDBY

ROBERT BASIST 1971

ACKNOWLEDGMENTS

I should like to express my sincere gratitude to Dr. Walter K. Kirk for his advice, encouragement, and con­structive criticism during the writing of this thesis. I am also grateful to Dr. James E. Wert for arranging computer programming assistance. Dr. John T. Emery and Dr. Jean E. Draper for their ideas on quantitative analysis. Special thanks are due Dr. Richard W. Hansen for his advice regard- , ipg thp ..questionnaire, Mr. Ronald W.. Chorba for his computer programming assistance, Mrs. Josephine A. Engle for her as­sistance with the mailing of the questionnaire, and Mrs.Ruth D. Shuping for typing the final copy of the thesis.

In addition, my heartfelt thanks go to my wife, Rita, who supported my decision to return to academic life, kept the children quiet, and assisted me with the tabulating of replies to the questionnaire and the typing of the drafts of the thesis.

TABLE OF CONTENTS

PageLIST OF TABLES . . , - . / . . . . . . . . . . . ixABSTRACT ... •. . . . . . . . •.......... xi

I. INTRODUCTION . . . ... . .. . . ' 1Purpose of the Paper . . . . . . . o . . , 1Background and Review of Literature . . . 1Guide to the P a p e r ............... 5

II. METHODOLOGY . . . . . . . . . . . . . . . . . 7Statistical Definitions . .•. . . . . . . 7Data . 8Statistical Methods . . . . . . . . . . . 9

. ..j?03r JQSlsLel • .♦ . * » o . e © . 9Null Hypothesis . . . . . . . ............ 10Chi-Square Test. ......................... 11Computer Processing . . . . . . . . . . . 12Limitations of the S t u d y ............ 12

III. THE DEPENDENT VARIABLE - PERFORMANCE .. . . . . 18Over-emphasis . . . . . . . . . . . . . . 18Measurement . . . . . . . . . . 19Comparison with Market Averages ......... 20Risk . . . . . . . . . . . . . . . . . . . 20

IV. THE INDEPENDENT VARIABLES ................. 23Co-movement with Market Averages . . . . . 23Asset Size . . . . . . . . . . . . . . . . 24New Money . .......... . . ........ 26

The Positive S i d e ........ .. 26The Negative Side ........ 28

Incentive Fees . . . . . . . . . 29No-Load Funds . . . . . . . . . . . . . . 31Stock Manipulation, Shortage and

Turnover . . . . . . . . . . . . . . . . 31

" v

viTABLE OF CONTENTS— Continued

. ' •PageManipulation............ ............ 31Stock Shortage.............. . 34Stock Turnover . „ 35

V. EMPIRICAL RESULTS . . . . . . . . . . . . . . . 37General . . . . . . . . . . . . 37Evaluation of Liquidity of Mutual Funds

Two "Down" Years, 1966, 1969 . . . . . . 39Evaluation of "Dow Jones Earnings,"'

Three "Up" Years, 1965, 1967, 1968 . . . 41Evaluation of Low Expense Ratio,

Three "Up" Years, 1965, 1967, 1968 .... 43• Evaluation of "Concentrating Funds in

the Blue Chip Stocks," Three "Up"'Years, 1965, 1967, 1968 . . . . . . . . 45

Evaluation of "Positive Cash Flow IntoFund"' Five Years, . 1965-1969 ...... .... 47

Evaluation of Two Most Important Factors— Singularly Five Years,'1965-19'69, Three '"Up" Years , 1965,1967, 1968; Two. "Down" Years, 1966, 1969 49

Evaluation of Two Most Important Factors—Factors Considered in Combintation Five Years, 1965-1969; Three ""Up" Years,1965, 1967, 1968; Two "Down" Years,1966, 1969 . . . . . . . . . . . . . . . 56

Evaluation of "'Percent New Cash"Three "Up" Years, 1965, 1967, 1968 . . . 59

Evaluation of "Date Shares Offered"Three "Up"' Years, 1965, 1967, 1968 . . . 61

Evaluation of "Load Versus No-Load Funds™Three "Up" Years, 1965, 1967, 1968 . . . 63

VI. SUMMARY AND CONCLUSIONS ............. 65Suggested Areas for Future Study . . . . . 67

APPENDIX A: QUESTIONNAIRE AND COVER LETTER . 69APPENDIX B: CLASSIFICATION OF INDEPENDENT

VARIABLES . . . . . . . . . . . . 72APPENDIX C: COMPLETE LISTING OF FUNDS

COVERED IN THE STUDY . . 73

V l l

TABLE OF CONTENTS— ContinuedPage

APPENDIX D; EXTRACT FROM CHI-SQUARE VALUEST A B L E ....................... . . 76

APPENDIX E: MASTER RESPONSE TABLE, RECAP OF :COMPUTED CHI-SQUARE VALUES . . 77

APPENDIX F: DATA PROCESSING CODING SHEETAND NUMBER OF FUNDS IN EACH CLASSIFICATION 80

APPENDIX G: MAIN DATA CARD FORMAT . . . . . . 81.APPENDIX Ht MASTER CODE LISTING - DESCRIPTION

OF DEPENDENT AND INDEPENDENT VARIABLES .......... 82

APPENDIX I: MASTER RESPONSE TABLE— RECAP OFREPLIES TO QUESTIONNAIRE . . . . 86

APPENDIX J; MASTER RESPONSE TABLE— PERFORMANCE MEAN, MEDIAN AND NUMBER OF FUNDS BY INDEPENDENT FACTOR AND CLASS . ■ 89

APPENDIX K: PERFORMANCE TABLE BY THIRDS FORALL PERIODS . . . . . . . . . . . 94

APPENDIX L: COMPUTER RUN - FUND PERFORMANCEAND RANK . . . . . . . . . . . . 96

APPENDIX M: COMPUTER RUN - LIQUIDITY OF MUTUALFUNDS, TWO "DOWN"' YEARS (B-6) . . 103

APPENDIX N: COMPUTER RUN - DOW JONES EARNINGSTHREE “UP" YEARS (B-9) . . . . . 105

APPENDIX 0: COMPUTER RUN - LOW EXPENSE RATIOFOR THE FUND, THREE “UP,r YEARS (C-2) 107

APPENDIX P: COMPUTER RUN - CONCENTRATINGFUNDS IN THE BLUE CHIP STOCKS (C-9) . . . . . . . . . . . . . . 109

APPENDIX Q: COMPUTER RUN - POSITIVE CASH FLOWINTO FUND, FIVE YEARS (C-13) . . Ill

V l l l

APPENDIX R: COMPUTER RUN - TWO MOST IMPORTANTFACTORS - SINGULARLY, COMPUTER CODE NO. 39 . . . . . . . . . . . 113

APPENDIX S: COMPUTER RUN - TWO MOST IMPORTANTFACTORS - COMBINATION SAMPLE FOR 3 "UP" YEARS . . . . . . . . . . . 117

APPENDIX T: COMPUTER RUN - PERCENT NEW CASH,THREE "UP"' YEARS, COMPUTER CODENO. 52 . . . . . . . . . . . . . 121

APPENDIX U: COMPUTER RUN - DATE SHARESOFFERED, THREE "UP" YEARS,COMPUTER CODE NO. 6 . . . . . . . 123

APPENDIX V: COMPUTER RUN - LOAD VERSUSNO-LOAD FUNDS, FIVE YEARS,COMPUTER CODE NO. 7 . . . . . . . 125

REFERENCES 127

LIST OF TABLES

Table Page1. ' Probabilities of Gain in Value of Common

Stocks Since 1870 Based on the Standard and Poor's 500 Index of IndustrialStock Prices .. . . . o <, . «, » o . » . . , 3

2. Annual Performance Results of Funds(1962-1969) 21

3. Accumulative Performance Five Year TimePeriods (1962-1969).......... . . . . 21

4. Growth Mutual Fund Performance with CapitalGains Reinvested Plus Income DividendsReceived in Cash . . . . . . . . . . . . . . 27

. .. 5. -*N-et '»l>s*s.uanC'e-»a?nd-'Met ‘PurGha*s*es -of Equities . . 356. Comparison of 69 Growth Mutual Funds with

Standard & Poor's 425 387. Two "Down" Years, 1966, 1969: Liquidity of

Mutual Funds . . . . . . . . . . . . . . . . 408. Three "Up"' Years, 1965, 1967, 1968:

Dow Jones Earnings . . . . . . . . . . . . . 429. Low Expense Ratio for the Fund;

Three '"Up'" Years, 1965, 1967, 1968 ........ 4410. Three "Up"5 Years, 1965, 1967, 1968:

Concentrating Funds in the Blue Chip Stocks 4611. Five Years 1965-1969: Positive Cash Flow

Into Fund . . . . . . . . . . . . . . . . . 4812. Most Important Two Factors: Expected and

Observed Frequency . . . . . . . . . . . . . 5113. Most Important Two Factors: Performance

. by Factor . . . . . . . . . . . . . . . . . 53ix

LIST OF TABLES--Continued Table Page14, Two Most Important Factors—

Factors Considered in Combination 5715, Three "Up"' Years, 1965, 1967, 1968:

Percent New C a s h ....... 6016, Three "Up"' Years, 1965, 19 67, 1968:

Date Shares Offered 6217, Three "Up"1 Years, 1965, 1967, 1968:

Load Versus No-Load Funds . . . . . . . . . . 64

ABSTRACT

The study analyzed factors that may have influenced the medium term performance of growth mutual funds for the five year period of 1965-1969. The author reviewed relevant literature, then evaluated published facts and 69 replies to a mailed questionnaire.

The statistical analysis used in the study covered the chi-square test, arithmetic mean, standard deviation, coefficient of variation, median, range, quartile deviation, and geometric mean. Growth mutual fund performance (not ad­justed for risk) as measured by the geometric mean of yearly growth was the dependent variable for the chi-square tests. The 34 independent variables were chosen on a, priori basis.A separate computer analysis was completed for the full five years, one for the three "up" years, and another for the two "down" years.

The null hypothesis states that there is no statisti­cally significant relationship between the performance of growth mutual funds and its procedures, policies and inher­ent characteristics. The null hypothesis was accepted in 94 instances and rejected in eight cases.

CHAPTER I

INTRODUCTION

Purpose of the PaperThe purpose of this paper is to attempt to ascertain

the determinants of performance for growth mutual funds.^The study was based on 69 growth mutual funds operating from 1965 through 1969.

Background and Review of LiteratureIt is generally assumed within the mutual fund indus­

try that medium and long term performance results of a growth mutual fund depends on the following:

1. Objectives, policies and investment techniques employed by the investment advisors.

2. The general movement of the stock market.3. Outside environmental factors, such as the per­

centage of new money to assets invested in the mutual fund and legislation limiting investment action, etc.

1. A growth mutual fund is a company that special­izes in investing the money of its shareholders in the secu­rities of many companies, with the objective of maximizing long term growth of capital, as contrasted to maximizing dividend and interest income. For this study, the final de­termination of whether a mutual fund was a growth fund was based on Wiesenberger (Supplement, 6/30/70) and Lipper (Supplement, 10/8/70) .

1

24. Probability— the longer the time period the

greater the chance of gain. For example (Table 1), for the 95 five year investment periods since 1870, there were 68 periods of gain in value and 27 periods of loss of value, or a 72% chance of gain in value as measured by Standard and Poor's index of industrial stocks (Brevits 1970).

Perhaps the most comprehensive study of all aspects of the mutual fund industry was prepared for the Securities and Exchange Commission (Wharton School of Finance and Com­merce, 1962, pp. xi, xiii., 18, 19, 20, 31, 32). While this study did not cover the period of 1965 through 1969, many of the conclusions regarding performance are pertinent to thisz - - ' 'report. Erere are some of' the ma j or f indings:

". . . no relationship was found between performance and the amount of the management fee or the amount of the sales charge."

" . . . there is a significant positive correlation between the size of the sales charge and the rate of inflow of new money into the individual funds."

"Performance records, unadjusted for portfolio compo­sition, of the smaller funds were somewhat inferior to those of the other funds, but these differences can again be largely explained by differences in portfolio structure."

"The analysis revealed no strong relationship between turnover rates and performance, either when the variables

3TABLE 1

PROBABILITIES OF GAIN IN VALUE OF COMMON STOCKS SINCE 1870 BASED ON THE STANDARD AND POOR'S

500 INDEX OF INDUSTRIAL STOCK PRICES

Length of Investment

PeriodNumber of Periods

Since 1870Periods of Gain in Value

Periods of Loss in Value

Periods of No Change in Value

Chance of Gain in Value

30 years 70 0 0 100%20 years 80 76 4 0 95%10 years 90 77 13 0 86%5 years 95 68 27 0 72%1 year 99 58 40 1 - 59%

' Were ' exairvirmtl "for' the 'same 'tlm'e period or when performance lagged one year behind turnover.11

If investors are conscious of the performance rec­ords of the various funds, they might be expected to direct their purchases toward the funds that have been the most successful. If this be the case, there should be a positive relationship between perfor­mance in one period and net inflow in a later pe­riod. Annual, figures, with inflow lagged one year behind performance, do reveal a weak positive pat­tern among the common stock funds but no relation­ship among the balanced funds. Cumulative figures for the entire five and three quarter years show a strong positive pattern.

A priori it has been argued that shareholders (i.e., of larger size funds) benefit from increased diversification or risk and the ability of the advisor to afford more substantial facilities and able per­sonnel ; but it has been pointed out on the other side that small or moderate sized portfolios con­tribute to the flexibility of portfolio adjustments in the light of changing circumstances. Since nei­ther average performance nor variability of

performance has been significantly related to size of fund, neither of these considerations appear to have been decisive.

Another recent definitive study covering the mutual fund industry (Friend, Blume and Crockett 1970) found that for the period 1960-1968, fund size, sales charges, manage­ment expenses, portfolio turnover, and investment objectives showed no consistent relationship with investment performance properly adjusted for risk. One mutual fund research direc­tor (Fortune 1968) supported these findings when he stated categorically that he saw most of the studies and not one shows that any factor has any predictable effect on perfor­mance.

?- - -A. “le-ad-ing - 'Spokesma'n ‘'f-or •- -the indus try - (Bogle, Funds cope, 197.0a) found that performance of funds as a group in relation to the market can be predicted. He reported that the balanced funds go up and down on the ratio of about seven-tenths as much as the market, and the aggressive growth funds do the same on the basis of about 1.3 or 1.4 times the market.

In an article (Business Week September 13, 1969) con­cerning the Arthur Lipper Corporation> a financial writer tells of a study called Portfolio Performance Perspective to evaluate mutual funds, and to assess individual portfolio managers. The study will measure quality of portfolio hold­ings against their liquidity and scrutinizes turnover ratios.

To evaluate the reasons why one growth mutual fund performs better than another involves an analysis of the

decision-making process within the investment management firm, its operating practices and external factors such as asset size. The decision-making process or investment frame­work of a portfolio manager may include a review of the strength of the economy and the stock market itself and a fundamental and/or a technical analysis of the industry and the individual company. In the general area related to the economy and the stock market, eight factors were evaluated (Appendices A and B). Since the area of general operating practices and conditions of growth mutual funds has not been thoroughly investigated to date, it was decided that the re­port should concentrate on this aspect— 26 factors were eval­uated. In view of the many thousands of reports and books covering individual stock and industry selection, this report will not review this general area.

Guide to the Paper The paper is divided into six chapters.Chapter I, introduction. This portion of the paper

outlines the purposes of the study and reviews past litera­ture concerning performance of growth mutual funds.

Chapter II, Methodology. This section opens with statistical definitions, then discusses the statistical tests, hypothesis and the questionnaire. The section concludes with an analysis of the statistical shortcomings.

Chapter III, Dependent Variable-Performance. This chapter reviews the background of performance and the factors that may be related to performance«

Chapter IV, The Independent Variables. This chapter examines six independent variables, including the two found to have a significant relationship with performance.

Chapter V, Empirical Results. This chapter presents the major statistical findings of chi-square and performance median for all three periods.

Chapter VI, Conclusions and Recommendations. This chapter analyzes the results of the statistical tests, sum­marizes the conclusions and advances a number of recommenda- tions for 'future studies.

CHAPTER IT

METHODOLOGY

Statistical DefinitionsStandard Deviation; Square, root of the sum of the

squared deviations from the arithmetic mean, divided by the number of items. The standard deviation is a measure of dispersion.

Coefficient of Variation: The standard deviation di­vided by arithmetic mean, expressed as a percentage. It mea-s.unes ...relative, dispersion and is used ..when ..making comparisons.

thGeometric Mean: The n root of the.product of num­bers . The geometric mean is regarded as a better measure of relative price change performance than the "arithmetic mean," which is the sum of the items divided by their number.Briefly, it is felt the geometric mean.is the most descrip­tive representation of compound cumulative returns over time.

Median: The middle point of a distribution when ar­ranged in order of magnitude. Half the distribution is found above the median and the other half is found below. The me­dian is considered a better measure of central tendency if the distribution is skewed.

7

: 8Quartile Deviation: Another measure of dispersion

of a distribution. It is one-half the distance between the first quartile and the third quartile.

Null Hypothesis; A proposition stated in a negative form. A general statement of the null hypothesis is that there is no significant difference between two statistical measures, for example, observed and expected frequencies. If the null hypothesis is true, any difference between the two statistical measures is due to chance.

DataThe listing of all operating growth funds was obtained

from Wiesenberger (1970) and Lipper (1970) supplements to their guides. The Mutual Fund Guide (Fundscope April 1970) listed the year when the fund first began offering shares.If the offering date was prior to 1965, a questionnaire and covering letter (Appendix A) were mailed on October 26, 1970. If a reply was not received by November 9, 1970, a follow-up letter was sent. A total of 124 questionnaires were mailed, with 69 replies received (56%) (Appendix C). Yearly perfor­mance figures, including all distributions, ware obtained from the Fundscope (April 1970) while the five year total perfor­mance figures, with dividends added at the end of the five years, were secured from Investment Companies 1970 (Wiesen­berger 1971).

„ , ' ' 9The selected five year time span of 1965 through 1969

encompasses three "up" years and two "down" years. For anal­ysis , in addition to the five year period taken as a whole, the performance for the three "up" years and the two "down" years are analyzed separately.

Information on asset values, load or no-load, and in­centive fees, were secured from Fundscope (April 1970).

Statistical MethodsThe statistical measures utilized in this study are:

(1) Chi-Square independence test, (2) Arithmetic Mean, (3) Standard Deviation, (4) Coefficient of Variation, (5) Median, (6) Range, (7) Quartile Deviation, (8) Geometric Mean, and (9) Percentages. "

The geometric average to measure growth mutual fund performance does assume the automatic reinvestment of all capital gains and dividend distributions and has the advan­tage of placing all funds on the same comparative basis, re­gardless of how much or when they distribute their capital gains and dividends. In short, while the geometric average has shortcomings, it may be the best method available to com­pare performance of one growth mutual fund with another.

FormulaThe generally accepted method of measuring a fund's

performance is to compare the net asset value at the end of the year, including any dividends and capital gains

10distributions with the net asset value at the beginning of the year. In terms of a formula (Cohen and Zinbarg 1967, p. 631):

N.A.V. Dec. 31 + Dividends Formula #1-------------- h------------L _ iN.A.V. Dec. 31, t _1

For a period longer than a year (Badger 1969, p. 584) performance can be computed by multiplying the yearly results (Formula #1) to produce a chain index. For example, two suc­cessive years of 10% and 20% followed by a year of a net loss of 10% would become 1.10 x 1.20 x .90 = 1.18 (slightly less than 6% annually compounded). He recommended the compound interest assumption for intercompany comparisons whenever the annual rates vary widely or include a year of negative return.

Null HypothesisThe null hypothesis was established as follows: There

is no statistically significant relationship between the per­formance of a growth mutual fund and its procedures, policies, and inherent characteristics. The validity of the null hy­pothesis was judged at the .05 level of significance.^

1. At the .05 level of significance, there is a 5% probability that the null hypothesis is rejected when it should have been accepted.

11Chi-Square Test

The chi-square test of independence has been used to test the null hypothesis. The formula for computing chi- square is (Mason 1970, p. 102):

x2 = £ (Fo ~ F e ) 2where = sum of

fo = observed or actual resultsfe = expected frequency Formula #2x2 = chi-square value

By using the chi-square formula and by referring to standard published tables (Appendix D) it was determined with a certain degree of confidence, whether the difference in the actual results (observed frequency) from expected results could have occurred as a result of random sample variations (pure chance). If the computed chi-square.value is larger than the value shown in the table the null hypothesis is re­jected (hypothesis is not true) and it was concluded with a 95% degree of confidence that there is a correlation (not necessarily causal) between the dependent variable (perfor­mance of the growth mutual fund) and the independent variable (Sharpe 1970, p. 40).

The original tests classified performance (the depen­dent variable) into quartiles. However, it is recommended for a chi-square analysis to have a minimum of five cells with five or more expected frequencies in each cell and to consistently partition the dependent variable. Therefore, it was found necessary to divide the dependent variables into

12three classes rather than four. A chi-square test was run for each independent variable (Appendix E).

Computer Processing Data for the study was secured from results of a

mailed questionnaire (Appendix A) and statistics published in such publications as Wiesenberger's Investment Companies

X

and Fundscope _(Wiesenberger 1970; Fundscope April 1970). The inputs to the program consisted of two sets of 69 data cards, each containing information about one fund (Appendices F and G). After reading all the data, the growth mutual funds were sep­arated into thirds by performance.

For those determinants that had a fixed number of responses, such as yes, no, very important, somewhat impor­tant, not important, the chi-square test for independence was used in addition to the generally accepted parametric and non­par ametric statistical tests of central tendency. Those de­terminants that had no specific set of responses such as average fund assets, or annual percent of new cash, etc., were handled by grouping. Consideration was given to the num­ber of responses, generally accepted industry practices, and the limitations of chi-square analysis.

Limitations of the Study1. While the date that the investment advisor started

managing the growth mutual fund appears on the completed

13questionnaires, if the date were fewer than five years it was not used to reduce the performance period.

2. The percentage figure for new cash for each fundis at best an estimate. A more accurate figure could be ob­tained by basing the percentage of new money figures on an annual basis rather than on the beginning and ending values.By adjusting the 1965 asset value to reflect performance gains, the partially tentative, assumptions were made that:

a. realized capital gains and dividends were not distributed (Casey 1969, p. 7).

b . the asset base remained constant.3. The determination as to whether a fund was con-

-*si-dered- -a * •growth -fund -was—ba-s»ed entirely on -w i es-enbe r g e r (Sup­plement 6/30/70) and Lipper (Supplement 10/8/70) reports. There­fore, there may be funds included in the growth fund category which were not growth funds for the full five year period.

Over the years there have been a number of attempts to segregate growth- mutual funds into narrower classifications, depending on past investment policies and objectives of the management (Leuthold 1971, pp. 9, 22). In the judgment of the editors of Wiesenberger1s Investment Companies (Wiesen- berger 1968, p. 114) groupings are somewhat arbitrary. The editors of Forbes magazine in their annual Mutual Fund issue (Forbes 1970, pp. 51-68) separated stock funds from balanced funds but did not classify stock funds into separate group­ings based on volatility, objectives, or characteristics.

■ ■ • 14Considering these facts it was decided to have only one group ing covering all growth mutual funds„

4. Some of the fund managers' replies to the ques­tionnaire may be only their estimates or educated guesses as to how they operated (or should have operated) for the five year period.

5. Although the responses to the questionnaire far exceeded original estimates, those fund managers who did notcomplete the questionnaire may have had a reason not to re­spond, such as poor performance, or a desire not to reveal their superior ideas, etc.

6. In view of the great difficulty in combining stan dafd market averages covering the New York Stock Exchange and the American Stock Exchange, and the fact that percentage changes of most market averages over a medium and long term period are reasonably close (Wiesenberger 1968, p..411), a decision to use one of the more comprehensive averages. The Standard and Poor's 425 was made.

7. Many of the determinants may have a strong corre­lation with each other in addition to the dependent variable. For example, the fact that a growth mutual fund is a no-load fund may relate to the flow of new cash, asset size and ex­pense ratio. The statistical analysis did not separate this co-variation of independent variables.

8. Making comparisons of growth mutual funds with any unmanaged popular market average, considering that the

15growth mutual fund has an investment objective, while the market average does not, is somewhat unrealistic. Further,- the market averages do not take into account the expenses of managing and operating a growth mutual fund or the necessity for the fund management to keep a portion of the funds in "near cash" to cover redemptions, which 'may not contribute to. superior performance (Brady 1968, p. 5).

9. It would seem that in the professions there aremany keys to successful performance. For example, sound judgment, keen intelligence, superior knowledge and hard work and organization of management, are essential.

In the opinion of Charles Ellis (1968, p. .45) thedifference in performance of one mutual "fund over another maybe due to internal management organization. It is his judg­ment that to secure maximum staff performance it is essential to properly organize management procedures. While his arti­cle did not attempt to demonstrate any statistical correla­tion, it is his opinion that a competent portfolio manager has important advantages over a committee type organization. Unfortunately, it is difficult, if not impossible, to accu­rately measure these management factors for the purpose of running any meaningful statistical studies.

10. a. Length of Period. The determination of mean­ingful time span is difficult. In an article in Barron's (Leuthold 1971, p. 13), the author states that a meaningful time span is basic when viewing past performance. He makes

16the point that selecting a mutual fund based on a one year record or for only a bull or bear market period is not proper. If the past performance of a growth mutual fund is useful at all to judge future performance, it would seem that the longer the period covered the more functional the figure.This view is supported by one writer (Murray 1965, p. 61), who suggested that only the long term filters out the distor­tions and permits a proper assessment of the performance of a fundi

b. Is Period Representative. To secure the largest possible sample of growth mutual funds, it was arbitrarily de­cided to select the 1965-1969 five year period. This period included three "up" years and two "down" years and may not represent other five year periods, past or future. For exam­ple, the period selected included wide market fluctuations, heavy market volume, and large sums of new money invested in mutual funds which may have given the growth mutual funds the opportunities for superior performance (Barnes 1965, p. 65).

c. Specific Dates. A review of the records of growth mutual funds indicates that total performance in addition to other factors is influenced by the beginning and ending dates for the period. For the typical fund the high-low performance range of 1.7 for all five year periods over the past 21 years ending December 31, 1969 is extremely wide (Fundscope May 1970, p. 40).

17In short, regardless of how rigid or thorough the

analysis of this past performance data is, the findings apply only to the specific period investigated and there is no im­plication that the results of the study should be interpreted to cover or anticipate other periods of operation (Bogle, Financial Analysts Journal, 1970b).

CHAPTER III

THE DEPENDENT VARIABLE - PERFORMANCE (APPENDIX H)

Over-emphasis Many in the industry feel that the over-emphasis on

performance should be blamed on the Wharton School study\

(1962) which concluded that the typical mutual; fund was doing no better than the Dow Jones Industrial average. The fund managers at the time replied that the purpose of a mutual fund was to provide diversification and safety and growth commen­surate with the economy and not to take on the extra risks of trying to out perform the market averages.

Over the past five years, the cult of beating the market averages did get out of hand (Smith 1968). However, prior to the advent of the over-reaching for performance, many of the growth mutual fund managers methodically placed their customers' money into the blue chip stocks with very little effort on their part to secure superior performance. Perhaps in the 19701s a sense of proportion will permeate the industry and there will be less attempts to try to predict short term market moves (Fundscope October 1970).

19Measurement .

The dependent variable of performance over time may be calculated in many different ways. The generally ac­cepted method for measuring mutual fund performance (P) for a one year period is (Wharton School 1962) :

NAt+1+DI+DC Formula #3■ NAt

= Net assets per share at close of periodNA . = Net assets per share at beginning of periodDI = Dividends per share from investment income

during periodDC = Distribution per share from profits realized

in sale of securities during periodFor a time series (multiplying annual performance

..figures), a ..number of ..questions arise.., such as:1. Should either or both realized income and capital

dividends be compounded at the end of each yearly or quarterly time period?' . ‘

2. Is the mean performance a superior method forcalculating a measure of central tendency?

3. Should the base (numerator) be the beginning, ending or average net asset value?

An analysis of most methods of calculating the per­formance of a growth mutual fund, while interesting, probably would not materially change the conclusions of this study. Therefore, an arbitrary decision was made to measure "manage­ment performance" which shows what management did with the money available and does deduct the management fee and any

20

incentive fees from yearly performance« Calculations were based on the generally accepted method (Formula #3) for com­puting yearly performance with the time series calculated by multiplying yearly performance, including all cash dividend distributions added back at the end of each year.

The performance of the Standard and Poor's 425 was ../ . - • " selected as an appropriate standard for a hypothetical un­managed stock portfolio and performance was calculated using the index numbers and adding annual adjusted dividend figures (Standard and Poor's 1967, 1970).

Comparison with Market AveragesPerformance statistics shown in Fundscope (April 1970)

comparing their listing of growth funds with an "’adjusted"Dow Jones Industrial average for the years of 1962 through 1969 are pertinent (Tables 2 and 3).

RiskWhile some academicians such as Jensen (1968) may

agree that the risk-return dimensions of a portfolio may be measured, recently there have been doubts expressed as to the validity of these measurements for more than one period of performance (Wippern, Williamson, and Bower 1970).

As an example of the controversy in the field regard­ing risk, Seligman (1966) reported in a talk that his own investigation had yielded these results:

21

TABLE 2ANNUAL PERFORMANCE RESULTS

OF FUNDS (1962-1969)

Year 1962 1963 1964 1965* 1966* 1967* 1968* 1969*

D.J.I.A. -7.3 adjusted by Fundscope for dividends

+ 20.0 + 18.1 +13.8 —15.1 +18.3 + 7.3 -11.1

Growth Funds -18.5- ad jus ted. for Capital gain + Income Distributions

+ 19.5 + 10.5 + 27.7 -5.4 +44.7 +19.6 -16.1

*The years covered by this study.

TABLE 3ACCUMULATIVE PERFORMANCE FIVE YEAR

TIME PERIODS (1962-1969) (Calculated from above annual figures)

1962 thru 1963 thru 1964 thru 1965 thru Year 1966 1967 1968 1969*

D.J.I.A. adjusted by Fundscope for dividends

+27% +62% +45% +10%

Growth Funds adjusted for Capital gain + Income Distributions

+ 29% + 128% + 131% + 75%

*The years covered by this study.For the 1965-1969 period similar calculations using .

the Standard and Poor's 425 results in a yearly gain of 5.3%, including capital gains and dividends (Levy 1968, pp. 77-79).

22

When corporations which were in existence through the period 1929 to 1961 were classified by size and by Moody's quality ratings as of 1929, the rates of return on the larger of the higher quality corpora-

. tions were only moderately lower than for other cor­porations. . . . These small differences wouldpresumably be decreased and might disappear if they were adjusted for the influence of unsuccessful firms which did not weather the vicissitudes of the 1930's or later years. I have found even less evidence of an inverse correlation between quality and yield . . . in recent years.

In a 1971 unpublished study (Basist 1971) covering ■ the Standard of Performance for Growth Mutual Funds the author reviewed many of the major studies concerning the measurement of investment risk and concluded that the techniques for mea­suring risk, and indeed whether there is a "risk premium," are not generally accepted by the academicians and the prac­titioners in the industry (Richardson 1970, pp. 88-89). Other factors are that:

a. The study covers only growth mutual funds which generally have similar objectives, methods and risk charac­teristics (Treynor 1965)

b. The measurement of risk of growth mutual funds would entail an analysis of ex post data which may not be measuring objectives.

In view of the uncertainty about the risk-return re­lationship, it was decided not to introduce risk as a factor for this study.

CHAPTER IV

THE. INDEPENDENT VARIABLES (APPENDIX H)

Co-movement with Market Averages Sharpe (1966, pp. 127, 136, 137) observed that almost

90% of the variance of the return on the typical mutual fund (all types included) during the period of 1954-1963 was due to its co-movement with the Dow Jones Industrial Average. To compare performance, he compared the group average with the Dow Jones Industrial Average. He said (Sharpe 1970, pp. 161- ,162).. in-«a-'bat er ..art io le that .as, a, result -of -portfolio diver­sification the performance of most mutual funds was highly correlated with the standard market averages. After review­ing a study of Michael C. Jensen, Sharpe suggested that ap­proximately 85% of the variance of a mutual fund could be attributed to fluctuations of the market (Treynor 1966).

Another writer (Fama 1965, p. 92) also concluded that the average fund seems to do no better than the market and individual funds do not consistently outperform other funds. Five years later a similar conclusion was expressed by another author (Kahn 1970, pp. 11, 66) when he acknowledged that the average fund does not do very much better than the market averages over a full market cycle.

23

24

It is generally agreed that prior to 1960 most growth mutual funds did follow investment policies similar to trust companies and pension funds. As a partial result of this conservative investment policy the performance of the growth mutual fund closely matched the movement of the popular mar­ket averages. However, in the 1960's the concept of maximiz­ing growth permeated the policies of many of the growth mutual funds as a result of fund rivalry, the 1962 "Study of. Mutual Funds'1" (Wharton School 1962) , ebullient business climate and other factors. Many growth mutual funds engaged in such speculative practices as purchasing letter stock (stock pur­chased under market value with restrictions as to time of -sale) , rapid -portfolio turnover, buying the equities of com­panies in operation for only short periods of time, buying “new issues,“ and margin buying. In short, after 1960 there was a greater probability that the performance of the growth mutual funds would differ from the popular market indexes.

Asset Size -Many of the professionals, such as Douglas B. Fletcher,

in the mutual fund industry suggest that the relative rank­ings of the best performing funds change over a period of time as a result of asset size (Business Week May 3, 1969). Their reasoning is that while top performance attracts more new money, this very fact carries with it the seeds of its own destruction. This loss of opportunity (Laurence 1969,

25pp = 189—190), is partly due to the restrictions in The Invest­ment Company Act of 1940 which limits the percentage invested in any one company. Laurence opined that the larger fund is forced to diversify and to purchase shares in well-established firms which are less volatile and restricts the opportunity to secure superior performance that attracts investors.

This same judgment was expressed by the editors of Business Week (May 3,.1969, pp. 76-78) along with the comment,11 It is an ax ion of Wall Street that large funds lose their agility in the market, and other quasi-legendary figures of the fund business have been bowed by size - Edward C. Johnson II, Jack J. Dreyfus, Jr., and Gerry Tsai, among them."

Concerning legislation which may limit performance.The Investment Company Act (1940) prohibits the mutual fund from putting the first 75% into positions larger than 10% of the outstanding shares of any one corporation and it may not invest more than 5% of its own assets in any one company.There is no prohibition on the mutual fund from investing the balance of 25% in one company. The other major legislation (Fundscope October 1970, p. 11) that may affect the perfor­mance of a growth mutual fund is the Internal Revenue Code.The Code allows the mutual fund to avoid double taxation on realized capital gains and dividends (i.e., once at the cor­porate level and again after being distributed to their shareholders), by distributing 90% of its taxable income to shareholders.

26A contrary finding to Business Week is advanced in a

study (Wiesenberger 1970) which segregates growth mutual funds having, assets over 300 million dollars as of the 1968 year end. All growth mutual funds having less than 300 mil­lion dollars assets are considered "small.re

For the five year period of 1965 through 1969 there would not appear to be a significant difference in perfor­mance in the small versus the large growth mutual fund (Table 4) as defined by Wiesenberger. Along these lines, while intuitively it seems that the smaller fund may have the edge due to more opportunities that may be available, it should be pointed out that although the stock purchases of large funds may be restricted to the larger corporations, this may not limit subsequent performance (Business Week October 10, 1970).

' I : ■New MoneyThe Positive Side

The importance of new money being invested in funds was described in a feature article (Laurence 1969) inferring

Ithat the portfolio managers will admit that a steady influxof new cash is critically important. The pertinent portionreads as follows:

The unhappy experience of Mates Fund notwithstanding, one of the interesting aspects of the mutual-fund performance derby is that success breeds success, at

' least in the short run. Once a fund rises to the top

27TABLE 4

GROWTH MUTUAL FUND PERFORMANCE WITH CAPITAL GAINS REINVESTED PLUS INCOME

DIVIDENDS RECEIVED IN CASH

Year 1969 19685

1965years thru 1969

Average of Large Growth Mutual Funds

-13.2% +8. 3% + 79.7%

Average of Small Growth Mutual Funds

-15.2% +18.8% + 74.3%

ranks, it tends to stay there for a while. The rea­sons for this are obscure (for anyone who is inter­ested, the subject is discussed in detail in the June'1968 issue of Fortune) but they definitely relate to the influx of cash from new investors that usually accompanies a high position in the fund-performance list. A high ranking means new investors, and new investors mean new money. Once a fund management is blessed with new money, it is free to buy good new stocks whenever it finds them? it can buy them when the market goes down (obviously this is the best time to buy) and it can count on receiving useful research about hot new stocks from brokerage houses eager to get their hands on some of that incoming cash. Funds not blessed with new money, on the other hand, must dip into their reserves to make new investments or to meet redemptions = If they are fully invested and have no cash (most funds try to keep some in reserve), they must sell old investments, often at a loss, or at least at a time when they should not be sold. To the extent that a fund enjoys a steady stream of new money, it will be able to make the sort of good new invest­ments, that will keep it high in the rankings? and when a fund stays high in the rankings, it keeps get­ting more new money.

The relationship of new cash to performance was dem­onstrated by Alan Pope (1968, p. 138) for the five year period of 1961-1966. He concluded that, "new money does more to

28determine good performance than good performance does to at­tract new money." The basis for Pope's conclusions are:

1. With new cash coming in, the growth mutual funds may fake advantage of market dips and avoid having to sell promising investments to meet redemptions.

2. New cash attracts the advice of the best outside analysts.

3. New cash reduces the impact of past investments that have gone bad and acts as an "error eraser." Although from a practical standpoint large inflows of new money will "erase errors” only as long as the new money is properly in­vested.

■ -Many mutual fund investment advisors have expressed strong positive feelings regarding the benefits of an inflow of new cash. For example, the Putnam Management Company ex­pressed their sentiments in a publication (Putnam 1968, p. 27) that a continuing inflow of new money permits dollar cost ■ averaging in promising stocks.

The Negative SideNew money may be a two edged sword. Walter Heiby con­

cluded (1965, p. 121) after reviewing mutual fund data that the typical mutual fund buyer does (correctly) purchase more shares in the mutual funds during the middle of the market rise, and . usually continues to increase his purchases (incorrectly) as the market approaches the top. If this is the case, this

29large inflow of new money could place pressure on the growth mutual funds investment managers to invest heavily at the "wrong time" (Cohen and Zinbarg 1967, pp. 622-623).

The formula used to compute the approximate annual percentage of new money invested in a growth mutual fund is:

Formula #4*1969 closing +AV-1965 AV x Percentage 5 year growth** =

5 Average yearly newcash increase

Average Yearly NeW Cash Increase __________ _ =1969 Closing A.V + 1965 opening AV Annual Percentage

2 New Money Invested+AV = Asset Value*While most growth mutual funds distribute to their

shareholders, practically all of their net investment income after expenses have been deducted-and practically all of their realized capital gains, there are many exceptions (Casey 1969, p. 7).

**Percentage five year growth secured from Wiesenberger Investment Companies (Wiesenberger 197 0) „

Incentive Fees The basic idea behind the incentive fee is that the

standard form of compensation for the investment managers of growth mutual funds which averages about one-half percent of the asset value per year does not provide sufficient motiva­tion for the investment managers to perform at their best.The standard of measurement was normally one of the popular stock market averages, such as the Dow Jones Industrial aver­age, which usually was not adjusted for dividends. Another questionable practice that was.employed was that the incentive

. ■■ ' . 30fee was earned over a short time period, such as month or quarter. Therefore, it was entirely conceivable for an in­vestment manager t o ."earn" his incentive fee during a number of short time periods while the net asset value over a longer time period was actually dropping. In addition, an incentive fee may have the effect of fostering stock speculation on the basis of "heads," the investment manager wins and, "tails," the mutual fund investor loses.

An observation regarding incentive fees was made byH. G. Carpenter (1934, p. 99). He said, "by the simple device of putting their compensation bn a basis where they are paid for competence in managing money, rather than for competence in making sales, investment counsel . . . have eliminated the greatest handicap to successful investment management."

Approximately 30 years later another practitioner, Thomas A. Martin, president of the Channing Funds (Martin 1967, p. 27), strongly supported the concept of incentive fees and inferred they would increase performance by increas­ing effort.

In my judgment, incentive fees may be a reasonable method of compensation only if they also penalize losses on a similar basis, the basic management fee is reduced, the time period is long enough, and the standard of performance is rea­sonable and adjusted for dividends.

. No-Load Funds No-load funds do not have salesmen to sell their funds,

therefore, they do not levy commissions for either buying or selling their fund. The Twentieth Century Fund Study of mu­tual funds for the period of 1960-1968 (Friend, Blume, and Crockett 1970) determined: "To the extent that a relation­ship exists between performance and sales charges, the funds with the lowest charges, including the 'no-load' funds, ap­pear to perform slightly better than the other." One of the statistical tests made and reported in Chapter V of this the­sis will try to determine if load or no-load funds did do bet­ter or worse than the load funds for the 1965-1969 period.

Stock Manipulation, Shortage and Turnover

ManipulationMany persons on Wall Street feel that the success of

the growth mutual funds from 1965 through 1968 was not due to their trading skill but to stock manipulation (Kaplan and Welles 1969). As reported by Louis in Fortune (May 1967), William Martin, chairman of the Federal Reserve Board, told a New York audience that the tactics of the go-go funds re- . minded him of the "pool operations" of the 1920's. In the old pools individuals or groups of individuals would pur­chase large blocks of stock to bid up the price, attracting the unwary investor by the volume and the price movement, to

32bid up the price still further. At the point where the men behind the pools felt they had sufficient profit, they.would unload their shares. Subsequent to the speech of Martin, Manuel F. Cohen, former chairman of the Securities Exchange Commission, disclosed that his agency was investigating pos­sible manipulat3ma%of about 100 stocks owned by the funds. .

The subject of market manipulation, deliberate or not, during the years of 1967 through 1969 is a serious question. Business Week (July 25, 1970, pp. 53-61) in a special report confirmed that Wall Street recognized the "jet fuel effect" that institutional investors may have on a stock, particularly if it was glamorous and had a thin "float." Security analysts began talking about "self-fulfilling prophecies." If an ana-

7lyst shch as Tsai, Carr and others, decided "the stock would triple in price, the stock would triple," as everyone tried to get in when the knowledge of who is buying was leaked out. During this period of time, new concepts of value were ex­pounded and P/E ratios soared, with some over 150. Business Week commented that, "No one truly believes a 150 P/E ratio is related to anything except the hope of selling at a higher price." Included in this special report was a description of the "go-go" broker orchestrating rumors and buying in a thinly capitalized issue, "bringing different institutions in at dif­ferent price levels as a symphony conductor brings in trum­pets with the flourish of his hand."

. 33If only half of what Business Week reported is true,

it appears that during that period of time, the performance of many of the growth mutual funds was based more on the ability to play the game of "musical chairs" or "old maid" than on superior investment skills.

Frequently an answer to a complex question is found by examining the pronouncements of the elder statesmen of the industry concerned. One is Harold Stein, president of the second largest fund in the United States. During 1969, Stein was interviewed (Forbes 1969, pp. 78, 83) and commented that in 1967 and 1968 most performance had been on a manufactured basis, rather than on a sound value basis. By "manufactured" "he meant that while har'd Work, "intelligence and experience may produce better results over a period of time, say five years, it can't do 20% to 50% better than the market. To secure extraordinary performance one technique is to purchase stock in small companies. If the capitalization is small enough, this buying increases the stock price, a sort of lifting yourself up by your own bootstraps.

Finally, David L. Babson and Robert C. Puff, Jr.(1970, p. 13) in an article suggested that the superior per­formance of many growth funds during the 1965-1969 period was due to "manufactured" results. During this period the in­vestment managers of many of the growth funds concentrated their buying in companies with a small outstanding "float"' driving the market prices upward. In his opinion, as the

34market prices climbed, new cash poured into the mutual fund treasuries and the "performance became a self-generating process,” In addition, many funds purchased "letter stock" which was sold at a discount to the funds because of restric­tions as to possible sale and then the fund would favorably price the stock for the purpose of net asset value determina­tion- In short, the performance of many funds was financed by new buyers and according to Babson and Puff (1970) the net asset values of many of the funds was not the value at which the portfolio could be liquidated.

Considering the above facts, it appears that a por­tion of the performance of many of the growth funds was "manu factured."

Stock ShortageIn the opinion of many analysts, a major factor favor­

ing the superior performance of growth mutual funds from 1965-1969 was the shortage of stocks in comparison with de­mand, Evidence of this fact, appears in a Solomon Brothers publication and shown in Table 5 (Homer 1970, p. 12).

Sidney Homer of Salomon Brothers (Homer 1970, p, 14) made this comment in regard to the "shortage" of stocks:

Until 1969 corporations issued little or no new equities net after retirement of outstanding equi­ties, Therefore, institutions could only make their large net purchases by paying up to price levels which would induce other investors to sell.This scarcity of new equities in the face of grow­ing institutional demand was an important factor

35TABLE 5

NET ISSUANCE AND NET PURCHASES OF EQUITIES (Billion Dollar Annual Net Issuance and Net Purchases)

1965 1966 1967 1968 1969

Total Net Flotation of New Equities

0 1.2 2.3 -.9 4.3

Total Net Purchases by All Investors

5.7 5.9 9.1 10.3 12.6

Total Net Purchases by Foreigners

— o 4 — o 3 .7 2.0 1.5

Total Net Purchases by Individuals and Miscellaneous

-5.3 -4.4 -7.5 '-13.2 —9.8

- feworing < r-is•lng st-©ok' -.,§>r«iaes --ija -the ,1960 -s, • especial ly when combined with record economic growth and exuber­ant business optimism.

Stock TurnoverOne of the hallmarks of the rapidly growing growth

mutual fund during the 1965-1969 period was the rapid turn­over of the stock portfolio. In a study (Babson and Puff 1970) the investigators found that the turnover ratio of the seven top-ranked firms in 1969 was only one-third as much as the ratio of the seven funds at the bottom of the list. The list contained more than 250 stock funds with assets of over ten million dollars.

Prior to the Babson and Puff report there was a re­view of past studies and up-to-date statistics. A researcher

36concluded (Louis 1967) that there is little evidence on the side of the argument that the heavy stock turnover of the performance funds has led to superior performance. On the basis of his own studies he suggested that most of the six fast trading funds would have done better based on a buy and hold strategy (Louis 1967) and in the case of only one fund did the stock purchased do significantly better than the stock sold (Louis 1967).

CHAPTER V

EMPIRICAL RESULTS

GeneralOf 102 chi-square tests, eight tests were found to

have exceeded statistical significance at a confidence level of .05 (Appendix E). The computed chi-square values for the balance of the tests were within the range that indicates that the distribution probably occurred as a result of chance.

The eight tests where computed chi-square value ex- l,».Gseeded—fh.e--.GJS-it'i.calchi’rsqua^re .v.f.able •.vabue. will be analyzed in detail, including performance median (Appendices I, J and K). In addition, the responses to the last question in Sec­tion C of the questionnaire asking for the two most important factors of the fifteen factors listed in Section C have been singled out for special consideration and statistical anal­ysis.

A complete listing of the funds performance within the three performance groups for the five years, three "up" years and two "down" years, is shown in Appendix L. Overall, the 69 growth mutual funds in the study performed are shown in Table 6.

38

TABLE 6COMPARISON OF 69 GROWTH MUTUAL FUNDS

WITH STANDARD & POOR'S 425 (All Distributions Included)

(See Appendices K and L)

YearsGeometric Mean

Performance

5 years (1965-196 9)69 Growth Mutual Funds 11.54%Standard and Poor's 425 5.34%

3 "Up" Years (1965, 1967, 1968)69 Growth Mutual Funds 27.54%Standard and Poor's 425 16.39%

2 "Down" Years (1966, 1969) 69 Growth Mutual Funds Standard and Poor's 425

-8.43%-9.37%

39Evaluation of Liquidity of Mutual Funds

Two "Down" Years, 1966, 1969Chi—scruare analysis (critical value 5.991; computed

value 5.474) (Appendix M). The null hypothesis was rejected, indicating a statistically significant difference between the observed and the expected frequencies.

Study of the chi-square table and statistical data indicates (Table 7) :

1. A relationship between the funds that give con­sideration to the "Liquidity of Mutual Funds" 6% to 100% ofthe time and those funds that cluster towards the low third of performance.

2. A relationship between, those funds that give 5%or less attention to the "Liquidity of Mutual Funds" andeither the first or second performance group.

3. An analysis of the performance mean and median, reveals no strong pattern between the attention to the "Liquidity of Mutual Funds" and performance.

Conclusion: There does not appear to be a strongrelationship.

TABLE 7TWO "DOWN" YEARS, 1966, 1969;

LIQUIDITY OF MUTUAL FUNDS (Section B, Question 6, Data Processing Code No. 18)

Performance Total-Classes 1, 2,

6 to 100% of the time

3 , 4 Class 5 5% or less

of the timeGroup Funds Observed Expected Observed Expected

1 7 11 .0 15 11.02 23 11 11 .5 12 11.53 23 16 11 .5 7 11.5

TOTAL 68 34 34 34 34

Class Number

Perfor­manceMean%

Coeffi- Standard cient Deviation Varia-

.% tion

Perfor­manceMedian%

Perfor­manceRange

%QuartileDeviation

%1,2,3,4 34

5 34 TOTAL 68

-9.8 . -7.3

-8.5

5.4 -.55 6.2 -.84 5.9 -.69

—9.4-7.5-8.3

3.1 to -22.5

6.3 to -21.2

6.3 to -22.5

3.43.13-7

40

• • 41 •Evaluation of "Dow Jones Earnings"Three "Up" Years, 1965, 1967, 1968

Chi-square analysis (critical value 9.488; computed value 10.278) (Appendix N). The null hypothesis was rejected, indicating a statistically significant difference between the observed and the expected frequencies. -

Study of the chi-square table and statistical data indicates (Table 8)i

1. Those funds that consider the "Dow Jones Earnings" 6% to 64% of the time, when making broad decisions regarding the fund's portfolio, appear to cluster towards the top third performance group.

2. A relationship between those funds that give at­tention to the "Dow Jones Earnings" 65% to 100% of the time and those funds that tend to fall in the low third performance group. '

3. Those funds that consider "Dow Jones Earnings"6% to 64% of the time, perform better than the other two class cells— 33.5% performance mean, compared to 25.5% and 25.3% respectively.

Conclusion; It appears that too much or too little attention to the "Dow Jones Earnings" was related to poor performance for this period of time.

TABLE 8THREE "UP" YEARS, 19.65, 1967, 1968::DOW JONES EARNINGS

(Section B, Question 9, Data Processing Code No. 21)

Performance TotalClasses 1, 2 65 to 100% of the time

Classes 3 , 4 6 to 64%

of the timeClass 5

5% or less of the time

Group Funds . Observed Expected Observed Expected Observed Expected

1 22 6 10.5 9 4.9 7 6.62 22 12 10.5 5 4.9 5 6.63 23 14 11.0 1 5.1 8 6.9

TOTAL 67 32

Perfor­mance

32

Standard

15

Coeffi­

15

Perfor­

20

Perfor­

20

Mean Deviation cient mance mance QuartileClass Number % % Varia­

tionMedian

%Range

. %Deviation

%1+2 32 25.5 10.7 .42 23.8 62.0 to

11.45.0

3+4 15 33.5 9.6 .29 30.1 55.8 to 19.9

8.15 20 25.3 9.7 .38 25.0 53.0 to

8.76.6

TOTAL 67 27.2 10.7 .39 . 25.6 62.0 to 8.7

6.5

43Evaluation of Low Expense Ratio

Three "Up" Years, 1965, 1967, 1968Chi-scfuare. analysis (critical value 5.991; computed

value 5.783) (Appendix 0). The null hypothesis was rejected, indicating a statistically significant difference between the observed and the expected frequencies.

Study of the chi-square table and statistical data indicates (Table 9):

1. A relationship between the funds that consider "low expense ratio" for the fund as "not important"' and those funds that cluster towards the low third of performance.

2. Based on the performance mean, there appears to be a slight relationship between the degree of importance that funds attach to the "low expense ratio" and performance. The funds that consider this factor as "very important" or "somewhat important" tend to perform slightly better— 30.7% for classes 1 and 2, as compared to 25.9% for class 3.

Conclusion: The relationship does not appear to bestrong.

TABLfe 9LOW EXPENSE RATIO FOR THE FUND

THREE "'UP" YEARS/j 1965, 1967, 1968 (Section C, Question 2, Data Processing

Code No. 24)

Performance TotalClasses 1,2

Very Important Somewhat Important

Class 3 Not Important

Group Funds Observed Expected Observed Expected

1 23 9 7.7 14 15.32 23 11 7.7 12 15.33 23 3 7.7 20 15.3

TOTAL 69 23 23 46 46

Class Number

Perfor­manceMean%

Coeffi Standard cient Deviation Varia-

% tion

- Perfor­mance

Median %

Perfor­manceRange%

QuartileDeviation

%1, 2 23

3 46 69

30.725.927.5

11.3 .3710.3 .40 10.9 .39

26.524.425.7

62.0 to 14.3 .

55.8 to8.7

62.0 to8.7

7.56.26.4 44

Evaluation of tltConcentrating Funds in the Blue Chip Stocks1*'

Three ,rUptr Years, 1965, 1967, 1968Ghi-sguare analysis (critical value 5.991; computed

value 11.883) (Appendix P). The null hypothesis was rejected, indicating a statistically significant.difference between the observed and the expected frequencies.

Study of the chi-square table and statistical data indicates (Table 10)

1. A strong relationship between those funds that consider "Concentrating Funds in the Blue Chip Stocks," "very important" or "somewhat important" and those funds that tend towards the low third performance group.

"2. A strong relationship between those funds that consider "Concentrating Funds in the Blue Chip Stocks," "not important" and those funds that cluster toward the top third of performance.

3. A negative relationship between the degree of im­portance attached to "Concentrating Funds in the Blue Chip Stocks" and performance. In terms of the performance mean, those funds in Class 1 and Class 2 ("very important" and "somewhat important") the figure was 22.4% while for Class 3 ("not important") it was 30.3%.

Conclusion; The statistics appear to confirm the in­tuitive judgment that for these three "Up" years the funds that concentrated their holdings in the Blue Chip Stocks did not perform as well as the others.

TABLE 10THREE "UP" YEARS,.1965, 1967, 1968;

CONCENTRATING FUNDS it THE BLUE CHIP STOCKS (Section C, Question 9,

Data Processing Code No. 31)

Performance TotalClasses 1, 2

■ Very Important Somewhat important

Class 3 Not Important

Group Funds Observed Expected Observed Expected

1 23 3 8.0 20 15.02 23 7 8.0 16 15.03 * 23 14 8.0 9 15.0

TOTAL 69 24 24 45 45

Class Number

Perfor­manceMean%

StandardDeviation

%

Goeffi- Perfor- cient mance

Varia- Median tion %

Perfor­manceRange

%

QuartileDeviation

%1+2 24 3 45

TOTAL 69

22.4 30.327.5

9.910.310.9

.44

.34

.39

20.127.225.7

62.0 to 11.1

55.8 to 8.7

62.0 to 8. 7

4.76.7 6.4

..... 47

Evaluation, of "Positive Cash Flow Into Fund"7 Five Years, 1965-1969

Chi-square analysis (critical value 5.991; computed value 7.849) (Appendix Q). The null hypothesis was rejected, indicating a statistically significant difference between the observed and the expected frequencies.

Study of the chi-square table and statistical data indicates (Table 11) :

1. There is a strong relationship between the funds that consider 11 cash flow'1 into the fund very important and those funds that tend to occupy either the first or the third performance grouping.

2. There appears to be a tendency for those funds that consider "cash flow" into the fund either ‘"somewhat im­portant"' or "not important" and those funds weighted towards the mid-third performance group.

3. Based on the performance median and the mean, ; there appears to be a slight relationship between the degree of importance that funds attach to "cash flow" and performance. The greater the relative importance funds consider "cash flow" the poorer the performance.

Conclusion: It would seem that; on the average, thosegrowth mutual fund managers who did not consider "cash flow" as very important performed slightly better for this five : year period.

TABLE .11FIVE YEARS,1965-1969:

POSITIVE CASH FLOW INTO FUND (Section C, Question 13,

Data Processing- Code No. 35)

Performance TotalClass 1

V e r f - importantClasses 2, 3

Somewhat Important Not Important

Group Funds Observed Expected Observed Expected

1 23 12 . 10.3 11 12.72 23 5 10.3 ' 18 12.73 23 14 10.3 9 12.7

TOTAL 69 31 31 : ss 38

Class Number

Perfor­manceMean%

Coeffi- Perfor- Standard cient mance Deviation Varia- Median

% tion '%

Perfor­manceRange

%QuartileDeviation

%

1 31 2+3 38

TOTAL 69

10.512.411.5

5.5 .53 9.9 5.3 .42 11.95.5 .005 11.3

23.8 to -4.4

29.4 to 3.0

29.4 to -4.4

3.21.92.4

49 '

Evaluation of Two Most Important Factors— Singularly Five Years, 1965-1969, Three "Up11': Years, 1965, 1967, 1968;

Two "Down'* Years, 1966, 1969Chi-square analysis (Appendices Rl, R2, R3);Five Years— critical value 18.307 ? computed value

12.180Three Years— critical value 18.307; computed value

12.544Two Years— critical value 18.307; computed value 6.851

The null hypothesis was not rejected. This would indicate that there was not statistically significant difference between observed and expected frequencies for any of the three time periods. The statistician would say that there was no statis­tically signi'ficartt relationship between the independent vari­ables and the dependent variable of performance.

Study of the chi-square table and statistical data indicates (Tables 12 and 13) :

1. Those funds selecting C-12 (Evaluating Research from Outside Sources) as one of their two most important fac­tors performed as follows:

For the five years— tendency to cluster towards the top performance group.

For the three "Up" years— tendency to gravitate to­wards the top two performance groups.

For the two "Down'" years— tendency to fall into the last performance group.

502, Those funds selecting C-4 (Emphasis on Timing

Rather than Stock Selection) as one of their two most impor­tant factors performed as follows:

For the five years:— did not place in the top third performance group.

For the three "Up'" years— concentrated in the last performance group.

For the two "Down" years— no pattern discernable.3. Those funds selecting C-8 (Cutting Losses Promptly)

as one of their two most important factors performed as followsFor the five years— fell mainly in the second and

third performance group. For "the threse "Up" years—-increasing tendency towards

lower performance group.For the two "Down" years— increasing tendency towards

top performance group.Conclusion; Further statistical testing is required

to arrive at a"fund profile" which may be related to "superior performance.

TABLE 12MOST IMPORTANT TWO FACTORS:

EXPECTED AND OBSERVED FREQUENCY (Data Processing, Code No, 39)

FactorsPerfor- Total Factor Factor Factor Factor Factor Factor C-l thrumanceGroup

Obser­vations

C-Obs

3Exp

C-4*Observe

c-Obs

8Exp

C-Obs

10' Exp

C-Obs

12Exp

C-Obs

13Exp

C-15Obs Exp

5 Years 1 42 9 6.5 0 1 4.6 13 12.4 9 5.9 5 5.5 5 7.21965-1969 EDP Aver­ 2 41 4 6.4 5 8 4.4 12 12.1 5 5.7 4 5.4 8 7.0aging . Code No. 2 3 46 7 7.1 _5 _5 5.-0 13 13.6 4 6.4 _8 6.1 _9 7.8

TOTAL ■ 129 . 20 20 10 14 14 38 38 18 18 17 17 22 22

3 "Up" Years 1 40 8 6 = 2 1 3 4.3 11 11.8 8 5.6 5 5.3 5 6.81965, 1967, 1968 EDP 2 43 6 6.7 3 4 4.7 14 12.7 9 6.0 4 5.7 6 7.3Averaging Code No. 3 3 46 _6 7.1 __6 7 5.0 13 13.6 _1 6.4 _8 6.1 11 7.8

TOTAL 129 20 20 10 14 14 38 38 18 18 17 17 22 22

TABLE 12 — -Continued

FactorsPerfor­ Total Factor Factor Factor- Factor Factor Factor C—1 thmmance Obser­ C-3 ' C-4* C-8 C-10 C-12 C-13 015Group vations Obs Exp Observe Obs Exp Obs Exp Obs Exp Obs Exp Obs Exp

2 “Down" 1 45 6 7.0 3 7 4.9 15 13.3 3 6.3 6 5.9 8 7.7Years1966, 1969 2 40 5 6.2 4 4 4.3 13 11.8 6 5.6 5 5.3 7 6.8EDP Aver­aging 3 44 9 6.8 __3 3 4.8 10 13.0 9 6.1 6 5.8 7 7.5Code No. 4

TOTAL 129 20 20 10 14 14 38 38 18 18 17 17 22 22

*Not included as a separate factor for the chi-square analysis since the ex­pected observations in each cell would be less than 5.

TABLE 13MOST IMPORTANT TWO FACTORS: PERFORMANCE BY FACTOR (Data Processing, Code No. 19)

FactorNum­ber

Perfor­manceMean%

StandardDeviation

%

Coeffi­cient

Varia­tion

Perfor­mance

Median ■ %

Perfor­manceRange

%QuartileDeviation

%

Factor C-35 Years 20 12.6 7.5 .59 12.0 29.4 to

-4.44.1

3 ,rUp" Years 20 30.3 13.5 .45 26.8 . 62.0 to 8.7

9.72 "Down"' Years

Factor C-4

20 -9.1 6.5 -.71 -9.3 5.3 to -21.1

4.1

5 Years 10 7.7 . 4.9 . 63 9.6 12.3 to -4.4

2.73 "Uprr Years • 10 20.7 6.1 .29 22.1 29.6 to

8.74.1

2 "Down" Years 10 -9.2 4.8 — .52 -7.8 -3.4 to . -21.1

2.8

Factor C-85 Years 14 10.2 4.3 . .42 11.3 20.4 to

3.02.3

3 "Up" Years 14 24.1 10.4 .43 22.7 . 55.8 to 11.4

4.82 "Down" Years . 14 -7.5 5.0 -. 66 -7.2 1.2 to

-18.23.1

TABLE 13b— Continued

FactorNum­ber

Perfor­manceMean%

StandardDeviation

%

Coeffi- , cient Varia­tion

Perfor­manceMedian

%

Perfor­manceRange%

QuartileDeviation

%

Factor C-10 -

5. Years 38 11.6 5.0 .43 11.1 29.4 to 2.7

2.13 "Up" Years 38 26.8 10.1 .38 24.6 53.0 to

11.16.9

2 "Down” Years

Factor C-12

38 -7.6 6.2 —. 80 -7.8 6.3 to -22.5

3.6 .

5 Years 18 13.4 4.7 .35 , 12.8 27.2 to 7.4

3.03 "Up"* Years 18 32.9 10.7 .32 28.0 62.0 to

16.38.2

2 "'Down” Years

Factor C-13

18 -10.3 3.8 -.37 -10.6 —3.6 to -16.8

3.3

5 Years 17 10.1 4.3 .43 9.8 20.4 to 2.7

2.43 "Up"’ Years 17 . 25.6 10.1 .40 23.3 55.8 to

12.85.8

2 "Down" Years 17 -9.2 6.8 -.74 -7.9 3.1 to -22.5

4.6

TABLE 13— Continued

FactorNum­ber

Perfor­manceMean%

Coeffi- Perfor- Staridard cient manceDeviation Varia- Median

% tion %

Perfor­manceRange%

QuartileDeviation%

TOTAL ALL .FACTORS 5 Years 1293 "Up" Years 1292 111 Down" Years 129

11.3 5.4 .47 11.0 29.4 to —4.3 2.6

27.1 10.8 .40 24.9 62.0 to 8.7

6.5-8.4 6.1 -.72 —8.4 6.3 to

-22.54.0

56Evaluation of Two Most Important Factors—

Factors Considered in Combination Five Years, 1965-1969, Three ■rUp,r Years, 1965, 1967, 1968,

Two "Down'" Years, 1966, 1969Chi-square analysis (Appendix S).Considering the nature of this analysis a chi-square

test was not attempted.Analysis of statistical data indicates (Table 14):1. Fox the five year and the three '"up"' year periods

three combinations of the two factors considered the most im­portant are related to better than average performance.These are, 3+10, 3+12, and 10+12— number 3 factor is "Invest­ing in emerging companiesnumber 10 factor is "Judging a portfolio reward versus risk relationship,11 and number 12 fac tor is "Evaluating research from outside sources."

2. For the two "down1" years, two of the above com^ binations are associated with poor performance. These are, 3+12 and 10+12. Three.factor combinations are related to slightly better performance. These are, 3+10, 4+10, and 8+10 number 8 factor is "Cutting losses promptly.

Conclusion: Generally speaking, for this study, thecombination of the two most important factors that are re­lated to superior performance in the "up" years, are related to poor performance in the "down" years.

TABLE 14TWO MOST IMPORTANT FACTORS—

FACTORS CONSIDERED IN COMBINATION (Having 3 or Moire Observations)

Perfor­manceMean

Factor Factor Number %

Coeffi- Perfor— Perfor- Standard cient mance manceDeviation Vania- Median Range

tion % %%Quartile : Deviation

% '

5 Years3 10 8 13.4 7.9 .59 12.0 29.4 to

4.06.7

3 12 8 14.1 5.8 .42 12.4 27.2 to 7.4

3.24 10 3 8.9 2.9 .32 9.3 12.3 to

5.2—

8 10 7 9.4 • 3.5 .37 11.1 12.7 to 3.0

2.010 12 6 14.6 2.5 .17 14.2 18.0 to

10.92.3

10 13 8 9.4 . 3.1 .33 . 9.7 . 13.6 to 2.7

2.3Fund Average

3 "Up" Years

69 11.5 5.5 .47 11.3 29.4 to —4.4

2.4

3 10 8 29.5 14.6 .50 22.9 53.0 to 11.1 14.4

3 12 8 35.4 12.0 .34 30.1 62.0 to 24.9

8.74 10 3 20.9 3.9 .18 18.6 26.3 to

17.8— ' m'•j

TABLE M-^Continued

Factor Factor Number

Perfor­manceMean%

StandardDeviation

%

Coeffi- : cient Varia­tion

Per for-' . mance Median

%

Perfor­manceRange%

QuartileDeviation

%

8 . 10 7 21.8 6.7 .31 24.0 32.7 to 11.4

5.610 12 6 35.4 8.1 .23 34.9 44.8 to

26.58.4

10 13 8 25.9 7.8 .30 25.9 38.4 to 14.3

6.9Fund Average

2 "Down" Years

69 27.5 10.9 .39 25.7 62.0 to 8.7

6.4

3 10 8 -6.5 6.6 —1.0 . -7.3 5.3 to -14.8

5.43 12 8 : -11.5 3-4 -. 29 -11.6 -5.8 to

-16.82.8

4 10 3 -6.9 . 3.2 -.47 —6.0 -3.4 to -11.2

—8 10 7 -6.7 3.6 -.53 -5.9 -1.0 to

-13.02.8

10 12 6 -10.6 4.1 -.39 -11.2 -3.6 to -15 .3

4.010 13 8 -11.1 6.8 . -.61 -8.4 . -2.6 to

-22.53.4

Fund Average 69 -8.4 6.0 -.71 —8.1 6.3 to -22.5

3.9

59 •

Evaluation of ‘"Percent New Cash'"Three "Up” .Years, 1965, 1967, 1968

Chi-square analysis (critical value 9.488?, computed value 10.091) (Appendix T ). 1 The null hypothesis was rejected,indicating a statistically significant difference between the observed and the expected frequencies.

Study of the chi-square table and statistical data indicates (Table 15) : ' : v’

1. A relationship between the funds that experienced over 20% yearly new cash (using formula No. 4) and those funds that tend to fall into the first performance group.

2. A relationship between those funds that had under 0% new cash and those funds that are distributed towards the low third performance group.

3. A progressive relationship is apparent between funds performance and “percent new cash.“ The funds in Group 1 (under 0%) obtained a performance mean of 23.1%, Group 2 (0% to 20% 26.7% and Group 3 (over 20% 31.5%).

Conclusions: While there appears to be a positiverelationship between "Percent New Cash" and performance for these three “up" years, there is still the unsolved question of which came first— the new cash or the performance.

TABLE 15THREE '"UP" YEARS ,1. 1965, 1967, 1968: '

PERCENT'NEW CASH (Data Processing:, Code No. 52)

Performance TotalClassUnder

10%

Clas s 2 0 to 20%

Class 3 Over 20%

Group Funds Observed Expected Observed Expected Observed Expected

1 23 3 5.3 8 9.7 12 8.02 23 4 5.3 14 9.7 5 8.03 23 _9 5.3 7 9.7 7 8.0

TOTAL 69 16 16 29 29 24 24

Class Number

Perfor­mance Standard Mean Deviation % %

Coef f i- ■cient Varia- , tion

Perfor­mance

: Median% _ ■

Perfor­manceRange% .

QuartileDeviation

%1 . 16 23.1 I—1«—1 i—1 .48 21.8 55.8 to

8.73.9

2 . 29 , 26.7 7.3 .27 26.3 48.4 to 11.4

3.13 24 31.5 12.8 . .40 30.4 62.0 to

12.810.6

TOTAL 69 27.5 10.9 .39 25.7 62.0 to 8.7 •

6.4

Evaluation of "'Date Shares Offered"61

Three “Up” Years, 1965, 1967, 1968Chi-square analysis (critical value 9.488; computed

value 10.499) (Appendix u). The null hypothesis was rejected, indicating a statistically significant difference between the observed and the expected frequencies.

Study of the chi-square table and statistical data indicates (Table 16):

1. Those funds that have been operating from ten to twenty years tend to cluster towards the top third performance group.

2. Those funds that have been operating over twenty years tend to fall into the low third performance group.

Conclusion: While those funds operating over twenty'years did not perform as well as those funds operating over a shorter time period, there may be other factors, such as fund size, that may be influencing the relationship with performance

TABBE 16THREE "UP" YEARS,: 1965, 1967, 1968:

DATE SHARES OFFERED (Data Processing, Code No. 6)

Performance TotalClass 1

5 to 10 yearsClass 2

10 to 20.yearsClass 3

Over 20 years.Group Funds Observed Expected ; Observed Expected Observed Expected

. 1 23 6 5.7 16 12.0 1 5.32 23 . 4 5.7 - 13 12.0 6 5.33 23 _7 5.7 . 7 12.0 _9 5.3

TOTAL 69 17 .

Perfor­mance

17

Standard

36

Coeffi­cient

36

Perfor­mance

16

Perfor­mance

16

QuartileMean Deviation Varia­ Median Range Deviation

Class Number % % tion % % %1 ' 17 27.4 11.4 .42 . 26.5 49.4 to

12.89.5 .

2 36 30.3 11.3 .37 27.8 62.0 to 11.0

4.63 : 16 21.5 5.2 .24 22.1 33.0 to

8.73.2

■ TOTAL 69 27.5 10.9 .39 25.7 62.0 to 8.7

6.4

■ 63 ..

Evaluation of "Load Versus No-Load Funds"’Three "Up'" Years, 1965, 1967, 1968

Chi-square analysis (critical value 5 - 991; computed Value 6.713) (Appendix v). The null hypothesis was rejected, indicating a statistically significant difference between the observed and the expected frequencies. ^

Study of the chi-square table and statistical data indicates (Table 17):

1. A relationship between load funds and a tendency to cluster in either the first or the mid performance group.

2. There is a strong relationship between no-load funds and the tendency to fall into the low performance group.

3. Based on mean annual performance figures the load funds as a group performed better than the no-load funds for this period of time^— 28.7% compared to 23.9% per year with standard deviations of 10.8% and 10.1% respectively. The median performance was 26.5% for load funds and 19.9% for no-load funds with quartile deviations of 5.0% and 6.8% respectively.

Conclusion; While the distribution is both skewed and scattered, the load funds achieved a better performance than the no-load funds for the three ™up,E years. For the two "down" years the chi-square test revealed no statistically significant difference (Appendix E).

TAB Li 17THREE "UP" YEARS,i1965, 1967, 1968:

LOAD VERSUS NO-LOAD FUNDS (Data Processing, Code No. 7)

PerformanceGroup

TotalFunds

Glass 1 Load Fund

Observed ExpectedClass 2

No-Load Fund Observed Expected

123

TOTAL

23232369

1920 13 52

17.317.317.3 52

43

1017

5.75.75.717

Class12

Number5217

TOTAL 69

Perfor­manceMean%28.723.927.5

Coeffi- Standard cient Deviation Varia­

tion%' 10.8 10.1 10.9

.38

.42

.39

Perfor­mance

Median%26.519.925.7

Perfor­manceRange%

62.0 to8.7

48.4 to11.4

62.0 to8.7

QuartileDeviation%

5.06.86.4

CHAPTER VI

SUMMARY AND CONCLUSIONS

A questionnaire (Appendix A), covering 29 factors thought to be related to performance was mailed to 124 growth mutual funds operating more than five years, for which annual performance data was available. Replies were received from 69 funds. In addition to the 29 factors, another five factors were tested as part of the study. Each of these independent variables was tested to determine if there was a significant .relationship with the dependent .variable for the five year period of 1965 through 1969, three "up" years of 1965, 1967 and 1968, and the two "down" years of 1966 and 1969. A total of 102 chi-square tests and other statistical data were run with only eight of the chi-square tests showing a statisti­cally significant relationship at the .05 level of confidence. These eight factors were:

1. Liquidity of mutual funds— for the two "down" years.2. Dow Jones earnings— for the three "up" years.3. Low expense rate for the fund— ^three "up" years.4. Concentrating funds in the blue chip stocks— .

three "up" years.5. Positive cash flow into fund— five years.

- V ■ ■ ■ 6 6 :

6. Percent yearly new cash— -three "up" years.7. Date shares offered:— three rrup"' years .8. Load versus no-load— three "'up"' years.

- Considering the other chi-square tests that were run and reviewing the statistical data obtained, such as mean, median, and standard deviation, it appears that none of the eight factors shown above had a statistically significant re­lationship with performance for both the three "uptp and the two "down"' years.

. An analysis of the replies to the question asking for the two most important factors influencing performance, seems to indicate that those factors either singularly or in combi­nation that may be positively related to performance duringthe "up"’ years, are negatively related to performance during the "down" years and vice versa.

An overall evaluation of the results suggests that for the 3 "up" years growth load funds, operating from 10 to 20 years, having over 20% new cash flowing annually into the fund, with an investment policy based on evaluating research from outside, sources, rather than on market timing and technical indicators, did experience superior performance.

It is recommended that the results of this study be tested over other time periods to substantiate or reject the findings.

67 .

Suggested Areas for Future StudyThe study undertaken herein was primarily an explor­

atory investigation covering many of the factors that may in­fluence the performance of growth mutual funds. However, the replies to the questionnaire, the statistics collected and the statistical framework for this initial investigation may provide the basis for further investigations into this very interesting area of portfolio management. In this manner, with each study building upon previous findings, it may be possible to statistically prove a significant relationship over a period of time between one or more of the factors that related to the performance of growth mutual funds. Some of the Suggested areas for "further study are:

1. Additional independent variables such as yearly expenditures for investment research, stability of new cash inflows, and dollar cost averaging.

2. Multiple correlation and regression tests based on the results of the questionnaire and the other statistics developed in this study.

3. The eight factors found to have a statistically significant relationship with performance should be tested over other time periods.

4. The replies to the question regarding the two most important factors should be subjected to additional rigorous statistical testing.

. • ■ ■■ ' , ' 68 ■ The above is not a complete listing of suggested

areas for future investigation to determine the factors re­lated to the performance of growth mutual funds. However, these subjects may have the potential to advance the study of growth mutual fund performance„

APPENDIX. A

' -QDESTTGNNA.TRE- AND COVER LETTER

69

70

Robert Baslst, c/o Dr. W. K. Kirk, ColleKe of Business 4 Public Administration The University of Arizona, Tucson, Arizona 85721

Subject:_________________________________________

(1) (2) (3) " (4).......... . W ™95 - 100% of the time

65 - 94% of the time

35 - 64% of the time

6 - 34% of the time of the time

■Kindly reply to all questions In Sections A and B based on the above KEY, for the period 1965 to 1970, or during the period of your Investment management of the fund, If a shorter period Is Involved.

(SEE* KEY)A. FOR THE ABOVE NAMED FUND: (Please check (*') each point)1. We concentrated the fund's assets In a minimum of ........... 11 | 2 | 3 | 4 ! 3 ]

industry categories (under 10 categories.)2. We did have a net positive cash flov(sales .........*-— ■— 1— 1— .

less redemptions) Into the fund................................ 11 | 2 | 3 [ 4 | 5 [3. We concentrated the funds assets in the medium ______

size and small companies (under 300 million sales)........... I 1 7 T T 3 T * [ 5 Ilisted on the N.Y.S.E. and the A.S.E. *-----

4. Depending on our appraisal of the future direction ------ j __ _of the stock market we made switches of the funds ........... 11 |2 j 3 14 1 5 |assets to over 10% cash or Its equivalent.

B. WHEN MAKING BROAD DECISIONS REGARDING THE FU N t/s PORTFOLIO,WE CAVE ATTENTION TO: (Please check (/) each point)

1.2.3.4.5*

1 2 3 4 5Dow TheoryDollar Cost Averaging Relative Strength by Industry Barron's Confidence Index Bond Index 4 Interest Rates

OTHER: (Please specify and show number)*__

Liquidity of Mutual Funds Changes In Money Supply Changes In Cold Prices Dow Jones Earnings Government Economic Indica­tors, other than those listed

1 2 3 4 5

9.10.

WE CONSIDER THE FOLLOWING FACTORS AS MAJOR DETERMINATES OF SUCCESSFUL LONG TERM CAPITAL CR0V.TH PERFORMANCE FOR A MUTUAL FUND (V.l. - very Important; S.I. - somewhat Important; N.I. - not Important). Please check (/ ) each item.

V.l. S.I. N.I1. Asset size of the fund2. Low expense ratio for the fund3. Investing in emerging companies4. Emphasis on timing rather than stock selection5. Not limiting purchases to domestic securities6. Using margin when appropriate7. Pyramiding gains (purchasing more of the stocks you hold)8 . Cutting losses promptly9. Concentrating funds in the blue chip stocks10. Judging a portfolio reward vs. risk relationship11. Purchase of lettered stock12. Evaluating research from outside sources13. Positive cash flow Into fund14. Purchasing puts and calls15. Performance fees

Which 2 factors do you consider the most Important? Numbers____OTHER: (Please specify other factors and show whether V.l,,S.I.

D. Please give any corments,examples, book or magazine references that you feel may be pertinent or helpful to me regarding the above questions or my research paper.*

E. Do you plan to operate differently in the years ahead? If so, what factors will you emphasize?*

F . We have been advisors to this fund since___________(year).

* Please use reverse aide of this questionnaire or a separate sheet of paper If necessary. (PLEASE CHECK TO BE SURE ALL QUESTIONS ARE ANSWERED)

THANK YOU FOR YOUR ASSISTANCE.

T H E U N I V E R S I T Y OF A R I Z O N AT U C S O N , A R I Z O N A 85721

COLLEGE OF BUSINESS AND PUBLIC AD M INISTRATIO NDEPARTMENT OF FINANCE, INSURANCE,

AND REAL ESTATE

i»/Asv%a.»Gxaduate..Szudaat...,o.fv,FdLna.n.C!e,,.at The University of Arizona and previously a vice president of a major Canadian food and department store corporation for ten years', 1 know how valuable your working time is, so I will get right to the point.

I have selected for my thesis for the Department of Finance, “Determinates of Performance for a Growth Mutual Fund." To pinpoint these factors, I am sure you will agree that a one-page questionnaire directed to the investment advisors of the growth funds (as classified by Wiesenberger Services or A. Lipper Corporation), operating over five years, should be the basis of this research paper. The individual responses will remain strictly confidential. If desired, a summary of the major thesis conclusions will be sent to you. This study may assist the industry to respond to the unjustified criticism of mutual funds over the past two years, and at the same time may shed light on areas for improving performance.

A self-addressed envelope is enclosed for your convenience in replying. Thank you very much for your assistance and early reply. ; '

Sincerely yours.

Robert Basist

Enclosures -

APPENDIX B

CLASSIFICATION OF INDEPENDENT VARIABLES

Strength of the economy arid stock market (8 factors evaluated).Section B of the questionnaire, questions 1, 4, 5, 6, 8, 9, 10. .Operating, practices and general conditions (26 factors evaluated).Section A. of the questionnaire, questions 1,2, 3, 4.Section. B .of ..the que.sti.opnaire., questions 2, 3.Section C of the questionnaire, questions 1 through 15In addition, these five factors were evaluated:

asset sizepercentage of new money invested incentive fee load or no-load date fund started

72

APPENDIX C

COMPLETE LISTING OF FUNDS COVERED IN THE STUDY

74Identifi­cationNumber Fund Name

1 . , . . . . American Investors Fund2 . . . . . . American National Growth Fund, Inc.3 ........Anchor Growth Fund, Inc.4 . . . . . .. Babson (David L.) Investment Fund5 . . . . . . Beacon Hill Mutual Fund, Inc.6 . . . . . . Boston Common Stock Fund, Inc. :■7 . . . . . . Capital Investors Growth Fund, Inc.8............ Capital Shares, Inc.9 . . . . . . Chemical Fund

10 . . . . . . Colonial Growth Shares11 . . . . . . Colonial Equities, Inc.12 . . . . . . Commerce Fund, Inc.13 . . . . . . Common Stock Fund of State Bond & Mortgage Co.14 . . . . . . Concord Fund, Inc.1 5 ........ .. Crown Western Investments; Dallas Fund16. . . . . . Delaware Fund17 . . . . . . de Vegh Mutual Fund, Inc.18 . . . . . . Dreyfus Fund19 . ... . . . Egret Growth Fund, Inc.'20 . . . . . . Energy Fund, inc.21............ Enterprise Fund, Inc.22 . . . . . . Federated Growth Fund23............ First Participating Fund, Inc.24 . . . . . . Franklin Custodian Growth25............ Growth Industry Shares26 . . . . . . Hedberg & Gordon Fund, Inc.27 . . . . . . Imperial Growth Fund28 . . . . . . Integon Growth Fund Corp.29 . . . . . . Investors Research Fund30 . . . . . . Ivest Fund31 . . . . . . Johnson Mutual Fund32 . . . . . . Keystone Custodian Fund, S433............ Keystone Custodian Fund, K234 . . . . . . Keystone Custodian Fund, S335 . . . . . . Knickerboker Growth Fund, Inc.36 . . . . . . Lexington Research Fund, Inc.3 7 .......... . Massachusetts Investors Growth Stock Fund38 . . . . . . MIF Growth Fund, Inc.39 . . . . . . Mutual Securities Fund of Boston4 0 .Nassau Fund41 . . . . . . National Securities - Growth Stock Series4 2 .NBA Mutual Fund, Inc.43 . . . . . . Newton Fund

75

Identifi­cationNumber Fund Name44 . . . . -. . Oppenheimer Fund45 . . . . . . Over-The-Counter Securities Fund, Inc.46 . . . . . . Penn Square Mutual Fund47 . . . . . . Pilgrim Fund, Inc.48 . . . . . . Pioneer Enterprise Fund, Inc.49 . . . . . . Planned Investment Fund, Inc.5 0 .T. Rowe Price Growth Stock Fund51 . . . . . . Rowe Price New Horizons Fund, Inc.52 . . . . . . Putnam Growth Fund53 . . . . . . Putnam Investors Fund54 . . . . . . Revere Fund55 . . . . . . Scudder Special Fund56 . . . . . . Security Equity Fund57 .......... Stein Roe & Farnham Capital Opportunities

Fund, Inc.58 . . . . . . Stein Roe & Farnham Stock Fund59 . . . . . . Technology Fund60 ............ Templeton Growth Fund, Ltd.61 . . . . . . Value Line Fund, Inc.62 . . . . . . Value Line. Special Situations Fund, Inc.63 . . . . . . Vanderbilt Mutual Fund64 . . . . . . Vanguard Fund, Inc.65 . . . . . . Venture Securities Fund, Inc.66 ........... Viking Growth Fund, Inc.67 . . . . . . Western Industrial Shares68 . . . . . . Windsor Fund69 . . . . . . Worth Fund, Inc.

APPENDIX D

EXTRACT FROM CHI-SQUARE VALUES TABLE

Column A Degrees of Freedom

1234

5678 9

10

Column B 95% Level of Confidence

3.8415.9917.8159.448

, 11.07012.59214.067

. 15.507, 16.919

18.307

76

APPENDIX E

MASTER RESPONSE TABLE RECAP OF COMPUTED CHI-SQUARE VALUES

77

A. QUESTIONNAIRE

DataProces- Degrees

Questionnaire sing ofSection-Question Code Freedom

1 9 42 10 23 11 , 44 12 41 13 22 14 ' 23 15 44 16 25 17 26 18 27 19 48 20 29 21 4

10 22 41 23 . 22 24 23 25 24 26 25 27 26 28 47 29 28 30 49 31 2

10 . 32 2

Critical _____ Chi-square Values_______Value from 3 "Up"Chi-sguare 5 Years Years 2 "Down"

Table 1965— 1965, 1967 Years(.05)1 1969 1968 1966, 1969

9.488 6.047 4.606. 6.0175.991 4.246 1.415 2.4779.488 3.359 . 4.146 . 9.1269.488 7.067 5.388 6.9665.991 2.032 1.848 .5145.991 .088 .79 5.4109.488 • .824 1.347 4.8965.991 2.881 1.194 2.5235.991 4.456 .024 . 2.0845.991 5.549 5.336 6.474s9.488 . 2.029 2.851 1.5945.991 1.007 3.228 4.3629.488 . 4.971 10.278s 3.7599.488 2.321 3.779 6.4285.991 4.557 .651 .1635.991 . .130 6.783s 3.2615.991 5.308 1.604 2.3455.991 4.739 3.602 .1905.991 1.533 . 4.983 4.6009.488 3.091 3.091 3.0905.991 1.460 .365 3.2869.488 . 2.256 6.302 5.8375.991 4.983 11.883s 3.4505.991 .411 .411 1.232 CO

Critical Chi-square ValuesData Value from 3 "Up"

Proces- , Degrees Chi-square 5 Years Years 2 "Down"Questionnaire sing of Table 1965- 1965, 1967 YearsSection-Question Code Freedom (.05) 1969 1968 1966, 1969

11 33 - — — —

12 34 2 5.991 3.280 3.280 4.33413 35 2 5.991 7.849s 3.632 .82014 36 - — - . — —

15 37 2 5.991 1.980 4.525 3.676Quest ionnaire 39 10 18.307 12.180 12.544 6.851

. B. ADDITIONAL INDEPENDENT FACTORSIndependent Factors Percent YearlyNew Cash 52 4 9.488 6.272 10.091s 4.306Date Shares Offered 6 4 9.488 7.196 10.449s 2.990Load vs. No-Load 7 2 5.991 4.371 6.713s 2.029Incentive Fee 8 2 5.991 3.019 5.606 1.725Average Asset Value ■ 47 . ■ 2 ' ■ 5.991 3.247 1.855 2.203

"*"95% level of confidence with appropriate degrees of freedom - ^Significant value

APPENDIX F

DATA PROCESSING CODING SHEET AND NUMBER OF FUNDS IN EACH CLASSIFICATION

A. Percent yearly new cash (EDP Code No. 52)Less than 0% - (16 funds) — Class 1 0 to 20% - (29 funds) - Class 2 Over 20% - (24 funds) - Class 3

B. Date shares offered (EDP Code No. 6)From 5 to 10 years (1960-1965) - (17 funds) - Class 1Over 10 years to 20 years (1949-1959) - (36 funds) - Class 2Over 20 years (1948 or before) - (16 funds) - Class 3

C. Load funds versus no-load funds. (EDP Code No. 7)Load funds - (52 funds) - Class 1 No-load funds - (17 funds) - Class 2

D. Management Incentive fee or not (EDP Code No. 8)Does have an incentive fee (5 funds) - Class 1 Does not have an incentive fee (64 funds) Class 2

E. Average asset value (EDP Code No. 47)Under 25 million (34 funds) - Class 1 25 to 100 million (13 funds) - Class 2 100 to 250 million (11 funds) - Class 3 250 to 250 million (8 funds) Class 4

• Over 500 million (3 funds) - Class 5F. Investment advisor and year

No statistical tests were run. Listing shown for informa­tion purposes only.

80

APPENDIX G

MAIN DATA CARD FORMAT

CardColumn Contents

1 - 3 Fund Number4 - 1 5 Fund Name16 - 24 Investment Advisor25 - 28 1965 Assets in Millions29 - 32 1969 Assets in Millions.33 . Date Shares Offered34 Code for Load, No-Load Funds35 Code for Incentive Fee36 - 39 Replies to Section "A'r of Questionnaire40 - 49 Replies to Section "B" of Questionnaire50 Blank '50 - 65 Replies to Section ,lC,r of Questionnaire6 6 - 6 7 Reply to Two Most Important Factors68 Blank6 9 - 7 0 Reply to Two Most Important Factors7 1 - 7 2 Year When Present Investment Advisor Hired73 - 80 Blank

81

z

APPENDIX H

MASTER CODE LISTING - DESCRIPTION OF DEPENDENT AND INDEPENDENT VARIABLES

82

83

___________ Code____________Question Data Description of Independent

Section Number Processing VariablesA 1 9 We concentrated the fund's assets

in a minimum of industry cate­gories. (under 10 categories)

2 10 We did have a net positive cashflow (sales less redemptions) into the fund

3 11 We concentrated the fund's assets• in the medium size and small

\ companies (under 300 millionsales)

• 4 12 Depending on our appraisal of thefuture direction of the stock market, we made switches of the fund's assets to over 10% cash or its equivalent

1 13 Dow Theory2 14 Dollar Cost Averaging3 15 Relative Strength by Industry4 16 Barron's Confidence Index5 17 Bond Index & Interest Rates6 18 Liquidity of Mutual Funds7 ' 19 Changes in Money Supply8 20 Changes in Gold Prices9 21 Dow Jones Earnings

10 22 Government Economic Indicatorsother than those listed

C 1 23 Asset size of the fund23

2425

Low expense ratio for the fund Investing in emerging companies

84 _________ Code ;___

Question Data ' Description of IndependentSection Number Processing Variables

C 4 . 26 Emphasis on timing rather thanstock selection

5 27 Not limiting purchases to domesticsecurities

6 28 Using margin when appropriate7 29 Pyramiding gains (purchasing more

> of the stocks you hold)8 30 Cutting losses, promptly

\ 9 31 Concentrating funds in the bluechip stocks

10 32 Judging a portfolio record vs.risk relationship

11 33 Purchase of lettered stock12 34 Evaluating research from outside

sources13 35 Positive cash flow into fund14 36 Purchasing puts and calls15 37 Performance fees- 39 Which two factors do you consider

most important- 51 Performance thirds- 52 Percent New Cash- 6 Date Shares Offered- 7 Load Versus No-Load- 8 Incentive Fee- 47 Average Asset Value

85Code

Question Section . Number

C -

Data Description of DependentProcessing Variables

2 Geometric mean of 5 year perfor­mance 1965-1969

3 Geometric mean of 3 "‘up" yearsperformance, 1965» 1967, 1968

4 Geometric mean of 2 "down"' years performance, 1966, 1969

APPENDIX I

MASTER RESPONSE TABLE-—RECAP OF REPLIES TO QUESTIONNAIRE

86

ClassCode 1 2 3 4 5 Unlisted Tot;

sstion Data 95-100% 65-94% 35-64% 6-34% 5% orProces­ of the of the of the of the less ofsing time time time time the timeCode

- 1 9 19 12 4 3 30 1 692 10 39 18 I 1 6 0 693 11 9 14 15 12 18 1 694 12 19 11 12 13 14 0 69- 1 13 5 3 4 3 53 1 692 14 4 3 . ii 11 37 1 693 15 26 20 14 3 5 1 69. 4 16 1 4 3 5 55 1 695 17 . 12 18 i. 9 21 1 696 18 5 6 14 9 34 1 697 19 23 20 10. 9 6 1 698 . 20 1 0 0 9 58 1 699 21 , 13 19 6 9 20 2 6910 : 22 25 17 15 ■ . 5 5 2 69

Very Somewhat NotImportant Important Important

1 2 3 Unlisted Total- 1 23 10 43 16 0 69

2 24 4 19 46 0 693 . 25 26 35 8 0 69 '4 26 - .13 48 8 0 695 27 1 23 45 0 696 28 2 1 66 0 697 29 7 35 27 0 69 oo<1

CodeQuestion Data Very Somewhat

Proces- Important Important s ing 1 2Code

8 30 25 289 31 4 20

10 32 48 1911 33 0 312 34 38 2413 35 31 2714 36 o 015 37 1 7

C - D 39 1 - 24 0■6 71 3

11 120 18

Not 'Important -

3 •Unlisted Total

16 0 6945 0 69

2 0 6966 0 69

7 . o 6911 0 6969 . 0 . .. 6961 0 69

3 ■ 4 520 10 1

8 9 1014 3 3813 • 14 . 15 Total17 . 0 0 138

APPENDIX J

MASTER RESPONSE TABLE— PERFORMANCE MEAN, MEDIAN AND NUMBER OF FUNDS BY INDEPENDENT FACTOR AND CLASS

89

DataProces- Number 5 Years

Independent sing of Mean MedianFactor Code Funds Class % %

5ect. Ques.A 1 9 19 1 10.1 11.1

19 2,3,4 11.8 12.330 , 5 11.7 10.8

A 2 10 39 1 11.4 11.330 2,3,4,5 11.7 11. 3

A 3 ' 11 23 1,2 11.8 11. 915 3 10.1 10.930 4,5 12.0 11.3

A 4 12 19 1 11.2 11.923 2,3 13.3 11.627 4,5 10.3 11.0

B 1 13 15 1,2,3,4 10.9 9.853 5 11.6 11.3

B 2 14 31 .1,2,3,4 11.6 11.337 5 11.4 11.1

B 3 15 26 1 11.6 11.520 2 11.8 11.522 3,4,5 11.0 11.1

B 4 . 16 13 1,2,3,4 10.5 9.755 5 11.7 11.6

3 "Up" Years Mean Median % %

23.629.428.1

23.6 27.125.6

26.429.1

25.626.1

29.826.326.4

27.225.623.8

28.431.024.0

27.126.723.7

27.5 27. 6

23.725.7

27.627.5

24.426.5

26.8 29.1 26.9 :

24.226.3 25.6

26.927.7

23.625.6

2 " Down" Years

Mean Median % %

-7.210.0-8.7

-7.9-8.8—8.6

-7.5-9.6

-7.1-10.0

•10.310.2-6.4

-11.6—8.8-6.4

10.0 — 8 = 4 -7.4

—8.8-7.3-6.3

-9.4—8.3

—8.8-7.9

00 00 I I -8.4

-8.1-7.5 -9.5 —8.9

-7.5-7.7-9.0

-9.4—8.3

—8.9 -7.9

DataProces- Number 5 Years^

Independent sing of Mean MedianFactor Code Funds Class % %

Sect. Ques.B 5 . - 17 30 1,2 10.3 919

38 3,4,5 12.4 11.9B 6 18 34 1,2,3,4 12.8 12.0

34 ' ' 5 10.2 10,1B 7 19 23 1 12.8 12.0

20 . 2 10.1 10.7.25. 3,4,5 11.4 1 1 6

B 8 20 10 1,2,3,4 13.8 12 i 358 5 11.1 11,0

B 9 21 32 1,2 11.2 m o15 3,4 13.3 11; 920 ' : 5 9.8 10,2

B 10 22 25 1 11.9 12.017 2 12.2 m o25 '3,4,5 10.2 10.3

C 1 23 53 1,2 11.2 11.116 3 12.8 12.2

C 2 24 23 1,2 12.7 11,346 ' 3 11.0 11.3

C 3 25 26 1 13.0 12.743 2,3 10.6 11.0

3 "Up" Years Mean Median % %

2 "Down" Years

Mean Median % %

26.7 25.3 -10.1 -9.028.2 25.9 -7.4 -7.031.3 26.9 -9.8 -9.4"23.8 23.5 -7.3 -7.529.9 27.2 -8.4 —8.825.0 24.2 -8.7 —8.027.4 25.6 -8.5 -7.834.3 27.2 -10.8 -12.826.4 24.4 -8.2 —8.025.5 23.8 -7.0 -7.033.5 30.1 -11.0 -11.625.3 25.0 ' -9.8 -9.026.9 24.4 — 6.9 -7.129.0 26.5 —8.8 —8.426.2 25.6 -9.8 -8.827.0 24.9 -8.6 -8.129.1 27.2 —7.8 -8.530.7 26.5 -9.5 -9.725.9 24.4 -7.9 -7.530.4 27.2 -8.4 ' -8.525.8 24.3 -8.5 -7.9

H

DataProces- Number 5 Years,

Independent sing of Mean MedianFactor Code Funds Class % %

Sect. Ques.c 4 26 13 .1 8 .3 9 .8

56 2 ,3 12 .3 11 .9

c 5 27 24 1 ,2 12 .6 11 .645 • 3 11 .0 1 1 .1

c 6 28 2 1 13 .6 13 .61 2 15 .0 15 .0

66 3 1 1 .4 1 1 .1

c , 7 29 42 1 ,2 12 .1 11 .927 3 10 .6 11 .0

c 8 30 25 1 1 1 .8 11 .528 2 11 .1 11 ,516 3 1 1 .8 10 .6

c 9 . 31 24 1 ,2 9.8 9 .9' 45 3 12 .5 12 .0

c 10 32 48 1 11 .7 11 .121 2 ,3 11 .3 11 .6

c 11 33 0 1 _

3 2 17 .1 16 .766 3 11 .3 1 1 .1

C 12 34 3831

12,3

11.8 12.011.2 11.0

2 "Down"3 "Up" Years Years____Mean Median Mean Median% . % % %

2 1 .8 22 .6 - 9 . 0 —8 .528 .9 . 26 .5 —8.3 —8 .0

3 0 .9 2 6 .4 - 9 . 8 - 9 . 025 .8 24 .0 - 7 . 7 - 7 . 8

30 .5 30 .5 - 7 . 5 - 7 . 54 0 .4 4 0 .4 - 1 4 . 8 - 1 4 . 827 .3 25.3 . - 8 . 4 —8 .0

27 .8 26 .0 - 7 . 6 - 7 , 527 .1 2 4 .8 - 9 . 8 - 1 0 . 6

27 .2 24 .4 - 7 . 4 - 6 . 726 .2 25 .3 —8.0 - 8 . 53 0 .4 3 2 .1 - 1 0 . 9 - 1 0 . 9

2 2 .4 20 .1 - 6 . 5 - 6 . 830 .3 27 .2 - 9 . 5 - 8 . 8

27 .6 25 .6 - 8 . 2 - 7 . 927 .4 25 .7 - 9 . 0 - 8 . 4

4 1 .4 38 .4 - 1 1 . 7 — 10 .62 6 .9 25 .3 — 8 .3 - 7 . 9

2 9 .4 27 .2 - 9 . 8 - 9 . 325 .2 24 .0 - 6 . 7 - 6 . 5

DataProces­ Number 5 Years-

Independent sing of Mean MedialFactor Code Funds Class % %.

Sect. Ques.C 13 35 31 1 10.5 9.9

38 2,3 12.4 11.9C 14 36 0 1 _ _

0 2 -

69 . 3 11.5 11.3C 15 37 8 1,2 11.8 12.8

61 3 11.5 11.1Percent 52 16 1 9.1 9. 7Yearly- 29 : 2 11.8 11.3New Cash. 24 3 12.9 12.7Date 6 17 1 11.0 9.8Shares 36 2 12.7 12.5Offered 16 3 9.5 10.4Load Versus 7 52 . 1 12.0 11. 7No-Load 17 2 10.2 9.7Incentive 8 5 1 15.7 12.9Fee 64 2 11.2 11.0Average 9Asset Value

34 1 10.9 10.835 2,3,4,5 12.2 11.3

3 "Up" Years Mean Median % %

26.2 23.328.6 26.3

27.5 10.923.5 23.228.1 26.323.1 21.826.7 26.331.5 30.427.4 26.530.3 27.821.5 22.128.7 26.523.9 19.934.0 26.527.0 24.927.6 26.827.5 24.8

2 "Down" Years

Mean Median % %

-9.3 -8.8-7.8 -7.8

—8.4 —8.1-3.8-9.0

-5.0-8.8

-8.5-7.2-9.8

-8.0-6.9

-10.1— 9.6— 8.8 -6.3

-9.3-8.5-6.4

-8.8-7,2

—8.0 — 8.4

-6.7-8.6

-6.0-8.5

1 1

H 00 -9.0

-6.9

APPENDIX K '

PERFORMANCE TABLE BY THIRDS FOR ALL PERIODS

94

A. 5 Years (Data Processing Code No. 2) 1965-1969

Performance

First Third Middle Third Last Third

Number of Funds

232323

Total 69

Mean_%

17.111,36.211.5

StandardDeviation

%

4.4.9

3.15.5

Mean Range% . Max.-Min.

16.6 29.4 to 12.811.3 12.7 to 9.87.4 9.7 to -4.4

11.3 29.4 to 4.4

B. 3 ,fUp" Years (Data Processing Code No. 3) 1965, 1967, 1968 First Third 23 39.8 8.9 38.4Second Third 23 25.6 1.6 25.7Last Third

Total2369

17.227.5

3.58.5

62.0 to 29.628.9 to 22.8

17.8 22.6 to 8.725.7 62.0 to 8.7

C. 2 "Down1" Years (Data Processing Code NO. 4) 1966, 1969 First Third 23 -2.1 3.6 -3.6Second Third 23 / -8.2 1.2 -8.1Last Third

Total2369

-15.0-8.4

3.16.0

6.3 to -6.0-6.3 to-10.9

-14.1 -11.2 to-22.5-8.1 6.3 to-22.5

APPENDIX L

COMPUTER RUN - FUND PERFORMANCE AND RANK

96

L - 1

9 a N K I D F U N O N A M EO a T f S h R S . O F F E R E D

i n v e s t m e n ta d v i s o r Y E A R

L O A U ' F U N O

I N C f m Tf e e

1 9 6 5a s s e t s

1 5 1 P R I C E T R N 1 R P R I C E - 6 0 ■ ? . 92 2 1 E N T E R o R I S E 2 s h a r h l d r s 6 2 1 1 63 , 5 6 S E C U R I T Y E . 1 S E C M G T ■ „ 6 3 ■- 2 • 14 6 2 V A L U E L I N E , 2 ■ r e r n h a r d 5 6 ■ '? 2 05 6 5 V E N T U R E 5 E 2 V E N T U R E . 6 6 . ? 16 1 5 C R U - v N w U/\ 2 5 E C U R I T I S 6 9 ; 2 27 5 5 S C U U D E R S P 2 S S C L A R K . 5 6 2 3 18 3 9 M U T U A L S E C ' 2 M U T U A L S C , 6 1 1 2 19 3 5 K ' N I C * E R 8 G 2 K P E T T I T . 5 3 - 2 4

1 0 1 1 C O L O N I A L E 1 C O L M G T 6 6 " 2 11 1 4 5 0 T C 2 R E V I E W M G 5 6 2 11 2 6 V I E m P l E T O n 2 T E M P L E T O N 5 4 2 . 41 3 2 9 I N V R E S E A R 2 I N V R E S R C 5 9 1 2 21 4 5 4 K E v E R F 1 R E V E R E M G 5 9 ; ? 41 5 6 3 V A N O E R H I L T 2 : V A h u E R H L T 6 4 2 • 11 6 • 2 7 . I M P E R I A L G 2 . I M P E R I N V • 6 3 2 21 7 6 7 W E S T E R N I N 2 I N V S T M G T 6 0 2 21 8 6 8 vi I n i j S O R 2 W E L L I N O T N 5 9 1 7 41 9 6 1 V A L U E L I N E 2 B E R N H A R D 5 0 . 2 1 32 0 9 ■ C H E M I C A L 3 E O E R S T A O T 3 8 1 ? 3 2 92 1 3 1 J O H N S O N 3 f) J O H N S O N 4 7 9 4 12 2 4 4 o p r e n h e i m e 2 . O P P E . N M G r 5 9 I • 2 82 3 4 3 N E K T O N 1 N E W T U N C O • 6 0 2 - 22 4 . 3 A N C H O R G R 2 . A N C H O R c r 5 2 2 1182 5 ' 3 0 1 V E S T . 2 I V E S T I N C : 5 7 ' 1 , 5-2 6 2 6 M E i) b (3 G 0 R U . 2 I N V C U l i S L , 6 4 1 . 42 7 1 7 U E V E G H 2 Ivu S T W I N ■ - t>3 2 2 02 8 2 A ;-1ER N A T G 2 S E C M t i T R 6 7 , 2 42 9 5 0 P R I C E T R G \ 2 R P H I C E M 5 0 2 1 2 93 J 2 2 F E o L R A T t U 2 O n E E L E V N 6 7 1 • 2 83 1 3 2 K E y S T O n l *S 3 K E Y S C O S T 3 5 2 . 2 2 63 2 1 3 C U M S T K S B 1 S T A T E H M D 6 2 2 33 3 1 ' A M E R I N V E S 2 C m E S T h U T T - 5 8 . 2 ' 2 5.34 4 9 P L A N N E D ' 1 B U R G E S S L . 61. 2 13 5 ■ 1 6 D E L A W A R E . 3 D E L M G r 3 7 . ? 1 8 6

1 9 ' > 9 A V G ■ A S S E T P F R C F M T " y « L Y 0 F 0 m M E A NA S S E T S • A S S E T S C L A S S M E - ; G a S M P E R F O R M A N C E

4.3 ' 2 . ' 7 . 9 2 9 . 3 77 7 1 3 8 R 4 . . 3 h U 6 . 2 7 . 1 S1 3 % ' 6 9 2 - 4 K . 9 • . ' 2 3 . 7 72 S 0 ■ 1 3 5 3 . ' 2 9 . 2 2 1 . 1 3

2 2 1 - 7 „ ? 2 0 . 4 41 3 * I . 2 2 . 6 1 6 . 0 5 .

1 9 0 1 1 0 ' 3 ‘ • 2 1 . 7 . • 1 7 . 3 14 3 1 1 1 4 . 6 1 6 . 6 4 ,

1 2 5 % 6 . 6 1 6 . 7 61 2 9 G S 2 3 9 . 0 1 6 . 7 4

3 . . 2 . 1 M . l 1 6 . 6 97 6 1 - 5 . 2 1 6 . 5 7 . ,6 4 1 H . O 1 5 . 2 6 •

. 2 1 1 3 1 2 0 . 0 • ) 5 . 0 22 0 1 0 1 3 4 . 3 1 4 . 9 01 % 1 0 1 ' 2 h . n 1 4 . 9 09 , 6 1 1 A . 6 1 3 . 5 7

, 3 0 7 1 9 0 ' 3 1 7 . 5 1 3 . 5 36 h 4 0 2 2 0 . 9 I 3 . 4 v

5 7 3 ' 4 5 1 4 - 1 . 1 1 2 , 9 h1 4 3 9 2 2 1 4 . 9 1 2 . 9 3

' 3 1 7 1 7 2 3 ' 3 0 . 6 1 2 . H y .1 6 9 1 • 2 7 . 6 1 2 . 8 1

5 1 9 . 3 1 8 4 ■ 1 9 . 1 , 1 2 . 7 12 9 6 1 5 1 3 ' 9 q . ] 1 2 . 6 2

1 3 9 1 1 3 . 7 1 2 . 2 95 9 3 9 2 1 1 , 3 1 2 . 2 2

7 6 1 — , 4 1 2 . 1 *6 . 1 3 3 7 1 4 9 0 . 9 1 2 . 0 3

1 6 1 2 1 9 . * ) 2 . 0 0 -6 1 V 4 ] % 4 9 , 6 1 1 . 9 3

2 6 1 4 1 ■ 2 8 . 7 1 1 . 9 3. 2 9 5 1 6 0 3 3 1 . 3 . 1 1 , 9 2

3 2 1 ‘ 1 2 . 8 1 1 . 5 7 .4 4 6 3 1 6 4 ' 7 . 7 1 1 . 2 7 ,

Ir -1 1— Continuedd a t e S h R S i n v e s t m e n t l o a d I N C E N T | R 6 5 1 9 6 9 A V G A S S E T P E P C F N T Y R L V G F Q M M E A NR a n k I Q F U N D N A M E o f f e r e d A D V I S O R . Y E A R F U N D F E E A S S F T S A S S E T S / a s s e t s . C L A S S N E W C A S H P E R F O R M A N C E

3 6 4 1 N A T S E C O R 3 N A T R E S C 4 0 2 1 4 5 ‘ 2 5 9 2 0 2 . 3 ' " 1 . 0 . 1 1 , 0 83 7 3 6 L E X I N G T O N 3 L E X s e c 4 1 . 1 . 2 3 3 1 1 6 . 7 4 2 ■ 1 6 . 0 1 1 . 0 43 8 1 0 c o l u n i a l g 2 ■ C O L M O T 4 9 ? • 4 4 7 3 5 8 - 1 . 7 . 1 1 , 0 13 9 5 2 P u t n a m O R 2 • P U T M A M M G 5 7 ‘ 2 . 2 8 0 6 b ? ’ 4 7 3 8 . 3 1 0 . 9 240. . 3 7 M A S S I N V G 3 M A S S F I N 3 4 ■ 2 7 U 1 2 5 2 9 8 1 1 . 5 1 0 . 7 54 1 . 3 4 K E Y S T O N E s 3 K E Y S C O S T 3 5 I 2 1 n 6 , 1 7 3 1 3 9 - . 9 1 0 . 4 94 2 •1 8 O R Y F U S 3 ' D R Y H U S C R 5 1 . 2 ’ 8 0 0 2 3 9 8 - 1 5 9 9 . 1 3 . 7 1 0 . 3 ?4 3 . 4 8 . P I O N E E R E N 2 • P I O N M O T . 6 2 ' 2 1 . 6' ' 4 2 4 . 9 1 0 . 1 04 4 4 0 L H A H S O N ; 1 . B A U S O N I N 6 0 2 5 3(1 1 8 '' ,• 2 5 . 2 , 1 0 . 0 34 5 5 9 t e c h n o l o g y 3 . S U P I N V 4 8 2 3 9 5 6 3 1 . 5 1 3 . 9 . 8 64 b 0 9 ; a/ U R T M 1 W O R T H . 6 2 ; ■ ? . 1 1 1 - 1 1 . 4 9 , 7 6Hi 6 6 V I K I N G G R O 2 P I O N F I N ' 6 3 2 1 1 1 - 9 . 0 9 . 7 34 8 2 0 E N E R G Y 2 r s a m u e l 5 5 2 3 5 1 3 5 ■ 8 5 ' 1 8 . 6 9 . 6 84 9 5 3 P U T N A - I I N V 3 p u t n a m m g 6 4 • 2 2 6 7 3 1 u • 2 8 8 * 4 - 8 . 1 9 . 4 95 0 2 4 F R A I n M I N c . 3 f r a n k o i s 4 8 • , 2 6 1 3 1 0 . - 7 , 7 9 . 2 75 1 3 3 : K E Y S T ( ) N E K 3 k e y s c u s r ‘ 3 5 1 • 2 1 3 ? 2 9 7 ' 2 1 4 8 . 5 9 . 2 15 3 6 4 V A N G U A R D 1 • V A N G U A R D 6 6 1 2 1 2 2 6 . 8 8 . 5 2 .5 3 5 8 S T E I N R O E • 2 . s r h q f r n • 5 8 2 ? 4 7 1 2 5 8 6 ' . 1 2 . 8 8 e ? 65 4 1 4 C O N C O R D 2 . C H A U V I S 6 5 2 2 . 1 3 2 1 5 . 4 7 . 9 95 5 3 8 M I F G R O W T H ‘ I ‘ H E R I T A G E 6 1 1 • ? 1 • ? 2 " 1 1 3 5 . 7 7 . 8 25 6 2 5 G R O W T H I N O ■ 3 »v M L A I R 6 9 2 ? 3 7 44 4 0 - 4 , 4 • 7 . 5 35 7 7 C A P I T A L I N . 3. C A P S P O N S 6 2 . 1 .. 2 1 4 3 2 0 , 6 7 . 4 95 8 2 8 I N T E G M N O R 1 i N T t G O N , 6 4 1. 2 • • 3 i ' 9 , 6 1 5 . 8 7 . 3 6

■ 5 9 5 7 , S T E I N R O E ■ : ■ H ■ S T R Q f r n • 6 3 2 . 2 2 2 " 1 6 ' . - . 1 9 ' - 1 4 , 0 6 a ib O 4 6 P E N N S O O A R • 2 .. P E N N S O ■ 5 7 . '• 2 ' .2 ’ 7 6 ■■■'. 1 5 0 '■ 1 1 3 8 . 9 5 . 5 3o l 4 7 p i l g r i m . 1 P I L G R I M ■ 6 4 ' ' 1 ? . ■ 1 1 2 - 1 3 3 . 0 5 , 5 1• 0 2 1 9 E G R E T G H 1 E G R E T M O T . . 6 5 1 2 4 ' 3 0 ' 1 7 ? % . ? . . 5 , 2 76 3 . 1 2 • c o m m e r c e 2 F U N D S I N C 4 9 1 " ' 2 7 9 .. 9 3 8 8 - 2 . 4 5 . 2 50 4 5 6 E A C U N M I L 1 ■ B E A C O N M L 6 4 2 ? 1 1 - 4 . 6 4 . 4 86 5 6 B O S T O N C O M ' 2 B O S T O N M G 5 2 . 1 2 6 1 .48 5 4 - 9 . 9 4 . 0 56 6 4 2 N E A M U T U A L 1 E D U C M O T 6 8 • 1 2 1 • 1 6 3 4 . 8 3 . 6 46 7 4 0 N A S S A U • ■ 2 C L R K 0 0 0 0 6 9 '■ 2 . 2 . ■ 6 8 7 1 ’ ■ 3 . 0 3 . 0 16 6 2 3 F I R S T P A R T 1 A M E R O E M 6 7 2 2 ' 1 4 1 2 3 , 0 2 . 6 66 9 8 c a p i t a l s h 3 C a P S P O N S 6 0 1 2 1 4 1 6 1 1 0 1 « 1 o # o - 4 . 3 8

C O M P A f < A H u £ M A R K E T P E R F O R M A N C E = ' 5 . 3 4

L - 2

R A N K ID. F U N D N A M ED A T E S H R S O F F E R E D

I N V E S T M E N TA D V I S O R Y E A R

L O A DF U N D

I N D E N TF E E

1 9 : 6 5A S S E T S

' 1; 2 1 E N T E R P R I S E 2 S H A R H L D R S ■ 6 2 1 62 6 5 V E N T U R E S E • 2 V E N T U R E - ■ 6 6 1 2 13 6 2 V A L U E L I N E , 2 . P E P M H A R D . 5 6 1 2. 2 04 5 6 S E C U R I T Y E 1 S E C M G T 6 3 2 1. 5 5 1 P R I C E T P N. 1 : R P R I C E ' 6 0 2 96 1 6 c r o w n w ’d a 2 S r . C U R I T I S 6 9 2 27 3 9 M U T U A L S E C 2- M U T U A L S C 6 1 2 18 5 5 S C U O D E ? S P 2 S S C L A R K 56. . 2 3 1q 6 3 V A N D £ 5 9 1 L T : 2 v a n o e r r l t 6 4 2 .. 1

1 0 5 4 R E V E R E i: R E V E R E M-G 5 9 2 4i t 1 1 C O L O N I A L E i C O L M G T 6 6 1 ■ 2 . ■ 11 2 6 9 W O R T H - i W O R T H 6 2 2 , 11 7 1 A M E ' R T N V E S 2 C H E S T N U T ! " 5 8 .. 2 2 51 4 1 4 C O N C O R D 2 C 0 A D V I S 6 5 2 11 5 3 2 K c y S T O N E S 3 K E Y S C U S T 3 5 1 2 2 2 61 6 6 1 V A L U E L I N E . 2 B E R N H A R D 5 0 1 2 1 31 7 4 5 9 T C 2 R E V I E W M G . 5 6 2 11 * 2 A M E R M A T G 2 S E C M G T R 6 7 1 2 41 9 4 8 P I O N E E R E N 2 . P I O N M G T 6 2 2 12 0 2 7 I M P E R I A L G . 2 I m D E R I N V 6 3 • 2 22 1 6 7 W E S T E R N I N ‘ 2 I N V S T M G T 6 0 . 2 22 2 3 5 K N I C K E R B G 2 K P E T T I T 5 3 2 42 3 4 9 . P L A N N E D 1 P U R G E S 5 L 6 1 2 . 12 4 7 A N C H O y GP. 2 A N C H O R C R 5 2 1 2 . 1 1 32 3 4 4 O R R f N H E I N E 2 O P P F N M G T . 5 9 1 2 32 6 ' 2 8 . T N T E G O N G R 1 I N T E G O N 6 4 2 32 7 2 9 I N V P F S 6 A R . 2 I N V R E S R C , 5 9 1 2 22 8 4 3 N E W T O N 1. . N E W T O N C O • 6 0 2 22 9 5 2 P U T N A M - O R 2 P U T N A M M G 5 7 2 2 8 03 0 6 4 v a n g u a r d 1 ' V A N G U A R D 6 6 1 . 2 1 ,3 1 3 0 I V E S T , ' 2 I V E S T I N C 5 7 ■ ' 1 53 2 5 8 W I N D S O R . - 2 W E L L I N G T N . 5 9 • ■ 1 7 43 3 2 6 H E D 9 G G O R D 2 I N V C O N S L 6 4 1 43 4 2 2 F E D E R A T E D 2 O N E E L E V N 6 7 2 . 83 5 3 3 K E Y S T O N E K 3 K E Y S C U S T 3 5 1 2 1 3 2

1 9 . 6 9 A V G A S S E T ; P E R C E N T Y P L Y G E O M M E A N5 S F . T S A S S E T S ’ C L A S S N F W C A S H P E R F O R M A N C7 7 1 3 8 8 4 3 8 . 6 6 2 . 0 4

2 2 1 ■ ■ - 7 . 2 5 5 , 8 12 5 0 ■. 1 3 5 - 3 2 9 . 2 5 3 . 0 21 3 8 6 9 ' ■ 2 3 3 . 9 4 9 . 7 94 3 2 6 2 7 . 9 • 4 8 . 3 71 3 8 1 2 2 . 6 4 4 . 7 84 3 ‘ 1 . 1 4 . 6 4 4 . 5 0

1 9 0 1 1 0 ‘ 3 • 2 1 . 7 - 4 4 , 3 62 0 1 0 1 • 3 4 . 3 4 1 . 0 02 1 1 3 1 2 0 . 0 4 0 . 4 1

1 2 9 6 5 2 3 9 . 0 3 3 . 4 21 . 1 1 ' - 1 1 . 4 3 8 . 4 0

2 9 5 1 6 0 3 ‘ 3 1 , 3 3 3 . 8 63 2 1 1 5 , 4 3 3 . 1 3

6 1 0 4 1 8 4 9 . 8 3 3 . 0 26 8 4 0 2 2 0 . 9 3 2 . 8 3

. 3 . 2 1 ■ 3 . 1 . 3 2 . 7 67 6 ■- 1 - . 4 3 2 . 6 96 ■’ 4 1 2 4 . 9 3 2 . 4 7

1 8 ;• i d ’ 1 2 3 . 0 3 2 . 3 89 6 1 1 3 . 3 3 1 . 4 1

1 2 8 1 . 6 . 6 3 0 . 0 93 2 - ' 1 1 2 . 8 2 9 . 5 6

5 1 9 3 1 8 4 1 9 . 1 2 8 . 8 73 1 7 1 7 2 3 3 0 . 5 2 8 . 4 9

9 6 1 1 5 . 8 2 7 . 2 06 4 . 1 8 . 0 2 7 . 1 3

1 6 9 1 2 7 . 6 2 7 . 1 26 6 7 4 7 3 4 8 . 3 2 6 . 7 3

2 2 1 6 . 8 2 6 , 5 22 9 8 151 ' : 3 3 3 . 1 2 6 . 5 03 0 7 1 9 0 3 •• 1 7 . 5 2 6 . 5 0

1 3 9 . 1 1 3 . 7 . . 2 6 . 3 51 6 ' • 1 2 1 2 . 3 2 6 . 2 7

2 9 7 2 1 4 3 8 . 5 2 5 . 6 5

.vovo

■ L - 2— ContinuedORTH S HRS ' I N V E S T M E N T LORO I N C E N T 1969 RVG ' . R S S E T . P E R C E N T Y R L Y ' GEOM HERN

R A N K I D F U N D N A M E O F F E R E D . A D V I S O R • Y E A R F U N D • F E E A S S E T S A S S E T S . A S S E T S C L A S S .. N E W C A S H , P E R F O R M A N C E3 6 1 6 D E L A W A R E ' ■ 3 ' D E L M G T , 3 7 ' ' 1 2 • 1 8 6 4 4 6 ' 3 1 6 ' 4 7 . 7 2 5 o 6 13 7 3 4 K E Y S T O N E S 3 K E Y S O U S T 3 5 • 1 2 1:06 1 7 3 1 3 9 3 - . 9 2 4 . 8 93 8 3 6 L E X I N G T O N • 3 . L E X S E C 4 1 1 • 2 '33 1 1 6 ' 7 4 2 1 6 . 0 2 4 . 8 23 0 1 7 O E V E G H > 2 W O S T W I N 6 3 . 2 2 E O 5 9 3 9 2 1 1 . 3 2 4 . 4 44 0 1 0 C O L O N I A L G 2 C O L M G T 4 9 1 2 :44 7 3 5 8 . 2 - 1 . 7 2 4 , 2 7 .4 1 4 1 N A T S E C G R 3 N A T R E S C • 4 0 . 1 2 1 4 5 2 5 9 ' 2 0 2 3 1 . 0 * 2 4 . 0 44 2 6 0 T E M P L E T O N 2 T E M P L E T O N ' 5 4 1 2 4 7 6 1 - 5 . 2 . 2 3 . 8 94 3 . 1 3 C O M S T K S B .1 S T A T E 3 N D 6 2 . 1 ' 2 ‘ 3 2 6 1 4 1 2 8 . 7 ‘ 2 3 . 7 04 4 2 0 E N E R G Y 2 R S A M U E L 5 5 : 2 2 3 5 1 3 5 8 5 2 1 8 . 6 2 3 . 6 44 5 6 6 V I K I N G G P O 2 P I O N F I N • 6 3 i • 2 ; 1 1 1 • 1 - 9 . 0 2 3 , 3 14 6 ' 7 C A P I T A L I N 3 C A P S P O N S ' 6 2 i 2 : i ' 4 3 1 2 0 . 6 2 2 . 8 54 ? 5 9 T E C H N O L O G Y . 3 . . ' S U P I N V . 4 8 i 2 3 9 5 • 6 3 1 ’ 5 1 3 ' . 5 * « 2 * 2 2 . 6 04 8 1 8 D R Y R ' J S 3 D P Y F U S C R 5 1 i 2 . 8:00 2 3 9 8 1 5 9 9 . 5 . ■ 1 3 . 7 ; 2 1 . 6 24 9 . 9 C H E M I C A L 3 E B E P S T A O T 3 8 i . 2 3 2 9 ' 5 7 3 4 5 1 . 4 - 1 . 1 2 0 . 9 35 0 4 6 P E N N S O U A R 2 P E N M S O 5 7 2 2 7 6 1 5 0 • ■ 1 1 3 3 3 . 9 . 2 0 . 2 75 1 3 1 J O H N S O N . 3 0 J O H N S O N 4 7 2 2 4 1 1 4 3 9 2 ' 2 • 1 4 . 9 . 1 9 . 9 45 2 5 0 n R I C E T R G . 2 R P R I C E M 5 0 • 2 2 1 2 9 • 6 1 3 3 7 1 . 4 2 0 . 9 1 9 . 8 45 3 4 7 ° ' T L G R I M • . 1 P I L G R I M 6 4 • 1 2 1 1 2 ' ' 7 . ' 1 3 3 . 0 . 1 9 . 6 55 4 3 8 M T F G R O W T H ' 1 H E R I T A G E . 6 1 1 2 1 2 2 • 1 1 1 3 5 . 7 1 9 . 6 05 5 4 0 L B A O S O N ' 1 0 A C S O N I N 6 0 2 2 . 5 3 0 1 8 1 . 2 5 . 2 . 1 9 . 2 79 6 5 3 S T E I N R O E 2 S T R O F P N . 5 8 2 2 4 7 1 2 5 8 6 2 1 2 . 8 1 8 . 7 35 7 2 4 F R A N K L I N C ' 3 p p A N K O T S 4 8 . 1 2 6 1 3 1 0 1 7 . 7 1 8 . 5 75 8 3 7 M A S S I N V G 3 M A S S F I N 3 4 •,■ 1 . 2 . . 7 1 1 . 1 2 5 2 9 8 1 ' ' 5 . 1 . 5 " 1 7 . 8 4. 5 9 1 2 ' C O M M E R C E 2 F U N D S I N C • 4 9 1 2 7 9 9 3 8 6 2 ' - 2 . 4 1 7 . 8 2 .

. 6 0 5 7 S T E I N R O E ' 2 S T R O F P N 6 3 2 2 .22 - 1 6 1 9 . 1 - 1 4 . 0 1 7 . 4 16 1 - 5 3 P i J T N A M I N V ■ " 3 P U T N A M M G . ' 6 4 ■ ‘ V ' 2 2 6 7 3 1 0 2 8 8 4 ” 3 . 1 1 7 . 0 46 2 2 5 G R O W T H I N C W B L A I R ■ . 6 9 2 2 . 3 7 4 4 4 0 '■ 2 - 4 . 4 1 6 . 3 16 3 1 9 9 G ? E T G R E G R E T M G T 6 5 . i 2 4 3 0 1 7 1 2 9 . 2 1 6 . 2 46 4 5 B - A C O N M I L * 1 D E A C O N H L 6 4 2 . 2 1 . 1 . 1" 1 - 4 . 6 1 4 . 6 36 9 2 3 F I R S T E A R T A M F P G E M 6 7 - 2 2 1 ' 4 3 • 1 2 3 . 0 1 4 . 3 166 4 2 . N E A M U T U A L 1 E D U C M G T 6 8 1 ' .. 2 •' 1 ' 1 6 ' 9 '' 1 • . 3 4 . 8 1 2 . 8 2 .6 7 ' 4 0 N A S S A U ? C L R K D O O G 6 9 - 2 • ? : • : ■ ' 6 • 8 7 1 . • 3 . 0 1 1 . 4 4 .6 8 ' 6 B O S T O N C O M 2 B O S T O N M G . . 5 2 1 ' 2 • . • 6 1 4 8 5 4 2 ' - 9 . 9 : ■ ' 1 1 . 0 66 9 8 C A P I T A L S H . 3 C A P S P O N S . 6 0 1 2 . , 1 4 1 6 1 10.1 3 - 1 0 . 0 8 . 6 8

C O M P A R A B L E ^ A ^ K f T D E R F O R M A N C E = 1 6 . 3 9

100

- '•■ ■■ ~--- DATE SHRS i n v e s t m e n t%ANK ID FUND NAME o f f e r e d . a d v i s o r

1 60 TEMPLETON 2 TEMPLETON2 51 PRICE TR N 1 R PRICE3 31 JOHNSON 3 0 JOHNSON4 9 CHEMICAL 3 e b e r s t a d t5 50 PRICE TR G 2 R PRICE M6 .37 MASS INV G 3 ■ MASS FIN7 29 INV RESEAR 2 INV RESHC8 35 k n i c k e r s g . 2 K PETTIT9 53 PUTNAM INV 3 PUTNAM MG

16 4 D L RABSON 1 BA8S0N INn 24 f r a n k l i n c 3 FRANK DIS12 68 WINDSOR ' 2 w e l l i n g t n13 13 COM STK SB 1 STATE BND14 45 0 T C 2 : REVIEW MG15 17 DEVEGH 2 WD ST WIN16 25 GROWTH IND ' 3 W BLAIR17 18 DRYFUS • . 3 DRYFUS CR18 30 IVEST 2 IVEST INC19 6 BOSTON COM 2 BOSTON MG20 43 ' NEWTON 1 NEWTON CO21 58 STEIN ROE 2 ST RO FRN22 41 NAT SEC GR ■ 3 . NAT RE SC '23 26 HEDBG GORD 2 INV CONSt.24 10 COLONIAL G 2 COL MGT25 22 FEDERATED 2 ONE ELEVN.26 56 SECURITY E 1 SEC MGT .27 59 •TECHNOLOGY 3 SUP INV28 36 LEXINGTON 3 LEX SEC29 44 OPPCNHEIME 2 OPPEN MGT30 27 IMPERIAL G 2 IMPER INV31 16 DELAWARE 3 DEL MGT32 38 MIF GROWTH 1 HERITAGE33 3 ANCHOR GR 2 ANCHOR CR34 66 VIKING GRO 2 PION FIN35 34 KEYSTONE S 3 . KEYS CUST

L " 3/-- —

LOAD INCENT "1965 1969 AVGYEAR FUND . FEE ASSETS ASSETS ASSET!

54 "1 2 4 7 660 2 2 9 43 ’ 2647 2 2 " 41 143 9238 1 2 329 573 . 451

: 50 •2 . 2 129 613 ■ 37134 1 2 : 711 . 1252 98159 1 2 2 6 453 1 2 4 12 ; 864 1 2 267 310 28860 2 2 • 5 ' 30 1848 • - 1 2 6 13 1059 . 1 1 74 307 ■ 19062 1 2 3 26 1456 1 . 2 1 3 . 2 -63 2 2 . 20 59 * 3969 2 . 2 . 37 44 4051 1 2 , 800 . 2398 159957 1 1 . 5 298 15152 1 2 61 48 5460 1 2 2 16 958 . 2 2 47 125 8640 1 2 ■ 145 . 259 20264 2 ' 1 • ’ - 4 13 . 949 1 2 44 73 V. 5867 • 1 2 8 16 1263 , 1 2 1 138 6948 1 2 : 395 ' 631 . 51341 .. 1 2 33 116 7459 1 • 1 ' 28 317 17263 1 2 . 2 18 1037 1 2 186 446 31661 1 2 1 22 1152 1 2 . 1.18 519 31863 1 2 1 1 135 1 2 . 106 173 139.

ASSET. PERCENT YRLY GEOM MEANCLASS . NEW CASH PERFORMANCE

1 ”5o2 6,312 7 09 5.262 14o9 3.114 -1.1 1.884 , 20,9 . 1.185 1.5 -• ,851 8.6 - .581 6.6 - . 784 -8,1 -1,001 25.2 -2.571 7.7 " -3.413 17 o 5 -3.551 28.7 -3.741 8,1 -3.922 11,3 -3.962 -4,4 -4.485 13.7 -4,763 38.1 -5.342 -9.9 -5.731 27.6 -5.752 12.8 -5.813 1.0 -5,931 '' 13.7 -5.992 -1.7 -6.351 ’ 2.8 -6.512 38.9 -6.745 -«2 —6.872 16,0 • -6.903 30.5 • " -7,121 28.0 -7.174 7.7 -7.311 35,7 -7.774 l?.l -7.871 -9.0 -7.943 -.9 -8.13

101

L - 3— ContinuedDATE SHRS i n v e s t m e n t LOAD INCENT " 1965} 1969 AVG ' ASSET PERCENT YRLY g e o m m e a n

Ra n k ID FUND NAME o f f e r e d ADVISOR YEAR FUND FEE a s s e t s ASSETS ASSETS. . CLASS NEW Ca Sh p e r f o r m a n c e

36 20 ENERGY ’ 2 R SAMUEL 55 2 2 . ■ 35 - 135 85 2 Itiob ■ =8.4237 40 NASSAU “ 2 ' CLRK DOOG .. 69 2 2 6 8 7 1 3,0 =8.5338 42 NEA MUTUAL 1 EOUC MGT . 68 • 1 2 ’ 1 16 9 1 34 o 8 -8.8039 67 WESTERN IN 2 INVST MGT 6C 1 2 2. 9 6 - . 1 18,8 -8.82' 4n 57 STEIN ROE 2 ST RO FRN 63 . ‘ • 2 ■ 22 - 16 19 . 1 "14*0 -8.9041 5 BEACON MIL 1 • BEACON HL 64 2 .. 1 1 1 ' 1 • -4,6 -9.15. 42 52 PUTNAM GR 2 PUTNAM MG . 57 2 . 280 667 473 : 4 .8,3 . -9.2343 19 EGRET GR 1 EGRET MGT • 65 2 . 4 30 17 1 29,2 -9.3444 11 COLONIAL E 1 COL MGT 66 • 2 1 129 . 65 2 39,0 -9,6545 61 VALUE LINE 2 BERNHARD 50 1 2 . ' 13 68 40 2 • 20,9 =10*63 .46 49 p l a n n e d ■ 1 BURGESS L 61 1 ■ 2 1 3 2 1 12.8 -10.9147 12 c o m m e r c e 2 FUNDS INC 49 2 79 93 86 2 -2.4 -11*2148 33 KEYSTONE K 3 KEYS CUST 35 2 132 297 .214 . 3 8,5 -11.5849 21 ENTERPRISE 2 s h a r h l d r s 62 1 • 6 771 388 4 38,6 .-11.685 a 7 CAPITAL IN 3 CAP SPONS 62 2 • 1 4 3 1 20.6 -12°1051 23 ■ FIRST PART 1 AMER GEN 67 2 . 1 4 3 1 . - 23,0 -12.70

' 52 47 PILGRIM 1 PILGRIM 64 . 2 ■ 1 12 7 1 ■ 33.0 -12,7053 2 AMER NAT G 2 SEC MGT R • 67 1 2 4 7 6 1 -«4 -12,9554 15 CROWN W DA 2 SECURITIS 69 , 2 . 2 13 8 : 1 22.6 -13.1555 A 6 PENN SQUAR 2 PENN SQ 57 2 76 150 113 3 8,9 -13.32 •56 32 ' KEYSTONE-S 3 KEYS CUST 35 : 2 • 226 610 ' 418 4 9,8 ' -13,6657 64 VANGUARD 1 = VANGUARD 66 2 . . 1 2 2 . 1 6,8 -13,8658 55 SCUDDER SP . 2 S S CLARK 56 ' 2 31 190 110 3 21.7 -14,1459 ■ 1 AMER 1MVES 2 CHESTNUTT 58 2 25 295 • ■ 160 3 31.3 -14.5060 .. 62 VALUE LINE 2 BERNHARD 56 - 2 . 20 • 250 - 135 - 3 29,2 -14,7561 • 54 REVERE 1 REVERE MQ v 59 • 2 : 4 21 13 1 • 20.0 -14.7862 39 MUTUAL SEC 2 MUTUAL SC 61 2 1 4 3 1 14.6 -15.0763 63 VANDERBILT ? . VANDERBLT 64 2 1 20 10 1 34.3 -15,5464 48 PIONEER EN 2 PION MGT 62 2 1 , ' 6 4 1 24.9 -16,6365 28 INTEGQM GR ' 1 . INTEGON 64 1 ■ . 2 : 3 9 6 1 . 15.8 -16.8166 65 VENTURE s e 2 VENTURE 66 ■ , 2 ■ 1 2 2 1 -7,2 ■ -18,20•67 8 CAPITAL SH . 3 CAP SPONS 60 1 • 2 . 141 61 . 101 3 -10,0 -21.1568 14 CONCORD 2 C B ADVIS 65 2 ■ 2 1 3 • . 2 . ’ 1 15.4 -21.1769 69 WORTH V WORTH 62 • 1 . 2 1 1 1 1 -11 o 4 -22.55

COMPARABLE MARKET PERFORMANCE = -9.37

APPENDIX M

COMPUTER RUN - LIQUIDITY OF MUTUAL FUNDSTWO "DOWN" YEARS (B-6) .

103

CLASS12

OBSERVED FREQUENCY TABLE, CLASS

' PERF GRP TOTAL 1 2

22 7 ' 1523 • 11 . 1223 , 16 7

TOTAL ■ 68 . 34 34UNLISTED RESPONSES = 1 '

EXPECTED FREQUENCY TABLE ■. CLASS

.PERF GRP TOTAL 1 2

1 22 11,0 11,02 23 11,5 11.53. 23 . 11.5 11.5

TOTAL 68 34 34

CALCULATED CHI SQUARE = 6.474degrees of freedom = z

C U S S NUM . MEAN STD DEV

1 34 -9,773085 5,3965672 34 -7.3267)2 6.183106

123

RESPONSES 1 •1 2 3 45

COEF VAR ' .•-.552187 -.8439)3

TOTALCLASS 68 . -8,549899 5*930688 -.693656

MEDIAN ■ ; ... MAX MIN QDtV

-9.442806 3.110620 -22.546788 3,432848-7.466170 : 6.313640 1-21.165617 3,080.395

-8.276565 . 6.313640. . -22.546788 3.682179

104

APPENDIX N

COMPUTER RUN - DOW JONES EARNINGSTHREE "UP" YEARS (B-9)

105

CLASS ' RESPONSES 1 1 22 3 43 . 5

OBSERVED FREQUENCY TABLE •

; PFRF GRP \ TOTAL

1 ' 222 223 23

.TOTAL • 67 32 . 15 20

UNLISTED RESPONSES = 2 :

EXPECTED FREQUENCY TA9LE

PERF GRP . TOTAL

1 22 10. 5 4,9 6.62 . 22 10,5 4.9 6.6.3 - 23 11.0 5.1 6.9

TOTAL 67. .32 . 15 20

CALCULATED CHI SQUARE, = 10.27%DEGREES OF FREEDOM = 4

CLASS V 1 3

CLASS' ...1 2 y: 3

6 ‘ 9 .. • 712 •' 5 5

■14 • 1 8

CLASS MUM .MEAN

1 32 25.47.8 0 622 IF 33.5292383 20 25.321109

TOTALCLASS 67 27.233713

STD DEV COEF VAR

10.661142' .4184449.621354 ■ .2869549.739462 / .384638

V 1 0 . 7 1 2 7 4 7 ' : - . 3 9 3 3 6 3 . •

MEDIAN

23.79501630.03732724.952627

, MAX

62.04192355.31015653.022745

... MIN11.44100419.9408568.676124

. QDEV

4.9568968.1117736.554865

2 5 . 6 1 2 9 5 4 . 6 2 . 0 4 1 9 2 8 8 , 6 7 6 1 2 4 ' ■ 6 . 4 6 0 5 1 1 .

106

• APPENDIX O

COMPUTER RUN - LOW EXPENSE RATIO FOR THE FUNDTHREE "UP" YEARS (0-2)

107

C L A S S12

R E S P ON S E Si 23

ORSEPVEO FREQUENCY TABLE ■CLASS

RERF GRP TOTAL • ' 1 2

1 ' 23 9 ■ .142 23 ' 11 12

' 3 23 3 20• T O T A L . 69 • 23 46UNLISTED RESPONSES = 0

rREOUEMCY TABLECLASS

D ERF GRP TOTAL 1 2

1 23 '' 7.7 15.32 2 3 . 7.7 15.33 23 7.7 15.3

'TOTAL 69 23 • 46

CALCULATED CHI SOUARE = . 6.783 DEGREES OF FREEDOM = 2

CLASS N U M MEAN STD DEV ■ ■ COEF VAR

1 23 30. 740696 11.208816 ’• '• . 3675522 46 . 25.937399 ' 10.256731 ,■ .395444

TOTALCLASS 69 27.538498 10.654300 ■ .394150

MEDIAN.• MAX MIN • QDEV '

%6.496272 62.041928 14.306546 7.53263124.359392 • 55.810156 8.676124 . ■ 6.230091. .

25.664631 62.041928 8.676124 ' 6.440127 -

108

APPENDIX P

. COMPUTER RUN - CONCENTRATING FUNDS IN THE BLUE CHIP STOCKS (C-9)

109

CL ASS12

RE S P ON S E S1 23

OBSERVED FREQUENCY TABLE •' ' CLASS

°ERF GRP TOTAL 1 ' 2

1 23 3 • 202 . -23 . . 7 16

. 3 23 14 9

TOTAL 69 . 24 ‘ 45

UNLISTED RESPONSES = 0

EXPECTED FREQUENCY TABLECLASS

PERF GRP TOTAL ' ' 1 ' . 2

1 23 8.0 . 15 .0,2 23 8.0 15.03 23 ; 8.0 • 15.0

TOTAL 69 24 45

CALCULATED CHI SQUARE = 11.883DEGREES QP FREEDOM = 2

CLASS NUM MEAN = STD DEV ■ f

1 . 2 4 22,427677 9.9086742 45 . 30.264269 , 10.340529'

COEF VAR ''

.441806 '

.*341674'

TOTALCLASS 69 2,7. 533493 10..854300 ' . .394150

MEDIAN MAX ' MIN ■ ' QDEV •

20.107096 62.041928 ' 11.064302 ■ ,4.73009427.204521 55.810156 8.676124 . 6.672611

25.664681 62.041928 8.676124 6.440127

no

APPENDIX Q

COMPUTER RUN - POSITIVE CASH FLOW INTO FUNDFIVE YEARS (C-13)

111

CLASS ' RESPONSES1 1. 2 2 3

OBSERVED FREQUENCY TAKLG ' . ..■ CLASS'P E R F G R P T O T A L '• 1 2

1 23 12 112 23 S I B3 . 23 1» 9

. T O T A L . 69 31 39

U N L I S T E D R E S P O N S E S = 0 .

E X P E C T E D F R E O U E N C T T A t i L E .

■ . C L A S S P E R F G R P T O T A L ' 1 - 2

: i 23 10 . 3 . 12.72 23 1C .3 12.73 23 10.3 12.7

T O T A L , 69 31 38

C A L C U L A T E D C H I SOUA. RE = 7 . 9*9D E G R E E S O F F R E E D O M = 2

C L A S S N U m ME A N S f U D E V

1 31 10.453623 5.4958962 38 12.432736 5.253306

T O T A LC L A S S 69 11.543569 ' 5.453249

MEDIAN ' MAX . - • MIN, . OOEV '.9 . 0 6 2 1 8 7 . ' , . 6 3 . 7 6 7 0 5 7 - 4 . 3 0 3 2 0 0 3 . 2 2 3 0 3 8

1 1 . 9 2 7 1 5 8 2 9 . 3 7 0 9 9 5 3 . 0 0 7 1 4 , 1 1 . 9 0 3 3 3 9

11.265109 ; >9.370995 -4.383200 2.*33771

112

APPENDIX R

'COMPUTER RUN TWO MOST IMPORTANT FACTORS

COMPUTER CODE NO.- SINGULARLY 39

113

R -j - 1C L A S S R E S P O N S E S • • '

■■ i r ' v ■3 . 10 . .. .. %

■t ■■ : ■ !! - '

6 1 2 4 5 6 7 9 n 14 15

OBSERVED FREQUENCY TABLE' " ' CLASS. • • ' ■ .

. PERF GRP T O T A L 1 2 : ) 3 ' " 4 ' 5 '6 .

1 42 9 . 1 . 13 9 5 52 41 4 8 12 5 . 4 b3 46 .7 ' 5 - .. ' 13 - ' 4 . B &

TOTAL . .129 2U 14 38 18 17 22

U N L I S T E D R E S P O N S E S = .9

E X P E C T E D F R E Q U E N C Y T A B L E

C L A S SP E R F G R P . . T O T A L ,1 2 3 . ; 4 . $ .6

1 42 6.5 - 4.6 12.4 S .9 5.5 7.22 41 6.4 4.4 12,1 5.7 5.4 7.63 46 7.1 5.0 13.6 6.4 6.1 7.5

. T O T A L . 129 2'o •. 14 38 ' 1 8 ■ 17

calculated chi square = 12.180D E G R E E S OF F R E E D O M = 10

C L A S S N U M ' M E A N 55T U O E V C O t T V A R1 2 v 1 2 . 6 4 6 5 1 2 7 , 4 6 1 9 6 8 . 5 9 0 0 4 22 H . . 1 U . 1 5 4 0 4 9 4 . 3 0 2 5 5 2 • . . 4 2 3 7 2 83 3 8 1 1 , 5 5 0 5 7 7 4 . 9 6 4 7 8 4 , 4 3 1 3 3 74 l b , 1 3 , 4 3 4 2 5 8 4 , 6 9 3 7 6 0 ' . 3 4 9 2 8 35 1 7 1 0 , 1 1 9 1 5 4 . 4 . 2 2 3 2 1 1 . 4 2 7 2 3 1

• 6 2 2 • 9 . 7 0 4 0 6 7 . 4 . 6 3 5 1 3 2 • ■ . 4 9 * 2 2 7

t o t a lC L A S S 1 2 v 11 . 3 3 , 45 o -02167 .476775

MEDIAN MAX MIN QOEV

1 1 . 9 7 9 6 1 6 / . :?9 . 37,1995 ' - 4 . 3 5 3 2 0 0 4 . H 17491 1 . 3 2 4 6 5 5 2 0 . 4 4 3 5 6 4 3 . 0 0 7 1 4 0 2 . 3 4 0 8 9 6n .059446 9 9 e37, ; q q s 2.655025 2 . 085)571 9 . 7 6 2 2 9 0 2 7 . 1 9 7 3 9 3 . ■ • . 7 . 3 6 3 5 9 9 3 . 0 4 6 2 * 9 .0 . 7 5 7 7 4 9 •. 2 0 . 4 4 3 6 6 4 ' 2 . 4 5 5 * 2 6 , 9 . 4 3 1 1 9 1

l . o . 5 3 4 5 0 ' V ■ 1 6 .74 j S ( ) 5 : - 4 . 7 6 3 2 0 0 3 . ( 5 0 1 4 5

1 1 . n 9 ( A 3 9 2 9 . 3 ( . ' 9 9 6 ' ' \ 2 . 6 3 3 3 ) 4

114

R - .2• CLASS ' RESPONSES

1 3 . ' ... :% . . * . :3 . 104 . 12. " \ .. '' / - -5 13 .6 1 2 4 5 6 7. " 9 11; • 14 15.,

OBSERVED FREQUENCY TABLE. CLASS -

PERF GRP TOTAL : 1,, 2 3 4 5 ■ 6

1 40 8 3 11 8 5 52 43 6 4 14 * 9 4 63 46 6 7 13 i . 3 11

TOTAL • • 129 20 . 14 ,: 38 • 18 ... 17 ■ 22UNLISTED RESPONSES ■= 9

EXPECTED FREQUENCY TAHLFCLASS ■

PERF GRP TOTAL .1 2 3 • 4 : 5. . 6

1 ’ 40 6,2 4,3 11,8 5.6 5, 3 6.82 . 43" 6.7 4.7 12.7 6.0 5.7 7.3 :3 .46.. 7,1' 5.0 13.6 6.4 :.6.1 .7.8

TOTAL 129 20 14 38 18 . 17 22

CALCULATED CHI SQUARE = 12.544DEGREES OF FREEDOM = 10

CLASS NUN ■ MEAN STD DEV COEF VAR. MEDIAN' / MAX MIN QDEV

' 1 2 9 30. "?15879 13.633092 .4464Q3 26.815794 - 62.041928 8.676124 ’ 9,7163882 14 24.085748 .' 10.422559 .432727 ' 22.661370 - 55,810156 ‘ ' ,11.441004 • 4,8422603 38 26.333835 10. 093069 . ,376.132 . ■ 24.627909 . 53.022745 ' • 11.064302 6,8820314 18 • 32.939184 10.673642 .324041 28.037294 62.041928 16.308405 ' 8.1506115 , 17 25.594216 10.114572 .395190 23.306163 55.810156 12.815688 5.8199986 22 22.322745 6.533811 .285036 22.724366 33.861822 8.676124 4.616640

TOTALCLASS 129 • 27.0 96988 10.839460 .400026. 24.893303 62.041928 8.676124 ' 6.463303 115

CLASS ” RESPONSES1 32 8; ii ■■■'5 13 .6 1 2 4 5 6 7 9 U 14 15

OSSERVED FREQUENCY TABLECLASS

PERF. GRP TOTAL 1 2 3 4 . 5

1 4 5 • 6 7 .• 15 ' 3 • 6a 4 0 . 5 4 13 6 53 4 4 9 3 • 10 9 6

t o t a l 129 2 0 14 38 18 . 17

UNLISTED RESPONSES = 9

e x p e c t e d f r e q u e n c y t a b l eCLASS

PERF GRP TOTAL ■ 1 2 3 4 !

1 45 7,0 4,9 13.3 6.3 5.'2 40 6,2 4,3 11,8 5,6 5»:3 44 . 6.8 4.8 13.0 6.1 5,1

TOTAL 129 20 14 38 18 1'

CALCULATED CHI SQUARE = ‘ 6o 851d e g r e e s OF freedom , = 10

CLASS NUN! . MEAN STD DEV COEF VAR '

■ 1 2 :, -9»b88237 6.521416 -.7175672 14 -7,523638 4.992746 6636q 83 38 -7,640588 6.153932 - s8 o 54264 18 -10.337793 ■ 3,873156 -*3746605 17 -9,154528 6,837844 -o 7469366 22 -7,388986 6.362716 ■ -.861108

TOTALCLASS 129 -8,385294 6.059174 -.722595

co h-

3

6

22

67 . 76.8 7.522

MEDIAN MAX

-9.277521 -7.229812 -7,820354 =10.615660 -7,941160 -7.794552

5.2603911.1802356.313640 -3.5501173,1106206.313640

MIN QDtV

-21.145070-18.203179'-22.546788-16,809616-22.546788-21.145070

4.0685073.1384253.58i3363,2854354,621516•4.778852

8.423365 . 6.313640 -22.546788 3.9693u0 116

APPENDIX S

COMPUTER RUN TWO MOST IMPORTANT FACTORS - COMBINATION

SAMPLE FOR 3 rrUPrr YEARS

117

f a c t o r . FACTOR NUMBER MEAN STD DEV COEF VAR

2 0 0,0000 • 0,0000 0,00001 3 ’ ‘ 0 0,0000 0.0000 0,00001 4 0 0,0000 0,0000 . 0.0000

5 . 0 ".. 0,0000 0,0000 0,00006 0 0,0000 0,0000 0,00007 0 0,0000 0,0000 0,00008 , 1 , 19,6492 . 0.0000 0,00009 V • 0 . 0,0000 ■ 0,0000 ■ 0,0000

10 1 23,6396 0,0000 0.000011 0 0,0000 0.0000 0.000012 1 32,3793 0.0000 0,000013 1 30.0873 • 0,0000 0,0000H 0 . 0,.0000 0,0000 0,00.0015 .0 0,0000 0,0000 ■ • 0,0000

' 16 . 0 0,0000 0,0000 0.0000I \ 2 - 3 0 0,000.0 0,0000 0.00002 2 4 0 0.0000 ■ 0.0000 0.0 000r, 2 . , 5 0 0,0000 0.0000 0,0000‘j 2 6 0 0.0000 0.0000 . 0.0000% 2 7 0 0,0000 , 0.0000 . 0.0000

2 6 . 0 - 0,0000 0,0000 0,0000• 2 9 0 d.oooo 0,0000 0.0000

i ' 2 10 . 0 0,0000 0,0000 0,00002 11 0 0,0000 0,0000 0,0000

57 2 12 0 0,0000 0,0000 0,00002 13 . 0 0.0000 d.oooo 0,0000

|j ' 2 14 0 0.0000 0,0000 0,00002 15 o 0,0000 0.0000 0,0000

y • ■ 2 16 0 0,0000 0.0000 0,00 0 03 4 .1 . ,8.6761 0.0000 0.0000

. . . 3 , 5 . ; 0 .' 0.0000 • 0,0000 •, 0.00003 ' 6 0 0,0000 0,0000. 0,00003 7 0 0,0000 . 0.0000 0.0000

• 3 8 1 19,8365 0.0000 . 0.00003 9 . 0 0.0000 0.0000 0,0 000

i . 3 10 8 29,4586 : 14,6067 .4958.... 3 ■ 11 .... 0 0,0000 . 0.0000 0,0000

3 3 12 V . 8 ’ 35,3577 11,9807 .33883 .. 13 1 44,4975 0,0000 0.00003 14 . • 0 0,0000 0,0000 0,0000

M E D I A N MAX M I N Q D E V

0 , 0 0 0 0 0 , 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 0o . o o o o 0 , 0 0 0 0 • 0 , 0 0 0 0 0 , 0 0 0 06 , 0 0 0 0 0 . 0 0 0 0 • 0 , 0 0 0 0 . 0 , 0 0 0 0o . o o o o 0 , 0 0 0 0 . 0 , 0 0 0 0 1 OoOOOO0 , 0 0 0 0 0 , 0 0 0 0 . 0 , 0 0 0 0 OoQOOO6 , 0 0 0 0 0 , 0 0 0 0 ■ .; 0 , 0 0 0 0 . • 0 , 0 0 0 0

1 9 *6 4 9 2 . .. 1 9 , 6 4 9 2 . 1 9 . 6 4 9 2 , . 0 . 0 0 0 00 , 0 0 0 0 0 , 0 0 0 0 0 . 0 0 0 0 0 . 0 0 0 0

2 3 , 6 3 9 6 2 3 . 6 3 9 6 2 3 . 6 3 9 6 . 0 . 0 0 0 0o . o o o o 0 . 0 0 0 0 0 . 0 0 0 0 0 . 0 0 0 0

3 2 . 3 7 9 3 3 2 . 3 7 9 3 3 2 , 3 7 9 3 O . n O O O3 0 . 0 8 7 3 3 0 . 0 8 7 3 • 3 0 , 0 8 7 3 0 . 0 0 0 0

0 , 0 0 0 0 0 . 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 06 , 0 0 0 0 0 , 0 0 0 0 0 . 0 0 0 0 o . o o o oo . o o o o ■ • 0 , 0 0 0 0 0 . 0 0 0 0 0 . 0 0 0 00 , 0 000 . 0 , 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 06 , 0 0 0 0 0 , 0 0 0 0 0 , 0 0 0 0 . . o . o o o oo . o o o o 0 , 0 0 0 0 0 , 0 0 0 0 0 . 0 0 0 06 , 0 0 0 0 0 . 0 0 0 0 0 . 0 0 0 0 \ 0 . 0 0 0 00 , 0 0 0 0 0 . 0 0 0 0 ■ 0 . 0 0 0 0 0 , 0 0 0 0d . o o o o 0 , 0 0 0 0 0 , 0 0 0 0 : o . o o o o0 , 0 0 0 0 . 0 . 0 0 0 0 0 , 0 0 0 0 . 0 . 0 0 0 0

. o . o o q o . o . o o o o 0 , 0 0 0 0 ■ 0 , 0 0 0 0o . o o o o o . o o o o 0 . 0 0 0 0 ■ 0 , 0 0 0 06 , 0 0 0 0 0 . 0 000 0 , 0 0 0 0 o . o o o oo . o o o o 0 . 0 0 0 0 0 , 0 0 0 0 o . o o c oo . o o o o 0 . 0 0 0 0 0 . 0 0 0 0 O . n O O Oo . o o o o 0 . 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 00 . 0 0 0 0 0 . 0 0 0 0 0 . 0 0 0 0 0 . 0 0 0 08 . 6 7 6 1 8 . 6 7 6 1 . 8 . 6 7 6 1 O . n O O Oo . o o o o , 6 » o o o o • 0 , 0 0 0 0 .. o . o o o o

1 o . o o o o : 0 . 0 0 0 0 ■ 0 , 0 0 0 0 0 . 0 0 0 0o . o o o o 0 . 0 0 00 0 , 0 0 0 0 0 . 0 0 0 0

1 9 , 8 3 6 5 1 9 , 8 3 6 5 1 9 , 8 3 6 5 . .. 0 . 0 0 0 06 , 0 0 0 0 0 . 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 0

22.8977 5 3 , 0 2 2 7 1 1 . 0 6 4 3 1 4 , 3 8 4 60 , 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 0 0 , 0 0 0 0

3 0 . 1 1 3 2 6 2 , 0 4 1 9 2 4 . 8 9 3 3 8 , 6 9 1 04 4 , 4 9 7 5 4 4 , 4 9 7 5 4 4 , 4 9 7 5 8 , 6 9 1 0

6 , 0 0 0 0 6 . 0 0 0 0 . 0 , 0 0 0 0 0 , 0 0 0 0

118

. FACTOR ‘ FACTOR NUMBER MEAN STD DEV

3 15 0 "0,0000 . 0,00003 16 ; 1 • 32,7589 • 0,00004 5" 0 '0,0000 .. 0,00004 6 O' - 0,0000 0,0000

• 4 7 : . 0 0,0000 ' .. 0,00004 8 . 2 25,5868 . 3,9690

, 4 9 0 0,0000 . • 0,00004 10 . 3 • 20,9128 3,85384 11 0 0,0000 0,00004 12 2 24,5578 1,70794 ■ 13 2 17,7073 - 4,89164 14 • 0 0,0 00 0 0,0000

, 4 15 • 0 0,0000 0,00004 16 0 0,0000 0,0000

s 5 6 . o 0,0000 0,0000I . 5 7 0 0,000 0 ■ 0,00001 5 8 ■ 0 0,0000 0,0000

S • 9 0 0,0 00 0 0,00005 . 10 1 . 23,8851 0,0000

: . 5 •. 11 0 0,0000 . 0,0 000g • 5 12 . r: o 0,0000 ' 0,0000

5 13 : 0 0,0000 0,00005 14 0 0,0000 0,0000

5 .• 5 15 0 0,0000 . 0,0000P ' ■ 5 16 . 0 0,0000. . 0,0000!.| 6 ' 7 1 33,8618 0,0000

6 8 o . 0,0000 ■ 0,0000ii 6 9 0 0,0000 OoOOOOu 6 ‘ 10 0 0,00 0 0 .0,0000

6 11 0 0,0000 0,00005? 6 12. 0 0,0000 0,00005 6 13 - V 0 0,0000 0,0000e . 14 . 0 0,0000 .0,00006 15 0 0,0000 0,0000

E 6 16 ■ 0 0,0000 0,00007 8 1 14,6347 0,00007 9 . 0 0,0000 . 0,00007 10 1 27,1316 0,00007 11 0 0,0000 0,0000

; 7 12 . 0 •0,0000 0,00007 ;• is Z • o 0,0000 ■ 0,0000

COEF VAR

0 , 0 0 0 0 OoOOOO 0 , 0 0 0 0 0 , 0 0 0 0 0,0000 .1551

0,0000 ,1843

0 , 0 0 0 0 ,0695 ,2762

0 , 0 0 0 0 0 , 0 0 0 0 0 , 0 0 0 0 0,0000

. 0,0000 0,0000 0 , 0 0 0 0 0 , 0 0 0 0 0 , 0 0 0 0 0,0000 0 , 0 0 0 0 0,0000 0,0000 0,0000 0,0000

• 0,0000 0,0000 0,0000 0,0000 0 , 0 0 0 0 0 , 0 0 0 0

• 0 , 0 0 0 0 0 , 0 0 0 0 0,0000 0,0000 0,0000 0,0000 0,0000 0,0000 OoOOOO

M E D I A N • m a x M I N q d e v

0 , 0 0 0 0 6 , 0 0 0 0 0 , 0 0 0 0 O o O O O O •32,7589 ■ 32,7589 32,7589 o , 6 o o o

0 , 0 0 0 0 ■ 0 , 0 0 0 0 0 , 0 0 0 0 / 0 , 6 0 0 00 , 0 0 0 0 . 0 , 0 0 0 0 0 , 0 0 0 0 0 . 6 0 0 0• O o O O O O 0 , 0 0 0 0 0 . 0 0 0 0 0 , 6 0 0 025,5868 29,5558 21.6178 0 , 6 0 0 0O o O O O O . 0 , 0 0 0 0 ■ 0 . 0 0 0 0 0 , 6 0 0 0

18,5716 26.3456 17,8212 0 . 6 0 . 0 06 , 0 0 0 0 0 , 0 0 0 0 0 , 0 0 0 0 , 0 , 0 0 0 0

24,5578 26.2657 22,8499 O o O O O O17,7073 22,5989 • 12.8157 . O o O O O O

6 , 0 0 0 0 0 . 0 0 0 0 ■ 0 , 0 0 0 0 0 , 0 0 0 06 , 0 0 0 0 0 . 0 0 0 0 0 . 0 0 0 0 0 , 6 0 0 00 , 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 0 • O o O O O O0 , 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 0 0 , 0 0 0 06 , 0 0 0 0 0 . 0 0 0 0 0 . 0 0 0 0 0 , 6 0 0 00 , 0 0 0 0 0 , 0 0 0 0 0 . 0 0 0 0 0 . 0 0 0 0

. 6 , . o o o o 0 . 0 0 0 0 0 , 0 0 0 0 o . n o o o23,8851 . 23.8951 23.8851 O o O O O O

0 , 0 0 0 0 0 , 0 0 0 0 0 , 0 0 0 0 0 . 6 0 0 00 , 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 0 0 . 6 0 0 00 , 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 0 , 0 , 0 0 0 00 , 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 0 OoOOOO0 , 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 0 0 . 6 0 0 06 , 0 6 0 0 0 . 0 0 0 0 0 . 0 0 0 0 0 . 6 0 0 0

33,8618 33.8618 33.8618 0 , 0 0 0 00 , 0 0 0 0 0 , 0 0 0 0 0 , 0 0 0 0 OoOOOO.0 , 0 0 0 0 0 . 0 0 0 0 0 . 0 0 0 0 O.nOOO6 , 0 6 0 0 0 . 0 0 0 0 0 , 0 0 0 0 0 , 6 0 0 06 , 0 6 0 0 0 . 0 0 0 0 0 . 0 0 0 0 * , 0 . 6 0 0 0 •0 , 0 0 0 0 0 . 0 0 0 0 . . . 0 , 0 0 0 0 0 . 6 0 0 00 , 0 0 0 0 0 . 0 0 0 0 ■ 6 , 0 0 0 0 o . n o o o0 , 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 0 .. 0 , 6 0 0 00 , 0 0 0 0 ' 0 , 0 0 0 0 0 . 0 0 0 0 . o . n o o o0 , 0 0 0 0 0 . 0 0 0 0 0 . 0 0 0 0 0 , 6 0 0 0

14,6347 14,6347 14,6347 o . n o o o0 , 0 0 0 0 0 , 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 0

27,1316 27,1316 27.1316 o . n o o og , o o o o 0 . 0 0 0 0 0 . 0 0 0 0 0 , 6 0 0 00 , 0 0 0 0 0 . 0 0 0 0 0 , 0 0 0 0 • 0 , 6 0 0 0 ■0 , 0 0 0 0 0 , 0 0 0 0 0 . 0 0 0 0 OoOOOO

119

f a c t o r FACTOR NUMBER MEAN STD DEV COEF VAR7 H 0 0,0000 ; 0,0000. 0,00007 15 0 0.0000 • • 0,0000 0,00007. 16 ' o 0,0000 . 0,0000 0,00008 9 0 0,0000 0.0000 0,0000S 10 7 21,7702 6,6936 ,30758 11 0 0.0000 0,0000 0.00008 12 .. . 0 0,0000 0.0000 0.0000a 13 ■ 2 39.7576 16,0526 ,40388 14 0 0.0000 0,0000 0.00008 15 0 . 0,0000 0,0000 0,0 00 08 16 - o. 0.0000 0.0000 0,00009 10 1 23,7050 0.0000 0.00009 11 0 0.0000 • 0,0000 0.00009 12 . 0 0.0000 0,0000 0.0000

. 9. 13 2 20.1071 .1662 .00839 14 0 0,0000 0,0000 0,00009 15 • 0 0.0000 0,0000 0,0000

. 9 . 16 . 0 0,0000 0,0000 0,0000lo . 11 0 , 0,0000 0.0000 0.0000

• 10 12 ■" 6 35.3735 8,1323 ,229910 13 • 8 25,8807 7.7633 .300010 14 • 0 • 0.0000 . 0,0000 0.0 00010 15 0 0,0000 0,0000 0.000010 . 16 . 2 28,5535. 4,2804 .1499U ' 12 o ; 0,0000 , 0,0000 0.000011 • . 13 " 0 0.0000 ' 0.0000 0,000011 : 14 o 0,00 0 0 .0.0000 0,000011 15 o 0,0000 0,0000 0,000011 16 . 0 0,0000 O.OOOO 0.000 0

• 12 13 i 24,2731 0.0000 0.000012 . 14 . 0 0,0000 0.0000 . . 0,000012 15 0 0,0000 0,0000 0,000012 . 16 ; , .0 • 0.000 0 0,0000 0,000013 14 ' - o 0.0000 ' 0,0000 0 .0 0 0 013 15 • ' 0 0.0000 0,0000 0,000013 16 0 0.0000 0,0000 ■ 0,000014 15 0 . 0.00 00 o.oooo . 0,000014 16 0 0,0000 0.0000 0.000015 16 . , 0 0,0000 • 0,0000 0,0000

MEDIAN

0 * 0 0 0 0O o O O O O0 , 0 0 0 00 , 0 0 0 0

24,04066,00006 . 0 0 0 0

39,75760,0000

, 0 , 0 0 0 06 . 0 0 0 0

23,70500 , 0 0 0 06 . 0 0 0 0

26,1071 0 , 0 0 0 0 0 , 0 0 0 0 0,0000 0,0 00 0

34,9357 25,89586.0000 0,0000

28,5535 0,0000 0 , 0 0 0 0 6,0 0 00 0 , 0 0 0 0 6 , 0 6 0 0

24.27316,ooooO o O O O OO o O O O Oo.oooo 0,0000 0.0000 0,0000 0,0000

. o.oooo

MAX• 0,0000 ■ 0.0000 0,00 0 0 o.oooo

32,6947 0 , 0 0 0 0 0 , 0 0 0 0

' 55.8102 0,0000 0,0000 0,000 0

23,7050 0,0000' 0,0000

20,2733 0.00 0 0 0.0000 0.0000 0.0000

44,7808 38.4049 0.0000 0.0000

3.2,8340 0.0000 0.0000 0.0000 1 0.0000 0.0000

24.2731 0.0000 0,00 00 o.oooo 0 . 0 0 0 0 o.oooo 0.0000 0.0000 0.0000 0.00 0 0

MIN0,0000 0.0000 0,0000 0,0000

i1.4410 0,0000 0.0000

23.7050 0,0000 0.0000 0.000023.7050 1 0.00000.0000 19.9409 0.0000 0.0000 - 0.0000 0.0000

26.4963 14,3085 . 0.0000 0.0000

24.2731 0.0000 0.000 0 .0.0000 0,0000 0,0000

24.2731 0.0000 0,0000 0.0000 0.0000 0.0000 0.0000 0,0000 0.0000 0.0 0 00

QDEV

O o O O O O 0.0000 0 , 0 0 0 0 0,0000 5,6049 0 , 0 0 0 0 0,0000 0.6000 0,0000 o,6 o o o 0 , 0 0 0 0 0,0000 O.OOOOo.nooo0.0000O . O O O OO.nOOOO o O O O O0 , 0 0 0 08.38626,93150 , 0 0 0 0o.ooooO o O O O O0.O0000.00000,0000o.nooo0,00000.00000,6000O.nOOO0.60000.00000.0000o.noooo.noooo.nooo0.0000

APPENDIX T

COMPUTER RUN - PERCENT NEW CASHTHREE "UPre YEARS

COMPUTER CODE NO. 52

121

CLASS123

RESPONSES123

OBSERVED FREQUENCY TABLECLASS'

PERF GRP TOTAL i 2 3

1 • 23 . "3 ■-■'s'. • ■' 122 23 . -4 14 • 53 . 23 ... . 9 7 7

TOTAL - • . • 16 29 24UNLISTED RESPONSES = .0

FREQUENCY TABLECLASS

•PERF GRP. TOTAL ' 1 2 • 3

1 ' 23 . 5.3 9.7 8.02 . 23-. 5.3 9.7 8.03 23 5.3. 9.7 8.0

TOTAL; 69 16 29 24

CALCULATED CHI SQUARE = 10.091DEGREES Oc FREEDOM = 4

CLASS NUM MEAN STD DEV

1 ■ 162 293 24

23.112349 26.724595 31.472730

11,107223 7.269937

12.777,9 4 5

COEF VAR •

. 4.90575 • .272025. 405<)97

t o t a l 'CLASS 69 27 ..533498 . 10.854300 • .394150

MEDIAN ■

21.73802926.34565030.432348

2 5 . 6 6 4 6 3 1

MAX

55.81015648.36599962.041928

6 2 . 0 4 1 9 2 3 ,

M I N . -

8.67612411.441004

CDEV

3.929609 3..107307

12.815683 10.582347

6 . 6 7 6 1 2 4 6 . 4 4 0 1 2 7

122

APPENDIX U

COMPUTER RU N— DATE SHARES OFFEREDTHREE "UP" YEARS

COMPUTER CODE NO. 6

123

CLASS . ' RESPONSES1 • 12 23 • 3

OBSERVED FREQUENCY TABLE

PERF GRP TOTAL

1 ' ' 232 . 233 23

TOTAL ■ 60

UNLISTED RESPONSES

EXPECTED FREQUENCY TABLE

PERF GRP TOTAL

1 232 23 .' 3 2?

; ' TOTAL ’ - 69CALCULATED CHI SQUARE = 10,DEGREES O F FREEDOM * = .. . 4

CLASS NUM MEAN

1 . . 17 27,3886302 36 30.2801553 16 21.529110

TOTALCLASS 69 27,538493 •

CLASS .1 2 36 16, . .1 ' .4 13 6 • •• •••’7 7 9

17 36' 16 ' .0 '

• CLASS1. 2 3

' 5,7 12.0 5.3‘ 5.7 ' 12.0 5.3 '5.7 12.0 ’• 5.3

17 36 16

STD DEV COEF VAR '

11.408646 •/ .41654811.344097 , .3746385.214434 •.242204

1 0 . 8 5 4 3 0 0 . • . 3 9 4 1 5 0

MEDIAN MAX MIN QDEV26.51616027.80650522,108311

49.38759062.04192833,021782

12.81563311,0643028.676124

9.533167 4.623835 3, 1.6 0 8 51

2 5 . 6 6 4 6 8 1 6 2 . 0 4 1 9 2 8 8 , 6 7 6 1 2 4 6 . 4 4 0 1 2 7

APPENDIX V

COMPUTER RUN - LOAD VERSUS NO-LOAD FUNDSFIVE YEARS

COMPUTER CODE NO. 7

125

CLASS ‘ RESPONSES1 i2 2OBSERVED FREQUENCY. TABLE-

• C L A S SPERF GRP TOTAL ' - 1. 2' 1 23 19 - ; 4 •

2 23 20 33 - 23 13 10

TOTAL 69 52 17

UNLISTED RESPONSES - 0EXPECTED FREQUENCY TABLE

CLASSPERF GRP TOTAL - 1 2

1 23 17.3 5.72 23 17.3 5.73 23 17.3 5,7

TOTAL 59 52. 17

CALCULATED CHI SQUARE = 6.713DEGREES OF FREEDOM 2 .

CLASS N'JM ‘ MEAN STD DEV' COEF

1 52 . ,26.727032 10.827559. ' .. 2 17 23.900229 ' 10. 1-00733 %

TOTALCLASS 69 27.538493 10.854300

VAR

376900422621

394150

MEDIAN MAX MIN - QDEV

26.507371 62.041928 • 8.676124 4.95453519.940856 \ 48.365999 11.441004 . 6, 346630.

2 5 . 6 6 4 6 3 1 6 2 . 0 4 1 9 2 8 8 . 6 7 6 1 2 4 6 . 4 4 0 1 2 7

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