ANALYSIS OF RATES OF RETURN AND RISK FOR COMMON AND PREFERRED STOCKS-~THE BRAZILIAN EXPERIENCE Thesis for the Degree of Ph. D. MICHIGAN STATE UNIVERSITY WLADIMIR A. PUGGINA 1974 Date This is to certify that the thesis entitled ANALYSIS OF RATES OF RETURN AND RISK FOR COMMON AND PREFERRED STOCKS -- THE BRAZILIAN EXPERIENCE presented by Wladimir A. Puggina has been accepted towards fulfillment of the requirements for Ph.D 2/28/74 0-7 639 degree in Business - Finance LIBRARY Michigan State Us iversity {I . HUAE 8. SUNS' HI BOOK BINDEIRI‘ WI? 4 m :Izsaszmsasalll ANALYSIS OF RATES OF RETURN AND RISK FOR COMMON AND PREFERRED STOCKS -- THE BRAZILIAN EXPERIENCE By Wladimir A. Puggina This research has as its main goal the performance measurement of the Brazilian stock market during the period 1968—1972. By performance we mean the average annual rates of return experienced by investors in common and preferred securities as well as for the various sectors into which these securities were classified. Related to this topic is the risk involved in these investment alternatives. We have chosen the BETA measure of risk for this pur- pose. The research of this dissertation is important for the following reasons: (1) In terms of economic development greater knowledge about rates of returns experienced by investors will help to stimu— late growth and allocate savings efficiently. (2) This research tests abroad certain models that are now being applied in the United States. (3) Financial analysts may find this information useful in their stock valuation models. (4) This study may enable measurement of the performance of mutual funds and institutional investors. (5) Finally, Brazilian and foreign investors may be aided in their investment decision processes. We have prOposed for ourselves several objectives from which our \ r / ”U (0 / =7) r‘. .fifi. Wladimir A. Puggina hypotheses were derived. The primary objectives were to determine the following: whether investment in the security market was a hedge against inflation and, if so, the degree of such a hedge; if differential returns experienced by common, preferred, total market, and various sectors were related to risk; and, finally, whether common stocks provide higher returns than preferred to justify the higher risks involved. Our secondary objectives were the following: whether the actual market index is biased; whether the reinvestment of cash proceeds derived from dividends and sale of rights in the same stock or in the market portfolio would provide different results; the impact of holding these proceeds in cash; and, finally, determining the impact of the largest companies on the market's performance. To accomplish these objectives we selected a sample of 178 com- mon and 138 preferred stocks, or a total of 316. We computed average annual rates of return and risk for these securities and constructed market indicators under different reinvestment and weighting assump- tions. We reached the following results. Investment in the security market for the five-year period not only was a hedge against infla- tion but also provided substantial gains since the average annual real rate of return was 34.9 percent for common, 41.4 percent for preferred, and 36.4 percent for the total market. For shorter periods of time, however, there were wide fluctuations in these rates of return. Furthermore, investment in the security market did not always provide a hedge against inflation. This conclusion Wladimir A. Puggina holds for common, preferred, and total market investments. We found a risk-return relationship for common, preferred, and total market stocks. This linear relationship was statistically tested and shown to be valid at the .05 level of significance. The seventeen sectors in which these securities were classified showed great variations in performance and risk. A risk-return relation— ship for the sectors also was found valid at the same level of significance. The results concerning the existence of a relationship between common and preferred stocks were inconclusive since preferred stocks showed higher return and a lower risk measure. We also showed that the actual market index is biased, although not as much as was expected. The decision of reinvesting the cash proceeds derived from dividends and sale of rights in the same secu- rity or in the market portfolio was shown to be irrelevant. The decision to hold these proceeds in cash rather than reinvest provided the same results in the long run, although in a bull market the reinvestment decision provided better results, and in a bear market the Opposite was true. We have also shown that smaller companies, mainly in the last year and one-half, have done better than the largest ones. They outperformed the largest companies in a bull market and proved more resistant to decline in a bear market. ANALYSIS OF RATES OF RETURN AND RISK FOR COMMON AND PREFERRED STOCKS -- THE BRAZILIAN EXPERIENCE By M x00 '- Wladimir A? Puggina A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Accounting and Financial Administration 1974 ©C0pyright by WLADIMIR A. PUGGINA 1974 ACKNOWLEDGMENTS I wish to express my appreciation for the assistance I have received from the many people who made this research possible, especially my committee members, Dr. Alan Grunewald, Chairman, Dr. Dole Anderson, and Dr. Richard G. Walter. I am very grateful for Dr. Grunewald's encouragement and guidance during the planning stage and for his careful and critical review of the results and conclusions. Dr. Anderson's suggestions were precise, timely, and important. A special note of thanks for Dr. Walter, who followed all the steps of this research and who helped a great deal with his encouragement and technical assistance. I would like to thank Professor Carlos Jose Malferrari and Professor Gustavo de Sa e Silva, present and former deans, respec- tively, of the Escola de Administracao de Empresas de Sao Paulo - EAESP - for allowing me to complete the doctoral program. I am also grateful to the EAESP for providing me with the necessary financing to complete this dissertation. Several peOple in different ways and at different points in time were very helpful. I am indebted to my friend, Professor Ivan Pinto Dias, for his encouragement, to Professor Jose A. Prettoni for providing me with computer facilities, and to Jose M. Cardin for allowing me to use the facilities of the Research Division of the Sao Paulo Exchange. I wish also to thank Elizabeth Johnston for iii her help in editing, Jo McKenzie for her careful typing, and Jacob Ancelewitz, who, as research assistant, supervised the data collection. All the merit for my completion of this dissertation and the doctoral program goes to my dear wife, Maria Helena, and to my children, Helena and Marcelo, for their understanding and support. They were my constant source of inspiration, and I am eternally grateful to them. I am also grateful to our parents, my sisters, and eSpecially my brother, Norman. iv TABLE OF CONTENTS LIST OF TABLES. O O 0 O O O O O O O O O O O O O O 0 O O 0 LIST OF FIGURES O O O O O O O O O O O O O O O O O O O O 0 Chapter I IMPORTANCE OF THE STUDY AND REVIEW OF THE LITERATURE O C O O O O O O O O O O O O O 0 Importance of the Study . . . . . . . . . . . . Importance for Economic Development. . . . . Importance of Testing Some Basic Models Abroad . . . . . . . . . . . . . . . Importance for Financial Analysts. . . . . . Importance for Measuring Mutual Fund and Other Institutional Investor Performance. . Importance for Brazilian and Foreign Investors . . . . . . . . . . . . . Review of the Literature. . . . . . . . . . . . Measuring Market Rates of Return . . . . . . Lawrence Fisher and James H. Lorie Study. John P. Herzog Study. . . . . . . . . . . Eugene F. Brigham and James Pappas Study. Conjuntura Economics Study. . . . . . . . Conclusion. . . . . . . . . . . . . . . . Risk Measurement . . . II OBJECTIVES, HYPOTHESES, AND HYPOTHESIS TESTING. . Objectives of the Research. . . . . . . . . . . Primary Objectives . . . . . . . . . . . . . Rates of Return for the Stock Market. . . Rates of Return for Common and Preferred Stocks . . . . . . . . . . . . Rates of Return by Sectors. . . . . . . Analysis of Risk and Return for Common and Preferred Securities . . . . . . . . Analysis of Risk and Return by Sectors. . Secondary Objectives . . . . . . . . . . . . Test of the Actual Market Index . . . . . Page viii xi ll 12 13 14 14 15 16 17 18 19 25 25 25 25 26 27 28 28 - 28 29 Chapter Page Test of the Impact of the Reinvest- ment Decision. . . . . . . . . . . . . . . . 29 Test of the Impact of the Weighting System. . 29 Hypotheses. . . . . . . . . . . . . . . . . . . . . 30 Hypothesis Testing. . . . . . . . . . . . . . . . . 31 III SAMPLING, DATA COLLECTION, AND COMPUTATION PROCEDURE. . . . . . . . . . . . . . . . . . . . . . 34 Sampling . . . . . . . . . . . . . . . . . . . . 35 Period Covered. . . . . . . . . . . . . . . . 36 Sampling from the Universe of Securities. . . 37 Data Collection Procedure. . . . . . . . . . . . 40 Data Required . . . . . . . . . . . . . . . . 40 Source of Data. . . . . . . . . . . . . . . . 46 Computational Procedure. . . . . . . . . . . . . 49 Index for Each Security . . . . . . . . . . . 49 Market Index. . . . . . . . .'. . . . . . . . 57 Deflation of Indexes. . . . . . . . . . . . . 66 Rate of Return Computation. . . . . . . . . . 67 Risk Computation. . . . . . . . . . . . . . . 68 Problems and Limitations . . . . . . . . . . . . 71 Methodology . . . . . . . . . . . . . . . . . 72 Commissions . . . . . . . . . . . . . . . . . 72 Data Collection . . . . . . . . . . . . . . . 75 IV RESULTS AND CONCLUSIONS . . . . . . . . . . . . . . . 76 Results . . . . . . . . . . . . . . . . . . . . . . 76 Indexes. . . . . . . . . . . . . . . . . . . . . 76 Market Indexes wi h Reinvestment. . . . . . . 77 Market Index I8 by Sectors. . . . . . . . . . 91 Comparison of the Market Index IS with the BOVESPA Index . . . . . . . . . . . 104 Comparison of the Total Market Index Under Different Weighting Systems. . . . . . 109 Rates of Return. . . . . . . . . . . , . . . . . 113 Rates of Return Matrix for an Individual Company Complete Example of the Output . . . 113 Rates of Return - With Reinvestment . . . . . 121 Rates of Return by Sectors. . . . . . . . . . 130 Rates of Return for the Strategy of No Reinvestment . . . . . . . . . . . . . 152 Rates of Return for the BOVESPA . . . . . . . 153 Rates of Return for Reinvestment in the Market Portfolio. . . . . . . . . . . 153 Rates of Return with Reinvestment of Proceeds but with the Same Weight for A11 Securities . . . . . . . . . . . . . 153 vi Chapter Risk and Return Analysis . . . . . . . . . Analysis of Risk and Return for Common Stocks. . . . . . . . . . . Analysis of Risk and Return for Preferred Stocks . . . . . . . . . Analysis of Risk and Return for the Total Market . . . . . . . . . Analysis of Risk and Return by Sectors . . . . . . . . . . . . . . Risk and Return Analysis Between Common and Preferred Stocks . . . . . . . . . Conclusions. . . . . . . . . . . . . . . . Was Investment in the Stock Market a Hedge Against Inflation? . . . . . . Can Differential Returns of Common Stocks Be Related to the Risk Differentials?. Can Differential Returns of Preferred Stocks Be Related to Risk Differentials?. . . Can Differential Returns of All Stocks Be Related to Risk Differentials?. . . Did Common Stocks Experience Higher Rates of Return than Preferred Stocks Due to Higher Risks? . . . . . . . . . Can Differentials in Rates of Return in the Seventeen Sectors be Related to Risk Differentials? . . . . . . . . Was the BOVESPA Index Biased as Predicted?. Was the Reinvestment Decision a Better Strategy than that of Holding the Proceeds in Cash?. . . . . . . . . Was the Size of the Companies Related to the Market Performance. . . . . . . Was the Decision to Reinvest in the Same Security a Better Strategy than the One of Reinvesting in the Market Portfolio?. Further Research . . . . . . . . . . . . . vii Page 154 161 163 166 168 173 175 175 177 177 178 178 179 179 181 182 183 183 Table 3-1 4-13 4-14 4-15 LIST OF TABLES Sample Size Evolution by Quarters . . . . . . Assumptions and Indexes Computed. . . . . . . . Market Index Is for Common Stock. . . . . . . . Market Index I8 for Preferred Stock . . . . . Total Market Index - Is . . . . . . . . . . . . Comparison of Total Market Index with Reinvestment in the Same Security and in the Market Portfolio . . . . . . . . . . Market Index I8 by Sectors - Nominal Terms. . Market Index I8 by Sectors - Real Terms . . . . Comparison of the Market Index - Ic and Is. . . Comparison of the Total Market Index - 18 With the BOVESPA Index 0 O O O O O O O O O O ' MIREE Index 18 and 18. o o o o o o o o o o 0 Rates of Return for Common Stocks of Company 37, Reinvestment Strategy . . . . . . . . . . . . . Rates of Return for Preferred Stocks of Company Reinvestment Strategy . . . . . . . . . . . . . Rates of Return for Common Stocks of Company 37, No Reinvestment . . . . . . . . . . . . . . . . Rates of Return for Preferred Stocks of Company No Reinvestment . . . . . . . . . . . . . . . . Rates of Return for Common Stocks, Reinvestment of Cash Proceeds in the Same Security . . . . . 37, Summary of the Rates of Return for Common Stocks. . viii Page 41 60 78 81 85 89 96 97 102 106 111 117 118 119 120 122 123 Table Page 4-16 Rates of Return for Preferred Stocks, Reinvest- ment of Cash Proceeds in the Same Security. . . . . . 125 4-17 Summary of the Rates of Return for Preferred Stocks. . . . . . . . . . . . . . . . . . . 126 4-18 Rates of Return for the Total Market, Reinvest- ment of Cash Proceeds in the Same Security. . . . . . 128 4-19 Summary of the Rates of Return for the Total Market. . . . . . . . . . . . . . . . . . . 129 4-20 Summary of Rates of Return by Sector. . . . . . . . . 134 4-21 Sectors Performance Classification. . . . . . . . . . 135 4-22 Rates of Return for Banks and Financial Institutions Sector . . . . . . . . . . . . . . . . . 136 4-23 Rates of Return for the Food Sector . . . . . . . . . 137 4-24 Rates of Return for the Rubber and Plastics Sector. . 138 4-25 Rates of Return for the Cement and Construction Sector . . . . . . . . . . . . . . . . . 139 4-26 Rates of Return for the Trade including Retailing Sector. . . . . . . . . . . . . . 140 4-27 Rates of Return for the Fertilizer Sector . . . . . . 141 4-28 Rates of Return for the WOod, Paper and Graphics seCtOI O O o o o O o o o o o o o o o o o o o 142 4-29 Rates of Return for the Machinery and Heavy Equipment Sector. . . . . . . . . . . . . . . . 143 4-30 Rates of Return for the Oil, Chemicals and Petrochemicals Sector . . . . . . . . . . . . . . 144 4-31 Rates of Return for Metallurgy including Forgering Sector. . . . . . . . . . . . . . . . . . . 145 4-32 Rates of Return for the Public Utilities Sector . . . 146 4-33 Rates of Return for the Steel including Mining Sector . . . . . . . . . . . . . . . . . . . . 147 4-34 Rates of Return for the Textile and Clothing Sector . . . . . . . . . . . . . . . . . . . 148 ix Table Page 4-35 Rates of Return for the Automotive and Automotive Parts Sector . . . . . . . . . . . . . . . 149 4-36 Rates of Return for the Electrical Equipment and Telecommunication Sector. . . . . . . . . . . . . . . 150 4-37 Rates of Return for the Tobacco and Beverages Sector. . . . . . . . . . . . . . . . . . . 151 4-38 Rates of Return for All Other Sectors . . . . . . . . 152 4-39 Summary of the Rates of Return Without Reinvestment by Year. . . . . . . . . . . . . 153 4-40 Summary of the Rates of Return with Reinvest— ment but with Equal Weight for all Securities . . . . 155 4-41 Rates of Return for the Total Market, No Reinvestment . . . . . . . . . . . . . . . . . . . 156 4-42 Rates of Return for the BOVESPA . . . . . . . . . . . 157 4-43 Rates of Return for the Total Market, Reinvest- ment of Cash Proceeds in the Market Portfolio . . . . 158 4-44 Rates of Return for the Total Market, Reinvest- ment of Cash Proceeds, but with the Same Weight for All securities. I o o o a o o o a o o o o o o o o 159 4-45 Analysis of Variance for Common Stock Regression. . . 162 4-46 Analysis of Variance for Preferred Stocks . . . . . . 165 4-47 Analysis of Variance for the Total Market . . . . . . 169 4-48 Rates of Return and Risk Measures by Sector . . . . . 171 4-49 Analysis of Variance Sectorial Regression . . . . . . 174 4-50 Rates of Return and Risk Analysis, Common and Preferred Stocks. . . . . . . . . . . . . . . . . 175 LIST OF FIGURES Figure ’ Page 3-1 Graphical Representation of the Normalization Scheme for Proceeds Held in Cash. . . . . . . . . . . 64 3-2 Graphical Representation of BETA. . . . . . . . . . . 70 4-1 Market Index Is for Common Stocks . . . . . . . . . . 79 4-2 Market Index I8 for Preferred Stocks. . . . . . . . . 82 4-3 Total Market Index I8 . . . . . . . . . . . . . . . . 86 4-4 Total Market Index I8 and Im . . . . . . . . . . . . 90 4-5 Total Market Index Ic . . . . . . . . . . . . . . . . 99 4-6 Comparison of the Indexes Ic and I8 . . . . . . . . . 103 4-7 Comparison of the Total Market Index IS with the BOVESPA Index. . . . . . . . . . . . . . . . 107 4-8 Total Market Index I8 and I; . . . . . . . . . . . . 112 4-9 Histogram of the Nominal Rates of Return. . . . . . . 131 4-10 Histogram of Average Annual Real Rates of Return by Sectors. . . . . . . . . . . . . . . . . 133 4-11 Histogram of Risk Measures. . . . . . . . . . . . . . 161 4-12 Analysis of Rates of Return and Risk for Common Stocks. . . . . . ... . . . . . . . . 163 4-13 Analysis of Rates of Return and Risk for Preferred Stocks . . . . . . . . . . . . . . 166 4-14 Analysis of Rates of Return and Risk for the Total Market . . . . . . . . . . . . . . 168 4-15 Analysis of Rates of Return and Risk by Sectors . . . . . . . . . . . . . . . . . . . 173 4-16 Rates of Return and Risk Analysis, Common and Preferred Stocks . . . . . . . . . . . . . 175 xi CHAPTER I IMPORTANCE OF THE STUDY AND REVIEW OF THE LITERATURE The areas of managerial business finance and investment analysis have been in a process of constant and rapid change in the last twenty years. In this process the two areas have become more closely associated and today are considered jointly in many aspects. This development is due to changes in the external business environ- ment and in the analytical tools that have become available.1 As a consequence of these changes there has been a growth in the quantity and types of research in the field. Research may be defined as "a careful inquiry or examination to discover new informa- tion or relationships and to verify existing knowledge."2 Because of its very nature the orientation in business finance has been more toward applied rather than basic or fundamental research which is carried on without regard for its immediate practi- cal value. Research in business finance and investment analysis will con- tinue in the future to play a role of increasing importance. 1J. F. Weston, The1§cope and Methodology of F13ance (Englewood Cliffs, N.J.: Prentice—Hall, Inc., 1960), pp. viii-x. 2F. J. Rummel and B. C. Wesley, Reseggch Methodology in Business (New York: Harper and Row Publishers, 1963): P. 10. 2 The type and nature of this research may vary. Some might be directed toward completely new approaches to problems in the field of finance. For example, new theories about capital structure or dividend policies might emerge. The alternative and more common approach in the literature is to concentrate research on testing theories already prOposed or to delve deeper into others. Eventu— ally some of the parameters of previous work may be changed in the hope of improving them. This has been an extremely fruitful approach, and it has achieved great progress. Another approach that has yielded important results in business finance and investment analysis, as well as in other fields, is to expand and test in new environments models and theories already developed. This means, in research, going to the international arena. Considering the tremendous development in communications and international trade, we will see in the future more and more of an increase in the areas of international business and investment. The type of research presented here falls into this third category. Cer- tain models and techniques previously developed will be applied in a completely new environment, that of Brazil. The research has a much broader objective than the mere testing abroad of models previously deve10ped; it also is important for aca- demic and practical reasons. By providing the rates of return on Brazilian securities, this study contributes additional knowledge about the performance of the stock market in a developing economy. Brazil's experience could be shared by other countries in the same stage of economic development. Investors, both Brazilian and foreign, should have access to prospective returns and should know the risk involved in their investment decisions. Such information also is required by financial analysts when appraising the intrinsic value of certain securities, as well as for measuring the performance of mutual funds and other institutional investors. Given the importance of the topic, it is easy to understand why other studies with similar goals are found in the literature. In reviewing previous research efforts one gains a better view of the methodological approach necessary as well as an insight into problems and limitations experienced in other work. Of course, changes must be made to apply these models and techniques to the Brazilian situ- ation. That is the purpose of this dissertation. Importance of the Study_ The main goal of the present research is to measure the perform- ance of certain types of securities (common and preferred stocks) listed on the Sao Paulo Securities Exchange. By performance we mean average rate of return. Related to this topic is the analysis of risk, a concept about which much will be said below. In Chapter II a detailed discussion of this main goal or objective will be presented. The research of this dissertation is important for the following reasons: (1) In terms of economic development, greater knowledge about rates of return experienced by investors will help to stimulate growth and allocate savings efficiently. (2) This research tests abroad certain models that now are being applied in the United States. (3) Financial analysts may find this information useful in their stock valuation models. (4) This research may enable measurement of the performance of mutual funds and institutional investors. 4 (5) Finally, Brazilian and foreign investors may be aided in their investment decision processes. Importance for Ecogggic Development Although economic development is a widely used term, its defini— tion is not clearly established. Some authors have stated that it is easier to define econom1c development by listing what it is not. Some of the confusion appears to result from its use with different meanings and objectives. For example, it has been identified with economic independence or with industrialization. Even if these two elements are considered to be closely related, they are very far from being identified with economic development itself. We believe that the following definition is broad enough to encompass the overall idea. Development is a "type of social change in which new ideas are introduced into a social system in order to produce higher income per capita and levels of living through modern production methods and im- proved social organizations."3 At the root of this definition is the notion that development is composed of economic growth plus social change. The concept of eco- nomic growth is not absolutely related to the general expansion of the economy. More apprOpriately, it is a relative concept translated into terms of growth in real income per capita. Social change is understood as "the process through which alterations occur in the structure and function of a social system."4 3E. M. Rogers, Mbderniggtion Among Peasants - The Impact of Com- munication (New York: Holt, Rinehart and Winston, Inc., 1969), p. 8. 4Rogers, Modernization, p. 3. 5 After World War II, perhaps because of the tremendous impact of communications, the problem of different levels of economic develop- ment became more apparent, mainly to the less developed nations. The economic recovery of Germany, Japan, and Italy in some ways made several nations believe that their chance to bridge the economic gap had arrived. Recent studies have shown, however, that these differences in economic development not only have persisted but also have widened. Whereas the 19503 were years of rising expectations, the 19608 could be considered a period of rising frustrations.S Due to poor results and because of political, economic, and humanitarian concerns, eco- nomic development became a subject of growing interest to the academic world, politicians, and governments. Despite this concern, economic development remains an unsettled and very controversial area, not only in terms of its real meaning and definition, but also when analyzed in terms of economic theory, history, or through the use of sophisticated approaches of mathematical modeling. Different theories and models use different parameters, and the role and importance accorded to each of these varies. Among the several parameters being used we are most interested in the role played by financial institutions, mainly capital markets. Certainly, the role and significance of capital markets in economic development has been controversial. An increase in the number and type of financial institutions and in the ratio of money and other financial assets relative to 5Rogers, Modernization, p. 15. 6 total output and tangible wealth always has been present in the economic development process.6 The essence of the process is that individual investors have their wealth in portfolios composed of non- reproducible assets (land and precious metals), reproducible assets (inventories, producer and consumer durables), and financial assets (currency, deposits, stocks, bonds, and so forth). There are many indications that the portfolio of individuals in underdevelOped and developing countries is far from socially ideal since investors tend to concentrate a substantial portion of their holdings in nonrepro- ducible rather than financial assets. The determining factors are many, ranging from economic to sociological and cultural. Financial institutions thus play a significant role in the reallocation process of forms of existing wealth. They do this by encouraging savers to hold their assets in reproducible assets, pro- moting the best allocation to the new capital brought into the sys- tem, and encouraging an increase in the rate of saving and investment. The main question is whether financial institutions grow as a consequence of economic development (demand - following) or whether financial institutions can induce economic growth by supplying assets and liabilities (supply - leading).7 6R. W. Goldsmith, "Financial Structure and Economic Growth in Advanced Economies," in M. Abramovitz, ed., Capital Formation and Economic Growth (Princeton: Princeton University Press, 1955). Also by Goldsmith see Financial Intermediaries the American Economy Since 1900 (Princeton: Princeton University Press, 1958), and Financial Structure and Development (New Haven: Yale University Press, 1969). 7H. T. Patrick, "Financial Development and Economic Growth in Underdeveloped Countries," Economigibevelopment and_ggltura1 Change 15 (January 1966): 174-89; and Rondo Cameron, Banking in Early Stages of Industrialization (Fair Lawn: Oxford University Press, 1967). 7 Independent of this dilemma, one can identify several ways in which financial institutions are very important to the economic development process. Financial institutions may allocate wealth more efficiently by facilitating changes in its ownership and its composition. They also can encourage a more efficient allocation of new investment by inter- mediating between savers and entrepreneurs. Finally, they can pro- vide incentives to increase the rate of accumulation of capital.8 These various effects have been analyzed by Gurley and Shaw, now known as the Gurley and Shaw model.9 To accomplish reallocation, investors must be offered a large range of financial assets with different characteristics of liquid- ity, maturity, size, and returns so that they can find financial assets that fit their requirements. Investors must have this array of alternatives if the reallocation process is to occur.10 8Patrick, "Financial Development." 9See the following by: J. G. Gurley and E. 8. Shaw, "Financial Aspects of Economic Development," American Economic Review 45 (September 1955): 515-38; "Financial Intermediaries and the Savings Investment Process," Journal of Fingnce 9 (May 1956): 257-76; Money in a Theogy of Finance (Washington, D.C.: Brookings Institution, 1960); and "Financial Structure and Economic Development," Economic Development and Cu1turg1_Ch§ggg 15 (April 1967): 257-60. 10A very interesting approach to the relationship between capital markets and economic development can be found in the papers listed below. They were presented at the First International Seminar on Capital Markets and Economic Development held in Rio De Janeiro, Brazil, September 1971. A. D. Bain, "Financial Structure and the Control of Credit"; A. Chaineau, "The Financial Devices of Economic Growth"; 8. Daim, "Industrializacao e Financiamento no Brasil - Notas sobre a Experiencia Recente"; G. S. Dorramce, "Capital Market and Economic Development"; K. Emi, "Capital Markets and Economic Develop- ment in Postwar Japan" and "The Relations between savings and Invest- ment in the Japanese Economic Development"; E. Gannage, "Capital 8 One of the main goals of this research is to present informa- tion regarding these alternatives. The rates of return and risk characteristics of some of the securities being offered in the Brazilian financial market are important to prospective investors. With proper knowledge, individuals may be induced to reallocate their wealth to financial assets, which we believe is a more produc- tive investment than real estate, foreign currency, or jewelry. New investment may be allocated to more socially desired alternatives, and individuals may even be persuaded to save and invest more. Such knowledge not only is useful for investors, but also may indicate to the government distortions and the need for corrective measures. It should be stressed that if the Brazilian capital market experience could be documented, other nations facing the same economic develop- ment problems could benefit. lgpggtance of Testing Some Basic Models Abroad As was noted, an extremely fruitful approach to business finance and investment analysis has been in the international arena.11 This Market and Economic Development"; C. Segre and L. Freres, "European and Offshore Capital Markets: Structural Problems and Evolution Prospects"; and M. C. Tavares, "Natureza e Contradicoes do Desen- volvimento Financeiro Recente no Brasil." 11For example, see the following: Tamir Agmon, "The Relations Among Equity Markets: A Study of Share Prices Co-Movements in the United States, United Kingon, Germany and Japan," Journal of Finance 27 (September 1972): 839-55; two articles by H. G. Grubel, "Inter- nationally Diversified Portfolios," American Economic Review 58 (December 1968): 1299-1314, and "A Proposal to Provide Development Aid Through Equity Investment and Mutual Funds," Economic Record 46 (March 1970): 86-95; H. G. Grubel and K. Fadner, "The Interdependence of International Equity Markets," Journal of Finance 26 (March 1971): 89-94; R. D. Haas, "A Portfolio Model of International Capital Flows" 9 approach has benefits in two directions. In testing existing models and theories abroad one may note how they fit new situations. In addition, one can analyze and study the experience of other nations in dealing with real problems or parameters that eventually might effect the United States. Inflation is but one example of a factor which has received more attention in Brazil than the United States. Allowing for certain differences, the Brazilian experience might assist analysts as the United States moves into higher and higher rates of inflation.12 Considering, however, the present state of the art of economic theory and the theoretical development of business finance and investment analysis, this study will concentrate on the testing abroad of already developed models and theories. The theories should be general enough to be applied in different environments. If adaptations and new parameters should be introduced, the reasons must be analyzed. (abstract of doctoral dissertation), Journal of Finance 27 (September 1972): 948; D. R. Lessard, "International Portfolio Diversification: A Multivariate Analysis for a Group of Latin American Countries," Journal of Finance 28 (June 1973): 619-33, and "Multinational Port- folio for Developing Countries" (abstract of doctoral dissertation), Journal of Fingnce 26 (June 1971): 798-99; Haim.Levy and Marshall Sarnat, "International Diversification of Investment Portfolios," American Economic Review 60 (September 1970): 668-75; B. H. Solnik, "A Note on the Validity of the Random Walk for European Stock Prices," Journal of Finance 28 (December 1973):1151-59; and J. C. McDonald, "French Mutual Fund Performance: Evaluation of an Internationally - Diversified Portfolio," Journal of Finance 28 (December 1973): 1161-80. 12The following articles exemplify the concern about stock prices and inflation: D. A. Nichols, "A Note on Inflation and Common Stock Values," Journal of Finance 28 (September 1968): 655-57; Brian Motley, "Inflation and Stock Values: Comment," Journal of Finance 24 (June 1969): 530-35; and J. C. Van Horne and W. J. Glassmire, Jr., "The Impact of unanticipated Changes in Inflation on the Value of Common Stocks," Journal of Finance 27 (December 1972): 1081-92. 10 Impgptance for Financial Ana1ysts The financial analyst must have specific knowledge about the economy, the position of a firm within its industry, and the market situation. This research will provide more detailed data for these analysts. The information will be related to the market as a whole, although it will be based upon the analysis of individual companies, as will become clear in chapter 111. Financial analysts who adopt fundamental analysis in the valu- ation process of securities must have some basic information. For example, they must have a basis for forming expectations regarding the rate of return for a certain risk class and a measure of relative risk of the specific security in relation to that of the market. Postponing a detailed discussion, suffice it to say that we will be looking for information to fill the needs of such analysts in their valuation process. The reader must realize that prior to this study this information was not available in Brazil, either in this form.or in the detail in which it will be presented.13 Certainly the Brazilian capital market experience in the last five years is the result of many and complex factors. Among these, there is no doubt that better analysts and improved tools for their acquiring information and data are needed. It is hoped that the information presented in this dissertation will enable the financial community to make better predictions about security prices and thereby contribute to the rationalizing of these 13See page 17. 11 markets. 1mportance for Measuring Mutual Fund and Other Institutional Investor Performance In the United States in the last twenty years the importance of institutional investors has increased. They have played an ever larger role in the market, and concern has grown regarding their im- pact. Frequently questioned is the performance of these investors and, in particular, that of open-end investment companies, or mutual funds.14 The academic community has provided studies and techniques for measuring the performance of these funds, and this tremendous contribution has been made possible by the quantity of data available. In Brazil mutual funds also have grown in importance for many of the same reasons. However, there also has been a governmental incentive program. We believe that mutual funds will have an even greater importance in the future when other institutional investors are incorporated into this incentive program. It is hardly necessary to discuss the significance of measuring how well these funds are per- forming in relation to the market as a whole. Before we can do this, 14For example, see Irwin Friend, M. E. Blume, and Jean Crockett, Mutual Funds and Other Institutional Investors: A New Pergpective (New York: McGraw-Hill Book Co., 1970); Irwin Friend and Douglas Vickers, "Portfolio Selection and Investment Performance," Journal of Finance 20 (September 1965): 391-415; Ira Horowitz, "The Reward - To Variability Ratio and Mutual Fund Performance," Journal of Business 9 (October 1966): 485-88; M. G. Jensen, "The Performance of Mutual Funds in the Period 1945-1964," Journal of Finance 28 (May 1968): 389-416; W. F. Sharpe, "Mutual Fund Performance," Journal of Business 9 (January 1966): 119-38; J. L. Treynor, "How to Rate Man- agement of Investment Funds," Harvard Business Review 43 (January- February 1965): 63-75; and.I. L. Treynor and K. M. Kay, "Can Mutual Funds Outguess the Market?" Harvard Business Review 44 (July-August 1966): 131-36. 12 however, it is necessary to know how well the market is performing since the comparison will be made with the market. A natural extension of this research, therefore, would be a study of institutional investors such as that indicated in the last chapter. 1mport§nce for Brazilian and Foreign Investors Investors, when allocating their savings among different alterna- tives, wish to know the expected returns and the risks of each of these alternatives. However, in the real world these two types of information are not always available. Therefore, one must try to assess these expectations by an ex post analysis of past results. Such ex post knowledge is basic to the investment decision process. As was noted, this investment decision process involves not only investment in securities of any type but also an extensive range of alternatives, from real estate to jewelry, antiques, and so forth. Ex post information is useful in making investment decisions concerning securities and in the rationalization of the markets. It is also important to the process of moving resources from the nonpro- ductive to the productive section of the economy. In this way ex post information assists in the reallocation of savings in the economic development process. What was true for individual investors is even more true for institutional investors. They must have this informa- tion to plan their investments and investment strategies. It is generally assumed that institutional investors are more rational in their investment decisions than are individuals. Whether they utilize their resources more efficiently is a matter for further inquiry, and 13 this study provides a partial foundation. When speaking of investors, one tends to think only of local or national investors. We have reason to believe this concept should be expanded to include not only Brazilians, but also foreign investors. In Brazil the economy is open to foreign investors, and foreign in— vestment plays an important role. At present this is true for direct investment or investment made through corporations in the form of subsidiary or joint ventures. In an effort to bring more resources into the securities market, several studies were conducted by the Central Bank concerning the feasibility of allowing foreign investment in the securities markets. We did not have access to these studies, so we cannot indicate the methods being considered, but sooner or later foreigners will be able to own financial assets listed on the securities exchanges. There has been tremendous growth in the size and importance of the so-called multinational corporation. It was some time before the corporate finance academic community recognized this area was deserv- ing of attention. We believe a similar process will occur in the area of investment analysis and strategy. Investors, individual or institutional, will have an increasing number of opportunities abroad, and, hopefully, this study will be useful when the time arrives. Review of the:L1tergture Articles relevant to the present topic have been published in the United States and Brazil. While we do not intend to present an exhaustive review, we want to refer to the major works and use them as a foundation. The articles fall into two major categories: 14 measurement of market rates of return and risk measurement. These will be discussed separately. ,MgmsuringTMarket Rates of Return Four studies are particularly relevant. The first three, all published in the United States, provide an example of the methodology utilized to handle a problem very similar to that with which we are concerned. Their strengths, weaknesses, assumptions, and shortcomings have been of great assistance in establishing our own procedures. The final article, appearing in Conjuntura Economigm, represents the first attempt to measure investor experience in Brazil, and its shortcomings must be viewed inthis light. Review of this article and consideration of its weaknesses has allowed us to avoid the same shortcomings. The following aspects of each of these studies will be discussed: (1) objectives; (2) model and methodology; (3) sample; and (4) strengths and shortcomings. Lawrence Fisher and James H. Lorie Study15 The basic objective of "Rates of Return on Investment in Common Stocks" by Lawrence Fisher and James H. Lorie was to compute rates of return on stocks listed on the New York Stock Exchange. The study used a discounted cash flow technique. The components of the cash inflow are: (1) dividends, (2) rights, and (3) market value of the stock at the terminal date. 15Lawrence Fisher and J. H. Lorie, "Rates of Return on Investment in Common Stocks," Journal of Business 37 (January 1964): 1-21, and "Rates of Return on Investment in Common Stocks," Journal of Business 41 (July 1968): 291-316. 15 The cash flow is adjusted for stock splits, income tax, trans- action costs, and tax on capital gains. The study is divided into two parts, one assuming reinvestment of dividends and the other assuming no reinvestment. It is assumed that the same amounts of money are invested in each security at the beginning of the period. The study sample covered all common stocks listed on the NYSE (approximately, 1856). The time period covered was thirty-nine years (1926-1965). The Fisher and Lorie study is a classic in the finance liter- ature. It is the most complete in terms of methodology and sample size. We do not believe, however, that giving the same weight to all securities provides the best representation of the market as a whole. We think that the weighting system should take into consideration the size of each company. John P. Herzog Study16 "Investord’Experience in Corporate Securities: A New Technique" by John P. Herzog computed the rates of return on corporate bonds and preferred and common stocks. Its secondary objective was to compare realized yield with an accepted measure of expected yield. The approach used was again the computation of the yield for a variable income stream, in which dividends and terminal value were considered. Stock rights were not. Nor was any provision made for adjustments for income tax and commission costs. The weighting system 16J. P. Herzog, "Investor Experience in Corporate Securities: A New Technique for Measurement," Journal of Business 37 (January 16 was based on the assumption that investors would buy an equal number of shares of each stock. The sample size was extremely small since only ten common stocks were included. The period covered by the sample was 1929—1962. The main advantage of Herzog's study is a comparison of the rates of return of different securities. The exclusion of considera- tion of rights as well as commission costs and income tax adjustments are limitations in the model. The most serious limitation is in terms of sample size and in the weighting system. Emggne F. Brigham and James Pappas StudyI7 "Rates of Return on Common Stocks" by Eugene F. Brigham and James Pappas also computed rates of return in common stock as well as the percentage of the total return that is attributable to dividends and capital gains. In relation to capital gains, Brigham and Pappas also studied the relative importance of gains in the P/E ratio and earnings. The model analyzed the cash flow stream of dividends and terminal value. Adjustment were made for capital gains, but rights were not considered. There is no indication of any adjustment for commission costs. Also, two approaches were assumed in relation to dividends: reinvestment and no reinvestment. The weighting system was based on the relative position of market value of each individual corporation on the total market value of.the sample. The sample consisted of 658 industrial and utility firms examined during the period 1946-1968. 17E. F. Brigham and James Pappas, "Rates of Return on Common Stocks," Journal of;§usimgss 42 (July 1969): 302-16. 17 The exclusion of rights and commission costs is a limitation. The study's main advantage is its analysis of the relative importance of dividends versus capital gains as well as in the weighting system used. Conjuntura Economics Study;8 "Rentabilidade do Mercado de Acoes - 1955/71 - Estudo Especial" intended to measure rates of return of the Brazilian securities ex— changes and develop a measurement of risk. The rates of return were computed from the Rio de Janeiro Ex- change Market Index. In building this market index consideration is given to dividends, sale of rights, stock dividends, and capital gains. There is no adjustment for income tax or commission costs. The stocks included in the market index were selected according to their liquidity and were weighted according to the same procedure. The sample was analyzed periodically for entrance or exclusion of securities and to change the weighting. The study covers the period 1955-1971. The limitations of this study are related to the assumptions used in the construction of the market index. By considering liquidity as the criterion for the inclusion of securities in the index and by weighting according to the same procedure, one obtains an index of the high liquidity stocks. By liquidity we mean the relative trading volume of a security in relation to the total volume traded in a certain period of time. We believe this index is biased upward in a 18"Rentabilidade do Mercado de Acoes," 1955/71 Estudo - ESPECiaI, Conjuntura Economics (December 1972): 49-52. 18 bull market and downward in a bear market since no consideration is given to the other stocks that are being traded and to their size.19 The study began in 1955 when the amount of trading was limited be- cause of the small number of companies being traded and because of the low liquidity and volume transaction; it ended in 1971 at the peak of the Brazilian stock market. The main advantage of the Conjuntura Economics study is that it was a pioneer work. The limitations which have been pointed out are related to the index it was based upon rather than to the study itself. Conclusion The review of these studies has helped us arrive at a theoretical ideal in terms of the methodology and sample size to be used. We should include in our model dividends, sale of rights, and capital gains. Adjustments should be made for income tax and commission costs and stock splits and stock dividends. In terms of sample size, the ideal would be to work with the total universe. The weighting system should be the relative market value of each individual corporation in the total market value of the total population. Considering Brazil's inflationary economy, adjust- ment should be made for that. The study should begin when the stock market is relevant and should be updated as often as possible. There is an obvious limitation to this approach: the cost in- volved. Reflecting its large budget, the Fisher and Lorie study is 19These limitations also are found in the index for the Sao Paulo exchange, the Bovespa, since the same methodology is used for both. 19 the one that most closely approaches the ideal model. Interestingly enough, despite the different assumptions made in the three U. S. studies, the results are extremely close to each other for the periods during which the studies overlap. The rates of return presented by Fisher and Lorie for 1950-1960 is 15.0, by Herzog, 16.5, and by Brigham and Pappas, 15.4. We will not be able to use the ideal approach because of the costs involved and because of the data collection problem. In Chapter III we will present a detailed description of the procedures used and the problems that did not allow us to use the ideal model. Risk Measuremgmg [ngk.normally is defined as "the chance of injury or loss."20 This is a broad definition, and most people would accept it. The concept is important in business administration, mainly in corporate finance and investment analysis, since the value of a firm is affected by both profitability and risk. Even though risk is accepted as a basic parameter in every financial and investment decision, a more precise definition is not easy to obtain. The problem is that a verbal definition is not precise enough to be used, and it is "desirable to develop a surrogate for the dictionary definition of risk which is amenable to quantification."21 Further- more, the ways of considering risk have changed. The theoretical dispute in the field of finance is essentially related to what is the 20Webster's New World Dictionagy. 21 J. C. Francis, Investments: Analysis and Management (New York: McGraw-Hill Book Co., Inc., 1972), p. 251. 20 best way to consider risk in financial analysis and models. J. R. Hicks has noted that in the pricing process of real assets "we must not take the most probable price as the representa- tive expected price, but the most probable price plus or minus an allowance for the uncertainty of the expectations, that is to say an allowance for risk."22 Harry Markowitz, departing from Hicks, went further in his con- sideration of risk. He applies the concept in pricing securities and not real assets. He also concentrated in the area of estimating the capital value of assets and introduced the allowance for risk in the discount rate and not in the expected cash flow, as was proposed by Hicks.23 In selecting securities to be included in a portfolio, Markowitz had to show why return was not the only important variable, and the need to define risk in the form of the variability of returns arose. Risk began to be defined as the variability of return around the mean or expected value of the probability distribution of these returns. In the quantification of variability of return several statis- tical measures were used, such as standard deviation, variance, semi- variance, and semideviation. However, Markowitz suggests the use of the standard deviation (or variance) because it "is superior with respect to cost, convenience, and familiarity ... and will produce 221. R. Hicks, Value and Capital, Oxford, Clarendon Press, 1948, pp. 125-26. 23R. G. Walter, "Fundamental Analysis and the Valuation of Securities: Theory," Revista de Administracao de Empresas, F. G. V. forthcoming. 21 the same set of efficient portfolios ... as the semideviations (or semivariance) if probability distributions are symetric."2" Markowitz was able to develop a theory by which the advantage of diversification could be explained, or why investors should diversify their holdings instead of concentrating their investment in the secu- rity with the highest expected return. The application of this theory in the real world became extremely difficult because it required a quadratic programming solution. As inputs, it was necessary to have expected returns, standard deviations, and intersecurity correlations for each security included in the analysis. Markowitz developed an efficient frontier, but it would be the efficient market frontier only if all securities were included in the analysis. Portfolio selection would be completed by a set of indifference curves that WOU1d reflect investors' preferences. Markowitz was not able to make any statement regarding the risk return relationship of a specific security. James Tobin improved the analysis by allowing the inclusion of risk-free assets, and, as a consequence, the possibility of borrowing and lending.25 In his analysis he concludes that every investor must choose the level of the risk he is willing to take and need not select a particular stock or combination of stocks in a portfolio. An investor willing to accept more risk would borrow at the risk-free rate and invest in the market portfolio. Because he separates the 24Harry Markowitz, "Portfolio Selection," Journgl of Finance 7 (March 1952): 77-91; and Harry Markowitz, Portfolio Selection: Efficient Diversification of Investmemgg (New York: John Wiley & Sons, Inc., 1959). 25James Tobin, "Liquidity Preference as Behavior Towards Risk," Review of Economics Studies (February 1958): 65-86. 22 problem of the risk level of the optimal portfolio, Tobin's theory became known as the separation theorem. From the market portfolio to the risk-free asset was determined the so-called "capital market line." In the early sixties several authors, among them John Lintner and W. F. Sharpe, tried to develop theories of the risk-return rela- tionship for an individual security.26 The concept we will be dis- cussing, the BETA coefficient, became more p0pular after the publica- tion of Sharpe's work as well as that of J. L. Treynor.27 Its import- ance to the field was considered so great that for some it became the BETA revolution in finance. The BETA coefficient theory begins with the assumption that risk can be decomposed into two components. The first is systematic risk, that is, the part of the risk related to the market as a whole. This is also called the nondiversifiable risk because it cannot be diver- sified away. The second component is called unsystematic or 26Some of their contributions are listed below: By W. F. Sharpe: "A Simplified Model for Portfolio Analysis," Management Science 9 (January 1963): 227-93; "Capital Asset Price: A Theory of Market Equilibrium under Conditions of Risk, Journal of Fingnce 19 (September 1964): 425-42; "Risk Aversion in the Stock Market: Some Empirical Evidence," Journal of Finance 20 (September 1965): 416-22; and "Portfolio Analysis," Journal of Finance andgguamtitative Analysis 2 (June 1967): 76-84. By John Lintner: "The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets," Review of Economics and Statistics (February 1965): 13-37; and Security Prices, Risk and Maximal Gains from Diver- sification," Journal of Fingpce 20 (December 1965): 587-615. 27W. F. Sharpe, Portfg1io Theoryygnd Capital Markets (New York: McGraw-Hill Book Co., Inc., 1970); Treynor, "How to Rate Management of Investment Funds"; Treynor and Kay, "Can Mutual Funds Outguess the Market?"; and J. L. Treynor, W. F. William, Jr., Lawrence Fisher, and C. A. Higgins, "Using Portfolio Composition to Estimate Risk," Financial Analysts Jommmal 24 (September-October 1968): 93-100. 23 diversifiable risk since it is the specific risk of a particular security. Research has indicated that approximately 50 percent of the price fluctuation of an individual stock can be explained by the market investment, 10 percent by the industry, and 40 percent by the particular characteristics of the stock.28 The BETA measure of risk is the quantification of this comovement of returns of an individual security with the market returns. In the determination of the risk- return relationship for an individual security, the so—called Security Market Line, this component is basic. It not only relates dispersion of returns of the market and of the individual security, but also its covariance. The BETA measure also can be interpreted as the slope of the regression between the rate of return for an individual secu- rity and the whole market. Thus, the capital market theory, as it also is called, was able to help in finding a risk-return relationship for an individual security. In so doing a new measure of risk appeared, the BETA measure. The main advantage of this new approach to risk is that it is a measure relative to the market performance. It determines the sensitivity of a particular security to market changes. It is important to stress that some empirical studies have shown that this degree of volatility is reasonably stable.29 This means that ex post BETA measures can be used as ex ante risk estimates. 28B. F. King, "Market and Industry Factors in Stock Price Behavior," Journal of Business 9 (January 1966): 139-90. 29M. E. Blume, "On the Assessment of Risk," Journal of Finance 26 (March 1971): 1-10. 24 More recently, however, the capital asset pricing model has been questioned on the basis of several empirical studies. The principal conclusion is that while the relationship between expected rates of return of a stock or portfolio and its systematic risk is linear, it is not directly proportional.30 As a consequence, some changes have been prOposed in the model. This situation reflects the actual state of the arts of the finance field. Further research is needed to improve actual models. HOpefully, our research will con- tribute to this effort. 30Fisher Black, M. C. Jensen, and Myron Sholes, "The Capital Asset Pricing Model: Some Empirical Tests," in Studies in the Theory of Capita1pMarkets, M. C. Jensen, ed. (New York: Praeger Publishers, 1972); Irwin Friend, "Methodology in Finance," Journal of Finance 28 (May 1973): 257-72; and M. E. Blume and Irwin Friend, "A New Look at the Capital Asset Pricing Model," Journal of Fingpce 28 (March 1973): 19-37. CHAPTER II OBJECTIVES, HYPOTHESES, AND HYPOTHESIS TESTING In this chapter we will discuss the specific aspects of the research objectives discussed in broad scope in the previous chapter. From these objectives our hypotheses have been formulated. We also have given consideration to how these hypotheses will be tested. Tied to the consideration of hypothesis testing are certain aspects, such as sampling, discussion of which is delayed until the following chapter. Thus some statements related to hypothesis testing will be more clear after reading Chapter III. Objectives of the Research It was already pointed out that the main goal of this research is to measure the performance of certain types of securities (common and preferred stocks) listed on the Sao Paulo Securities Exchange. We mean by performance average rate of return. Related to this topic is the risk analysis. We have also discussed in the previous chapter how and why this study is important. We now will concentrate on the details by examining the specific objectives. Primapy Objectives Rates Qf_Return for the Stock Market This study's main objective is to measure the performance of the Brazilian securities exchange as a whole. The measurement will be 25 26 obtained by computing the annual average rate of return of investors in the stock market during the period January 1968 to December 1972. This objective was selected for several reasons: (1) The average annual rate of return indicates how well the stock market has per- formed and can be compared with other investment alternatives. (2) This ex post facto information can be used to form ex ante expec- tations if the specific time span covered and the factors external to the market operating during that period are borne in mind. (3) If the rate of return also is adjusted for the risk of a particular security, it can be used as the average required rate in stock valuation models. (4) Such information would enable us to determine whether the reinvest- ment of the cash proceeds would increase the rates of return to in- vestors. (5) Knowledge of the market's performance is basic to the investment decision process of investors, whether they be individual or institutional, domestic or foreign. Rates of Return for Commonygnd Preferred Stocks In essence the comments regarding the market as a whole made in the previous section will be repeated for each of two types of stocks, common and preferred. For both types of securities, nominal and real rates of return will be obtained. The purpose of these computations is to determine whether the market recognizes that there is a risk differ- ential between these two types of securities. Such recognition would be reflected in a differential rate of return. The differences between common and preferred stocks are the same in Brazil as in the United States. Voting power is a privilege of the common stockholders. The fixed percentage of dividends paid to 27 preferred stock generally is assurred by law and in the charter of the companies. This percentage normally is higher than that for com- mon stocks. If a company decides not to pay dividends, they are accumulated for preferred stockholders. Investors may not receive dividends in a given year, but they are credited for them, and in a later year they will be paid. This is not true in the case of common stock. Legally, preferred stock should be paid only the percentage specified in the company charter. The general assembly of the stockholders may decide to pay whatever they wish for the common over and above the minimum speci- fied in the charter. As we can see, a preferred stock could be con- sidered a fixed income security by the company. Preferred stock also has a prior claim in the event of liquidation. In exchange for this benefit and the assurance of a minimum dividend, preferred stock- holders give up their voting rights. In actual business practice they receive a dividend differential since they cannot vote. It should be noted that in Brazil the dividend policy is extremely old fashioned; dividends are paid as a percentage of the capital account and not as a percentage of earnings. The concept of dividend pay out and other dividend policies have been introduced only recently, and corporations and investors have not yet learned how to deal with them. Retes of Return by Sectors Average rates of return for different industries or sectors will be computed to determine which sectors perform differently in the stock market. Further research should investigate the reasons 28 for these differentials. Analysis of Risk and Return for Common and Preferred Securities Risk, as was discussed in the previous chapter, is a basic com- ponent in corporate finance and investment analysis. Returns and related risk are interrelated parts of the same problem. Risk was included in this study for the following reasons. (1) Risk and returns are two parameters of the same problem and should be jointly considered. (2) Risk must be considered because investors are interested not only in maximizing returns but also in minimizing risks. For any given level of risk returns should be maximized. (3) The risk consideration is basic in stock valuation models because the expected rate of return is determined for a certain level of risk. (4) Risk is extremely relevant in the discussion of portfolios and capital market theory. The essence of portfolio construction in- volves diversification. (5) We are interested in explaining a differ- eantial in return between common and preferred stocks (if there is any) as a result of the risk differential. Analysis of Risk and Return by18ectors An analysis of risk and return by industry sectors will help determine whether any existing differential in returns among different industries bears any relationship to the risk of these industries. Secondary50bjectives There are other study objectives less important in terms of our research emphasis. They are secondary due to their limited scope. 29 Test of the Actual Market Index The previous chapter explained how the Sao Paulo Securities Exchange Index (BOVESPA) is constructed and its assumptions. We also have indicated why we believe it is biased upward when the mar- ket is bullish and downward when it is bearish. A new index must be built, free from these methodological problems, to test whether or not this hypothesis is acceptable. As we will see in detail in the next chapter, we have constructed an index which we believe better represents the market's evolution. By doing so we are able to test how the BOVESPA has behaved relative to that index. Test of the Impact of the Reinvestment Decision Our index is built upon the assumption that the proceeds derived from dividends and the sale of rights are reinvested in the same securities from which they were derived. We would like to know the impact of this decision on the returns to investors. In other words, we would like to know if the returns are lower or higher due to this decision. For this purpose we have built for each stock, and for the market as a whole, new indexes which assume that dividends and pro- ceeds from the sale of rights are not reinvested but are held as cash. We would like to know the impact of pooling the cash proceeds and reinvesting them in the market portfolio instead of in the same security. Test of the Impact of the Weighting System As will be seen in the next chapter, the total market index is a weighted one of all securities included in our sample. For a 30 perfect representation of the real market situation this index is built by weighting each security according to its market value (number of shares multiplied by its price). Consequently, the secu— rities of the largest companies have greater weight. We would like to know how this index would differ from one in which all stocks have the same weight. What we are looking for is the impact of the size of companies on the market as a whole. Hypotheses The hypotheses that will be formulated are a natural consequence of the objectives of the study. It could be said that hypothesis formulation states our goals and objectives and is necessary to guide our efforts. The following hypotheses have been formulated for the period January 1968 to December 1972. (1) Was investment in the stock market a hedge against inflation? (2) Can the differential returns of common stocks be related to differentials in risk? (3) Can the differential returns of preferred stocks be related to differentials in risk? (4) Can the differential returns of all stocks in the market be related to differentials in risk? (5) Did common stocks provide a higher return than pre- ferred stocks to justify the higher risks involved? (6) Can the differential returns of the seventeen sectors studied be related to differentials in risk? Some secondary hypotheses, related to our secondary objectives, also can be formulated. (7) Was the actual market index BOVESPA biased as predicted? (8) was reinvestment of proceeds a better strategy than holding the proceeds in cash? 31 (9) Was reinvestment of cash proceeds in the same security a better strategy than reinvestment in the market portfolio? (10) Did company size have an impact on market performance? Hypothesis Testimg Now that the hypotheses have been formulated we will indicate how we plan to test them. As will become clear in the next chapter, we have worked with the total number of securities in the market during the twenty-one periods of observation, not with a sample. Consequently, the results obtained are a real representation of the total universe. The results will determine whether some hypotheses ought to be accepted or rejected. In other words, statistical techniques will not have to be used to test whether the results are a reliable repre- sentation of the universe. For other hypotheses regression analysis has been used and some statistical tests must be made. With these considerations in mind, the hypotheses will be tested in the follow- ing way. (1) Was investment in the stock market a hedge against inflation? By analyzing the tables of rates of returns on a real basis we can conclude whether or not reinvestment was a hedge against infla- tion. The existence of positive real rates of return is an indica- tion of such a hedge and of its magnitude. (2) Can the differential returns of common stocks be related to differential in risk? To test this hypothesis we will compute a linear regression of common stock rates of return on their risk measures. A null hypothesis 32 will be formulated and tested with the F test for a chosen level of significance. (3) Can the differential returns of preferred stocks be related to the differential in risk? The same procedure for item (2) will be used. The null hypothesis also will be tested by the F test for a chosen level of significance. (4) Can the differential returns of all securities be related to the differential risk? Once again the same procedure will be used, but in this case we will analyze both types of securities, common and preferred. (5) Did common stocks provide a higher return than preferred stocks to justify the higher risk involved? By comparing the rates of return of investment in common and preferred stocks with their respective measures of risk we hope to explain the differential in return due to a differential in risk. (6) Can the differential returns of the seventeen sectors studied be related to differentials in risks? Again the testing procedure will be the same as for the first three hypotheses. For each sector we will compute rates of returns as well as risk measures. (7) Was the actual market index BOVESPA biased as predicted? The simple comparison of both indexes will indicate whether the BOVESPA is biased and whether the biased pattern we have hypothesized is true. (8) Was the reinvestment of proceeds a better strategy than holding the proceeds in cash? 33 Again by simple comparison of both indexes with and without reinvestment we can test our hypothesis. This test also can be accomplished by comparison of the rates of return obtained by both decisions. (9) Was reinvestment of cash proceeds in the same security a better strategy than reinvestment in the market portfolio? The comparison of the indexes built under these different assumptions will test this hypothesis. (10) Did company size have an impact upon market performance? By comparing the indexes with different weighting assumptions we can test whether the size of the companies had any impact upon market performance. The rates of return can indicate the size of this impact, if any. CHAPTER III SAMPLING, DATA COLLECTION, AND COMPUTATIONAL PROCEDURE Having stated the importance and objectives of our research and having defined our hypotheses, we turn now to methodological consid- erations. A research study may not owe its success to methodology alone, but its impact may be lessened because of faults in the methodology used. We have tried to follow a methodology that would produce unbiased, reliable results. In so doing we went much further in certain phases of the study than we had thought would be necessary. The sampling size, as we shall see, is an example. Some methodological aspects were easily settled, such as how to compute rates of return and to measure risks. In other instances problems were encountered as to the weighting system to be used. The lack of plentiful and reliable statistical data is a serious problem in developing nations, and Brazil is no exception. The Brazilian stock market is relatively new and has grown rapidly. Con- sequently, several institutions, especially the stock exchange, were not fully prepared to cape with the needs of the market in terms of quantity and quality of data. However, efforts are being made, and the data used for the latter years covered by this research improved substantially as a consequence. Private services, such as Moodys and Standard & Poors, do not exist in Brazil. The only known service of this type is the 34 35 Organizacao SN - Consultores Financeiros. It has improved greatly in the last few years, but its data still are limited in terms of quantity published and by updating problems. These considerations will not surprise anyone who has dealt with developing countries' statistical data or who has had experience with security exchanges. These difficulties are stressed in order to explain the time required to complete this research and to emphasize the procedures required at different phases of the data collection process. Our problem became more serious when we decided to extend the period of study from four to five years and to work with the universe, rather than a sample. Sampling Measuring the historical rates of return for an individual secu- rity presents few methodological difficulties since the problem is one of computation according to established formulas. The same does not hold true, however, when one attempts to measure stockholders' average rates of return in a given market over a certain time period. In this case we are no longer dealing with a single security, but with a number of securities which are basically different. The aver- age rate of return becomes a statistical question which depends upon certain characteristics of the universe of securities, for example, the relative portion of the market accounted for by each security, and upon the techniques used to sample from that universe. Sampling is a key phase in the research process if we wish to obtain representative results. Therefore, considerable attention was given to the problem of finding a solution which is both 36 methodologically correct and feasible in terms of cost and time involved. There are basically two dimensions to the sampling question: time, or the period covered, and portfolio composition, or the securities studied and their proportions as representative of the market as a whole. Period Covered The time period over which rates of return are to be measured certainly will affect the study results. Ideally, one would choose a period of relative normalcy so that results might have some measure of generality. In this regard we were limited by the newness of the Brazilian market as well as by our inability to describe any stage of its development as normal. The evolution of the Brazilian securities exchange has been very rapid in comparison to its counterparts in other countries. Development of the Brazilian exchanges began with the Capital Market Law of 1965, in which the basic structure of the capital market in general and of security exchanges in particular was established. It was not until 1968, however, that the impact of these laws became apparent in the security exchanges. Only since 1968 has the market possessed adequate liquidity and a sufficiently wide selection of securities to inspire investor confidence in the market structure itself. For these reasons 1968 was chosen as the first year to be studied. The original plan was to investigate the four-year period 1968- 1971. In early 1971, however, the market experienced a significant - price movement which was, at least in part, the result of speculative 37 activity. The decision to extend the study through the fifth year, the end of 1972, was strongly influenced by this unusual market activity, and we feel this extension has improved the results sig- nificantly. Thus, the time frame includes an initial period of relative price stability followed by a strong bull market which turned bearish for the final year and a half. We believe this period represents a reasonable sample of market conditions as they are likely to be repeated in the future. Price observations were made at quarterly intervals, as were adjustments to the number of shares outstanding. These adjustments, which will be explained in detail below, are necessary to account for stock splits and dividends and changes resulting from new sub- scriptions. In all, twenty-one observations and adjustments were made to allow the computation of returns over twenty successive quarterly periods. Samplipgrfrom the Universe of Secmrities Our basic objective is to compute market average rates of return which are representative of the results obtained by naive investors. Logic requires that we recognize that all securities must be held at all times by someone. Thus, an overall average rate of return could be computed by weighting the rate of return for each security for a given time period by its value relative to the total value of the market. As an alternative we considered a random sample from the universe in which the probability of selecting any individual security was proportional to its value in relation to the value of the market 38 as a whole. In either case, the following considerations make any sampling decisions very difficult. (1) Since there was no pilot study available, we had no indication of the spread of the distribution of returns. Lacking the basic data, the selection of a sample size on the basis of confidence limits for the results proved to be impossible. (2) Considering that our universe in terms of numbers of companies is relatively small (no more than 300 companies were actively traded in the ending period), the statistical sample in any case would include a substantial part of this universe in order to assure its representativeness. (3) As was noted, the market is composed of many companies. These vary in importance, mainly in terms of size and market value, and these characteristics change through time. Thus, simple sampling would be inadequate, and use of a stratified sample would be indi- cated. (4) Since the study covers a period of five years, a sample representing the beginning period certainly would not be representa- tive of the last. By the same token, if the ending year is considered as the basis, the sample drawn will not reflect the earlier market situation. The market differed not only in terms of the universe of companies, but also in that any individual company could change in relative importance during the period. (5) To solve these problems, we must draw not one sample but several in order for our sample to represent the market at different points in time. The question is, how frequently must we sample? 39 This issue is very important when we consider that during the last few years the Brazilian stock market was very dynamic in terms of the many stocks that were admitted to the exchange. (6) Finally, it should be noted that any sampling technique may be questioned. Although extreme care may be taken in selecting the sample, the estimate obtained always is doubtful. Given these factors, and considering the relatively modest num- ber of securities traded on the Sao Paulo exchange in the earlier years of the period studied, we chose to work with the total uni- verse, but with some qualifications. Among these qualifications are the following: (1) From the exchange reports we selected all the companies traded, excluding those that had less than 10 trades (each trade is a buying and selling operation) during the year. We wanted a result representative of stocks actively traded. Any stock that does not have at least one trading operation per month cannot be considered actively traded. (2) A few companies were excluded from the sample because they were not considered representative since trading was halted in the middle of the study period. We could not discover the reasons for these delistings. (3) A very few companies, in sectors stimulated by fiscal in- centives, were excluded because the size of the capital is distorted. (4) Some companies were excluded when it was impossible to obtain the basic data necessary, after all sources of information had been used. In conclusion, we have used the entire universe in our study 40 with certain exceptions. This is the approach adopted by Lorie and Fisher, and, despite the additional effort and expense of such an exhaustive sample, we feel that the results are better as a result of this decision. The criteria used in the exclusion process might be questioned, but omissions were necessary in order to make the study feasible. The sample size is shown in Table 3-1,where sample size evolu- tion by quarters and for each type of security is indicated. Data Collection Procedpre This section will outline the data required and their sources. Appendix 1 presents a brief description of the mechanical procedures used to collect, prepare, and process these data. Data Required This section will indicate which data were desired. In those cases in which the exact data were unavailable, the assumptions made and surrogate data collected will be specified. (1) Prices at the Eng;of Each Quarter Since our study was made on a quarterly basis, we had to collect prices at the end of each quarter. To avoid the bias inherent in collecting on unrepresentative days, that is, the beginning or the end of the week, we chose, whenever possible, to collect prices on the last Wednesday of the quarter. We departed from this procedure when Wednesday fell on a holiday or its eve. During the first two years, trading volume was low on certain occasions, and prices could not be obtained on certain 41 .usmoawfiswfiu hum> uos ma Numa a“ oaanse uses umsu mowsmeaoo mo Hogans ecu .mmmo ham aH .mmonmmsms moaqmmaoo son on “Humatwoma Boom mowosum newcomeoo omosu “ado moooausfi defiumeuomda monsoon any .mvnum onu vsouxo ou oopaoov o3 use .Hnmalwoma mofiuoe onu uo>oo Ou moswamwo madmafiwwuo mos soumomou one 2 2m 8m EN EN a: a: o: as 42 .5 2: 3 S S 8 2 R 33336 m B 2 3 cm 3 a S 3 mm A S 2 S I s e s «a sausage I u. ems HS 4: as E i 8 S mm 3 mm mm RN 2 2 am 2 33338 m 1 s82: «sensosam -NHNNN ...338m in: o: 03 02 o: 2: NS 3 a: R S 8 R R mm 2 on 33238 m. m momiemmmefimeeeuamNom “338". sq me we as em mm Nm an «N mm NN Hm ea ma NH as oo :3 23 SR 83 HmmMMHMH MNHm mumzmu ¢.nun e.o¢u ..o¢- m.a_u «.m ¢.- o.- ¢.o~ «.mm o.~¢ m.~¢ ~.m¢ m.Nm ¢.oq .ew >.nn «w o.-u n.c~I m.p~I c.o~I o.os r.em ~.—c ~.cm o.¢m .¢.mm c.~m m.c~ ~.oo c.es o.n~ o.- w._c ~.em mm m.qc- «.0u- q.u4u o..¢n e.. >.em o.mm >.e¢ «.ru v.4m a.U¢ n.9e ..ol e.¢e m.a» ,.me ~.I¢ «.1. Nu «.mnu —.~nu c.~mu o.~n ..oe o.o¢_ n.~u o.~e c.~m “.me w.»o_ >.no 0.50 m.oc_ m.~o A.Nm o.r¢ ~m . a.rmu «.c«. «.0; c.¢~e .._~m a.¢.~ m.-— c.oo~ e.~o q.mn_ ~.n- e.c_~ w.mH~ u.pc— «.08 w.mm «e c.0ml o.om~ m.~m~ o.nmn nomad c.¢md m.c¢_ o.e~— cuoo. «.rm— c.0a— ~o0¢~ 5.mm— ¢.w5 ~.¢o no r.eua m.¢mc ¢.m¢~ c.mpm v.9nm x.wo~ w ems o.¢_~ c.—r# m._h~ r «as o.m¢e o.ma «.cr me ouscv ~omec o-mhe ~.~m— o-nnu e on. a.wo— m.~n~ oven» n.0n— F.0m. 0.00 o.ru no _.n«_~q :. s.¢c c.a« r.t~ u.xr. u.ue~ e.N—_ env~u <.~cr ..«e «.er en a once. p.0w1 rnn >.m on m.cm .o.»o.:n.¢h e.mo ~.o— ¢.m_ on 0.40 ¢.«w e.mm o.mod 0.00. o.m~# n.am_ c.~o. ¢.m« m.r~ ~m 2 . :«slav. .Irutfiyw a§£\,. u Irk? . .fiyun moon ~.Nv~ oaeaa n.e- c.w~p poac— musm m.- an ~.- n.oe~ ~.a- e.mm_ ~.eme q.o;~ ..Na M.ee em r.mm.~p.m- c.pcw 0.9mm ~.>nu e.m~ ~.a~ n~ c .<~I c .cr e.w~ r.mr m.-I noo~o «N z. . . . E ,_ Mano.— («$33.69 38.. 0.314.; ¢._<~ ~.—c ".cwI r.~qI :— . , .fiw! .Hsv Nude: nu “.mou m.o~u ~— e.cut.~—. czmremw>7.ma re—z w_mae same ....u! ... . ... . w .omna.c¢| e.—mI c.m¢| on—eu >.>ml o w: o._m o.mn «.mw 0.4: ¢.o¢ o.ea s.me r.nc o.me o.om v.55 >.m¢ m.o¢ em women acean a an ¢.mo ~.m_— c.on e.h®r w.nb on n.m- o.~on —.mc~ ~.~au o.no_ v.00 .mono an .cou a. r¢I 3.0m: m.~mu o.o~ r.oc m.m~_ o.mp . ~m e.mm ~.u> m.¢__ ~.~o~ r.«c_ c.«- m.cc. o.»¢ c.rc Ne o.m—I m.cmu e.o—I Oohu ».~—~ .mnm c.>_~ c.o~. o.-a o.ob~ w.o¢~ m._m~ ¢.hm_ areas ~.0m_ p.ne p.5n an e.-- o.c~n ~.eo o.aa~ >.~o~ m.om~ _ ~m_ m.c¢_ «.ow— s.o~_ 1.¢ms e.pme L._ie ..aal c.q. a.cr «q 0-muI OoN—N rower no~c¢ m.¢«n «.cow o.oou.o.«o. r.n«o m.em. o.mm. norm. c.—r~ o.oo~ n.bo m0 4.ooc_o.mom o.o~o «.xmm o.¢o~ c.wm~ ~.:.~ ~.~m~ «.oNN ».~NN o.m- :.oaw ~.es. 5.0., we m.~mw mine o.~m~ ..now «.3. 1.. 7a Fifi n63 .5: Fame“ 3!: ~43 n...» 3,. m. «or~m. ~n— ~.~m~ .m- m Nod 0.0mm r.c¢~ m.¢m~ m.5m~ ~.o¢~ m.~5 r.rc on T I I . . «.5: 0.7 To... 4 .3 «.2. n.5 n.3— eé: Tea 0.0.. w...» mm hump. m.a.» r.eq 5.x.r m.ew~.c.~<~ Named rnmcfl ~o~n ec¢u NM . p.ub_ r.¢o .c.nv~ n.9mwkn.eo: ¢.~pw Owen» “.09 won't are n._m o.¢om o.a- o.ea~ .:«e s .Cm— e. av m. ~¢ an wooem—¢.m0m m.~h~ Muaew c nm~ coOm. ~.r¢ rm . 0.: ..ee m.>c~ «.mm p.ou e.cu - A I J... a . , . A“: Thou «1inflh.ao....ma 3 m «a. 5. ca .orl 0.0nl e. . . . _ e.p~ m.~hu noomI «a a.mou m.¢pn N— —.m Ha .w 4: we re .e a, «w an - 4n mm «N ”n e— m~ we #0 cc A 7c~>e 5n >z2wa 3th, 555.5 56583.5”. .R >zomh<¢hm Hzmzpmm>z_m¢ .5m >z<¢=ou mo myocpm nuzxmmmmm mom zxzhmz mo mmhex HHI: m4mc 4. an c. 00 .m. , o.oo. e. no come on . u£1.o.£saonn to... do!. do! 9.43 734381.46... 03. an ~. can 4.4» p. as o.oo a. me m.aoa o. a. 4. 4o. nose. o.~o~ 4.40 ..oo 44 , 4.0.3 n.ao. 9.6.4 o.e.4 4.993 .404. a.o~. o.o~o v.44. o.-~.o.o~. a.~u. on ...: 4.0¢~ o.m¢~ m.o¢— «.mna n.o- n.504 0.044 women n.0m4 momma c.5o coco to o.no~ «.44. c.c~o n.oco «.mon 4.44. 4.n- o.c~o.~.o«o n.~o n... .uc; ..ope n.o~m ~.o.~ 4.4nN 4.~.. ~.om~ ow-~ o.Oo~ o.oo~ _.m4o .Noo o. ~o. No 4.9.. ~..o~ p.4oo “.444 «.444 4.594 a.4o. 4.6». n.0p. «.444 4.4a 4.4» no A 4.44. ..ooo,n.oom ~.n- 4.4. ...eo n.~no a..." ~.44. 4. one a... ~.oo on I_. .ao.onv.4I4.. 4.44. a4ou. gonad o.fio..eooo pooono oono on.» «.mn an . n.-o 4.4.. 4.04 ~.~o~ o..4_ 4.4mo N...— 4. on. 4.4» ~.oo «n o.~oa ..uo- o.uv~.o.un~.o.oo..o.~oo e.on. 4.6o 4.4. an. r.o~ —.o¢m c.4pu 0.554 ~.o- oo~¢4 come noun «N n.4noan..ou n.4uu p.nn~ 4.4». n.o¢ a... «4M o.o ..n» ~.oo. ~.o» m.oI 4.oI - souoo.noooo.o.ooo.o.oov 4.». an .4 0.004 c.mo ~.O¢I Nodal cu . . .gm.>~. o.~oI «.4»- ma. 4.4.- n.4eI ~o . . 4.1 . .. ..u-...a;..t. 4.4 .nawl on ~m on 4~ m~ - z~ ..wm . In. ~_ .4 as s zo_»au~e_mmqou ~ wa>p 5m >zz_mm oz 45m >zz0wa hDOIh03 m—mqa 0qwa .tn|~.00| 0.00! n.0NO OOMNI 0.0 0.0 0.0 0.0 0.0 0.0 0!0 0.0 0.0 0.0 0.0. 0.0 0.0 0.0 0.0 Om 5.0 N.ml 0.50! m.m~I 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 (.0 c.0 0.0 mm ooh! 0.m~l ~.0mi 0.0 0.0 0.0 0.0 0.0 0.0 0.0 .0.0 0.0 0.d, 0.0 0.0. 0.0 cow 0.0. Na 0.0m0 ~.oml 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0m n.0ml 0.0 0.0 0.0 0.0 0.0. 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 00 00 mm Nm 0m 00 me «0 00 «m mm NM 0m 0N MN NN 0N . 00 N0 N0 00 4 zo_»zz~ma 43514.: 02025050000 oz ..R 2528 “5 8.03m 65.040me mo... 20550 no $.20 m7: 502.0 1221 .mwlcocmv «com: cote- m.mn0 >.mc| o.»~t o.m~ c.c~ nocn soon n.o¢u o.¢ru >.o¢u 0.5m: ~.ocu o.m~s ¢.—m «.cr o.m¢ «.«n ~.—~u comm: o.nmn m.omu n.ou p.0m a.mm p.oo o.~m coc~u non: c.0cu c.u~ n.5c «.so~ o.oo— 0.00 o.n~ ~.>cn oo—c coonu m.mn. «.mcu ..cp cork: m.—m ~a~0_ coro~ hoopu oooo a.m~o o.m¢o o.o~o u.-c couo~ cacso m.»om c.o~m ~.m- m.rcn nouo. ooew coco oucwl noupv .-u0.m~n a.mcu c.omn n.m~u n.~nn p.mo o.nm moon c.om 0.5m —.cnl comm: cocci poem- ~o0¢| oocl Nov: acne .uouh c.n¢ coho: ~.mcu m.m~u mo~cu p.o s.~o o.co c._a ~.sm 9.»- c.m~ ~.onl doto don~a ~.oc~ o.~c_ ¢o~o 0.0m Noon: mgso couou p.00— «.—op o.«_' n.nra «.mo nommw oo~o~ ~.~m~ noo~_ coco——~o~o-0osoh uohmm comnw o.on-o.nuc oooo¢ 0.0m— u.m¢~ p.~—~ ~.oc NJ: «90!. mono- ~m ur ¢¢ me we uo tn mm wm ~m rm >h_m=umm mzz~m¢ car: m4m<~ coo~ n.oe Coon 00—6 docs Fohm copa— ¢o¢0~ comm ~o~o «oar! dons n.~¢ noon Oo~o Geno ¢.n~u o.e~u _om- o.uo~ o.~o coo~ acoun nooou cm mon— aomw p.c« c.pn oohm 0.0m come oo—o coon cock homo ¢.~c moo- m.nn_ mac» Oo—o ~.o_ won: moat ~oo~ noon- 0.0 6.0 #000 moan! acme moms“ noon ~.oc 09N¢ moon ~.~m coho cork note m..o o.¢c_ 0.00 Moo—u nomad como— noceu 0o0h~ «.00 ~.- ~06 coco nor—I Oocw moan Non.“ hoe—u woho coohn MN - Noeo soot mour coor ¢.~o dose n.oo c.~o o.co— c.~od ~.m—— o.-~ c.o~— co~p~ o.mm~ comm" _.om mo¢o ~.- ~.0p «.oa ~.o~ n.mm_ nomad a...» hoosa o.__r comcm n.~oo roman nonn— m.- coo~ 9.60 ~.o¢ >.co coov ~o0~u ~.o~¢ m.m¢_ o.s¢_ p.0au wo—ou o.on~ comww n.nc~ nuwou ..-— ~.~m. o.uou n.o- dooou ~o-a oouau oono~ c.0mn noorm munmo count canoe—conho Ldlaud am «a c.¢c o._c m.oo n.~c m.oo «.mm o._m c.¢~ m.¢o ¢.no o.~o_ ~.~o ~31 n6: p.n~_ m.oo o.o» o.oo n.0o o.nm «.oa noun o.n~. o._a «pond n.do o.oo~ c.oe~ p.p»— o.m—— ..oc o.o~ ncoa noon m.o n.- o.»o o.e~ n.up m._o o.mo n.p.~ o.ood c.~n_ c.—~. nowcu aim» n.oo~ o.o- min. ~62 c.n#. c.~o_ n.oo capo o.~o o.oo «.0: his» m.~o~ m.mm_ m.oo~ o.oo_ o.p- s.¢n~ Quay Nona o.s ~.n~ ooou m~ ~— zuahwa uc .meOFm zozzou mom zmapmg mo.mmp.m~ o.~uu ~— o.m«n ~— m—mam dam: ~.po p.00 em «.op 0.00 an ¢.nm cook «a o.moq coma «a n.o- o.~o_ tc u .3“ fix: no o.~o— o.oc— uo cue». hcuuu av v.00 o._m on homo coco mm c.hs o.no ~n moo—u nooo an «.o- ooao on ..cou ~.c~d n~ n.0m— c..o - 0o~n noun aw n.m~ o.o~ :— annn o.~— n— o.nm non ~— Ooc~o nu oo oo mw»«a 442—202 122 Rates of Return - With Reinvestment In this section we will be analyzing the rates of return with reinvestment for common and preferred stocks and for the total market. a) Rates of Return for Common Stock We can see in Table 4-14 that common stock has provided a nominal average rate of return of 60.7 percent for an investment made in January 1968 (code 00) and held to December 1972 (code 54); the real average rate of return was 34.9 percent. These rates are on an annual basis compounded annually. Investments made only for one quarter have had very wide fluctu- ations in terms of average rates of return; one such extreme case was a positive rate of 974.6 percent in real terms which dr0pped to a negative 77.4 percent. This is a reflection of rapid and sharp changes in the market during these five years. Short-run investment policy could provide substantial gains as well as losses, but the chances for gains were much greater than for losses. Since our study covered twenty quarters, investors could have 200 investment timing strategies by combining these observation points. For these 200 alternative investment timing strategies we had positive results in 163 cases and negative in 37; in nominal terms we had only 27 cases of negative return alternatives. -The highest return possible, 974.6 percent, was obtained in the first quarter of 1971; the second quarter of the same year also provided a fabulous return of 913.9 percent. The sharpest decline, -77.4 percent, was in the third quarter of the same year. By an analysis of the rows we can see that there also were 123 great changes in the average rates of return for long-term invest- ment, but obviously these changes were not so sharp as for short- run strategies. Investors who realized their gains by the end of the second quarter of 1971 obtained the highest rates of return. It is interesting to note, as can be seen in Table 4-15, that in real and nominal terms the year 1969 (from January to December) provided returns higher than those of 1971. These data show that, contrary to general belief, 1971 was not the best year, in terms of return, for the common stock market. TABLE 4-15 SUMMARY OF THE RATES OF RETURN FOR COMMON STOCKS Real Rates Nominal Rates Annual Cumulative Annual Cumulative 1968 - 8.6 - 8.6 10.6 10.6 1969 179.7 59.9 236.3 92.3 1970 35.0 51.1 61.0 81.6 1971 135.0 68.8 181.4 102.6 1972 - 49.9 34.9 - 36.4 60.7 The average rate of return for the entire period for common stock, 34.9 percent in real terms, shows that not only is common stock a hedge against inflation, but also that investment in the stock market provided a fabulous investment opportunity. For short- term investment alternatives the returns were negative in 37 out of 200 possible cases. This was more usual for investments made after 124 the first quarter of 1972. b) Rates of Return for Preferred Stocks Investment in preferred stocks from January 1968 to December 1972, as can be seen in Table 4-16, provided an average annual rate of return of 68.5 percent in nominal and 41.4 percent in real terms . Also, in the case of preferred, the investments made for only one quarter showed substantial changes. These ranged from a positive 736.5 percent to a negative 83.5 percent. The highest return possible on preferred, 736.5 percent in real terms, was obtained in the third quarter of 1970, not the first quarter of 1971, in which the return to preferred was 547.4 percent. For preferred stocks the chances for gains were higher than for losses since among the 200 investment alternatives there were only 30 cases of negative returns in real terms and only 22 cases on a nomdnal basis. Investors who realized their gains at the end of the fourth quarter of 1971 had higher returns. It is also interesting to note in Table 4-17 that, in nominal as well as real terms, for preferred stock the year 1969 was slightly better than 1971. 1225 ommINo¢wl more! cocci howl hoch hotel 0000! sore! (Corl- oovtm.v~| nooct OoNCO Ooh NoOQI Duos! ~o~01 Coat! #00:! mm wm .m «e >HHm=umm mzz~m¢ seem- nooml worn! hoe! uomc Oov~l nohui moc~t eon «.00— me 9.0m! ~ommI Noon- docwl Mao- noocl ~oh~l uONNI Nomwt Donal o.¢~ Hahn! ~¢ oo-c noNI ~o—I h.¢~ 0.00 0000 {open hoN coma coo— meta wood” nom- vouch ~¢ nouu onc— o.m~ noh~ no~m comm Moth Como OomOu Ono—u noo- Noow— mooom oo~h~ nqwo¢ o.~o~ keen room «.mn nooc noou nohm c.hu moved 0.00 mo¢o~ oowm— OoONN won»— hoOmo oohtm pupae o.nn~ poem on mm ..om ooom a.~o m.-_ c.c- coco— ¢.nmn c.¢om o._c~ m.c«p p.00 moo. 0.00 conn— r.o- NoOmN comm: n.oom cooon poNOO ~m mH-a o.e~ m.m~ ~.o~ o.mm ~.nn «.mo o.cna o.~o n.c~ m.~, non-n moor ~.cn con. ~.o- Ooo~u noon— hound ¢.pe none 0.00: um m4m ~n moan“ n.aN~ an moo- «coo ¢~ money noowa mm OomN~ coon ~N cor. «one an ooNn FoON #— n00~u 0.0m n— moOnw 0.00 Na nonwl an 00 oo mwhqc act—:02 126 TABLE 4-17 SUMMARY OF THE RATES OF RETURN FOR PREFERRED STOCKS Real Rates Nominal Rates Annual Cumulative Annual Cumulative 1968 6.4 6.4 28.7 28.7 1969 149.2 62.8 199.6 96.4 1970 72.8 66.1 106.0 99.5 1971 145.9 83.2 194.5 119.9 1972 - 49.8 41.4 - 42.0 68.5 Investment in preferred stocks provided a hedge against infla- tion. By providing a real average return of 41.4 percent for the total period, preferreds also represented a substantial investment opportunity. These returns averaged 6.5 percent, greater than those to common stocks. It also should be noted that the average rates of return on preferred stocks were more stable than those for common. c) [gates of Return for the Total Market Investment in the Brazilian stock market from January 1968 to December 1972 provided investors with an average annual rate of rreturn of 36.4 percent on a real basis and 62.5 percent on a nominal basis. These fabulous rates of return over the entire period have shown, during shorter periods, wide fluctuations above as well as below. Investment for only one quarter has provided positive real returns as high as 858.1 percent and as low as a negative 73.8 percent. Short-run changes were drastic during the overall period, and 127 timing could change substantially the return investors obtained. This is the result of a bull market followed by a sharp bear market. As the investment period increases, returns tend to be more stable, but the fluctuations are still large, indicating a market in constant change. Among the 200 investment timing strategies, there were only 34 cases of negative rates of return on a real basis and only 25 cases on a nominal basis. The year 1968 presented, in real terms, only negative returns, but 1969 showed a complete recovery from the previous year. Invest- ments made up to December 1969 gained very high returns with wide fluctuations, depending upon the starting point. Investments made until December 1970 were very high and more stable than those of the previous ending periods. Investors should have realized their gains by June 1971 since returns for periods ending at that observation point were always higher. That can be seen by comparing line 42 of Table 4-18 with the lines thereafter. That was obviously the peak of the market. Investments made up to December 1971 were all positive and very high, the only exception being investors who entered the market in the June peak. The pattern is constant from this point on. Returns are always high and positive, but lower than the return they would have obtained if they had left the market in the previous quarter. Investors who entered after the peak always had losses, except during one period of small recovery. The best timing strategy would have been to invest in December 12MB .01-0.01- 1.00- 0.00- 1.01- 1.00- 1.01- 0.11 1.01 0.01 0.01 0.11 0.01 1.11 0.00 0.00 0.00 1.10 0.10 0.01 00 0.01- ».00- 0.00- 0.01- 0.00- 0.11- 0.11 1.01 0.00 0.10 1.01 0.1. 0.11 0.10 0.10 1.10 1.00 0.00 1.10 10 0.01- 1.00- 0.01- 1.00- 1.1- 0.01 1.10 0.10 0.11 0.01 1.01 0.10 0.10 1.00 0.10 1.00 0.00 0.00 10 1.11- 0.1- 0.11- 1.01 0.00 0.:01 0.»01 1.00 0.00 1.00 0.10 0.00 0.10 0.10 «.0» 0.01 0.10 10 0.01 1.00- 0.00 1.011 0.001 0.001 0.00 0.10 0.00 0.01 0.001 0.001 1.00 0.10 0.10 0.11 00 0.1»- 1.00 1.001 0.001 0.101 0.00 1.10 0.00 0.00 0.011 0.011 0.101 1.10 0.10 1.01 10 0.000 0.000 0.100 0.010 0.101 0.001 0.011 1.011 0.111 0.001 0.101 1.011 0.011 0.00 10 11000 0.010 1.011 1.001 1.001 1.11 0.10 1.111 0.011 0.111 1.00 0.10 0.11 10 0.101 1.011 1.01 0.00 1.11 1.»0 1.00 1.10 0.01 1.01 0.00 1.00 01 0.001 1.01- 0.0 0.1- 1.01 0.»» 1.00 1.00 1.00 1.10 0.00 11 0.11- 1.01- 1.011 0.0 0.00 0.01 0000 1.11 0.00 0.11 11 0.10 0.11 1.01 1.101 0.001 0.011 1.00 0.00 1.00 11 0.01- 0.10 0.001 0.011 1.011 0.11 1.00 0.10 01 0.101 0.000 1.101 0.101 1.111 1.011 0.10 11 0.10» 0.001 0.001 0.011 1.10 0.00 11 0.101 0100 1.01 1.11 0.01 11 1.11... 401- 1 .1 ».0- 01 0.1 0.01 0.1- 11 1.01 1.0- 11 0.01- 11 110.00 1001. .11-».01- 1.10- 0.11- 0.01- 0.01- 0.1- 0.11 0.10 1.00 0.11 0.00 0.11 0.00 1.1» 0.11 0.1» 1.00 1.00 0.10 00 0.01- 1.00- 1.00- 0.01- 1.11- 0.1 0.00 1.10 1.01 0.00 1.10 .1.00 0.00 0.10 1.00 1.1. .1.11 1.11 0.00. 10 0.10- 0.10- 1.01- 0.01-.o.0 1.10 0.01 0.10 1.10 1.00 1.00 0.00 0.00 0.101 1.10 0.00 1.00 1.11 10 1.01- 0.11 0.01- 0100 1.111 1.011 0.001 1.41. 0.: 908 151.01. «usage-1110.13.11.93 0.1.01 1.0.00 11 0.10 1.11- 0.11 1.001 0.101 0.001 0.011 0.011 0.00 1.011 1.001 1.101 0.011 0.011 0.011 1.001 00 0.00- 0.11 0.101 1.001 0.101 0.011 1.011 1.101 1.111 0.001 1.101 1.10w20.011 0.011 0.011 10 0.11010.10010.110 0.110 1.101 1.111 1.001 0.001 0.011 1.011 1.111 0.111 0.101 0.101 10 0.1oo1w.110 1.100 0.001 0.001 1.001 1.111 0.10170.1u1 10011.0.011 0.111 0.111 10 .011 1.111 0.00 0.10 1.00 1.11 0.011 0.011 0.011 0.101 0.001 1.00 01 1.011 0.0- 0.11 1.01 0.10 0.011 0.011 0.101 0.11 1.10 0.01 11 1.00- 0.01- 0.01- 0.01 0.00 0.111 1.00 0.00 1.00 1.00 11 0.011 0.01 .10111 0.011:1.11~‘00-01 00311 1.011 «.00 11 1.01- 1.001 0.101 0.101 1.101 0.111 0.111 0.00 01 0.001 1.010 0.010 0.101 1.001 1.101 0.011 11 1.100 0.100 0.011 1.001 0.111 1.10 11 0.001 0.11 1.00 0.00 0.11 11 1.1 0.11 0.01 1.01 01 0.11 0.10 0.01 11 0.01 0.01 11 0.11- 11 10 10 10 00 10 10 10 01 11 11 11 01 11 11 11 01 11 11 00 00 zuapwa no mwbtm Adrulg >11m=uum mz21m¢ .hmx¢<: 1mm a ooumnoa NH m.mm m.~o sowumoacaanooHua w unmaafidum Hmownuomam on H.5HI m.HI muumm m>wuoaoun< was m>wuoaoua< ma N.MH w.qm meanness s «Hauxoa «H «.mm ~.Nm . wages: assesses“ Hooum MH «.ma «.5m mmsunasua unansm NH ~.~m s.mm wauwuoa massaauafi unwuaaamuuz HH «.mm a.~n mHmUfiaweuouuua a «Hausauno .Hfio oH o.ws H.- pamaasawm s>uom a suoaseumz mo H.os o.mH useamuu s “mama .sooz mo m.ms H.m~ pausesuumm no m.MH ¢.qm mandamuom masssauas means so m.m~ m.ms cosuunuumaou s uaoamu no q.aH m.am monummaa can possum so m.mH n.~q soon mo ~.sm o.mm mcosususumcH Hmsoamafia s means so Hood HmaHEoz uouomm muoo Chfiumm MO mwumm moaomm rm szhmm mo mmHm~n n.a~u o.~o «.on o.pn o.on «.n—u p.0au o.¢o ..ps n.oo~ ~.n- ~.o_u ¢ooo o.—n~ rono~ m.m- o.co_ o.~em o.oo~ o.nn ~.¢~c ~.¢o~ o.ooo-.nom - nawuuu .slm.m. . -, ..s a ~.uu ~._ o.no Mona o.o a.» o.pn n.~o Noe—a n.0u noun .¢.~o o.¢o o.co n.mnu m.~a. coon— «0Nuu NoNcN noONN Oocn— ~.ON— hoocn Ochoa NoOON nomad Doug! Fofitn 0on0 Goo—n carom aoh~N~00uflo toOhu no QM an, NM n.o~ p.- ~.o~ o.om o.o~ ~.o~ p.nn >.o¢ c.n« p.c~. o.o~ o.no a... o.np ~.pp ~.no coou— cooo— Nomad h.u- hound couun moo—u ~00N~ Mo~m— «ocwd womwu —oro~ Ooom— Genuu coCu— nocnu CoCO— Ooccu Oocnu cohmu ......Lmut ...me 5.5 n.... .~_- a... ..oo . . 03‘. .1... n.a~. "one dated conic o.uc ~.no o.cc o.no n.~n ~.nm ..un ~.n~ r.oo a... .m.w¢ ,~.ns o.o- o.ana ma~4_ ~.~n. ...o_ ..oo~ ~.oou «.oo. c.us. «.on. o.nn. o.ops ..ocn ~.4~. ...c. syncs ages" n.~n. ~.~n. ~.no_ «.3... ~45. mi: p.03 o.~n ~.nc o.oo o.~o~ o.cn- was. p.nn .ramo‘ n.oo o.cw c.op~ ~.o~_ c.oo~ o.~o¢ um ON nu ma mohumm mzo_h=p~hmz_ 4<_uz~0 0. com a. O- No Emu .33.. ~3an ~¢ at ~. CON 0 no don- cm mm ooh- noNl Non hon comm coco nooou coco ~om— oa‘fi.. .Po. .0. o.- o.on a... nonw— ~.oo~ p.00 n.»n 0.00 couun goon ~o.~| noon coma most ¢.~I c.o Noe: mod to: ecu! ~.o— u.—~ ¢.—— ~.pm unnm o.mn ..Oo o.>s coda o.hw oos~ co- 0.0! Now morn J- 1.. ...... . to at 0.9. m -I tilts/.nodflb . 0 .3. :3 o.c 0.. .. 0.: octu PM uoou cars a Mu c.—~ con~ 0 ~— oo~¢ pone n.0n ~ooo 4.40 none ..On— oonuu o.no pone o.nn n.4n Fond o.- no. c.o~ o.~n ~.~— ¢.o~- our bu...H ~.un 4 ¢ uoudl —n «w m~ Nn mwua m4m~ m.¢~ mm corn roam wr «cor ao¢w pm m.~m o.oo «4 Math coco no hocm ..cs ~4 mun: c.om uo oonm uocc 4n non: comm mm 5.00 roan NM 0.... moan um coma moms cw oo~o~ >63 MN 0.00 no»: - coca coon «a so- ooo~ :— uw—o coca n— moco m.¢~ ~u ~oo~0 nu m—nqn acme mvn a..%ono on oo~ too: an atom Mona um «.00 node an n.mo..¢woh 00 c.0a~ uooo~ me coon. ace—a N4 {.00 coco do echo ooh» cm o.oc~ ~.cc mm .Obao~ «.00. Na o.p- 5.50— um ~ooou coca“ o~ canon comma aw .34....Qoos - .:c «one - mono «com o— acao uocn n— noonu oomn Nu ~.—0 ~— ~— 00 «truce: 1338i ¢.- o.o~ c.pu ».o~ 4.4— m.-. o.- ~.o~ o.o~ o.- m.¢~ o.>~ c.cm c.o~ c.om 0.04 o.o¢ c.0m c._m m.oo m.cc most coon «own ~.mc o.on n.0m 0.04 coon -fiomn m.o~ —.- o.on monk p.~n m.~> m.~m 0.0m m.~o o.~o~ o.~o ..oo .~¢u~.mnu ~.m~u ~.mmu o.cmn ~.o¢u o.a~- o.m~u n.ouu o.~ ...- ~.c- w.~- o.p~ m... n.o~u ~.~_u o.mmu o.~mu n._mn o.c~u o.ou «.mu n.o a.mu 5.: o.~ c.¢~ o.- m.o h.w«u ..ocu «.omu o.m.u ..m- 4.”- o.m. «.c. 9.. ~.m ..cm ..om ~.~ou o.mmo ~.~ou o.o~u a.»u o.nu o.oa o.~- o.c n.o o.~n o.»~ o.¢¢u ~.o~n ~.~ ~.r— 0.5— o.o¢ o.~. «.cm 4.5— m.oo m.~¢ o.~cu ~._¢ ~.om ¢.no n.~s c.c~ w.c¢ o.o~ ~.oo s.~n ~.moc~m.¢en o.co~ ..mcn o.~o c..c~ m.m~ ..m- »._c~ o.oe n.mc n.ro c.- o.o¢ o.c~ o.ep ~.~o o.¢~ e.oo~ >.a —..« ~.o_ «.o» c.—o p.4nn can 9.0! o.>u o.u0. coco 0.90- ..c.n ~.o—n o.oo o.¢c - . cocoa ~.¢n agno—_¢.o~u o.mm- 0.... «.... ~.oc~.c.ae~ o.o~u .owno.p~s o.m_u ~.m~o ~.o~c o.~¢c.o.ou ~.~ _o n.- 4.0 o.»~ ..m— o.oo 9.0m ~.>_u m.— ~.-u o.-u.o.ncu 4.»: o.o .s. ~.on n.e~ o.¢~ o.o~ o.o¢ «.44 o.n~ o.c~u n.6nc —.ocs_¢.ot o.- 4.0. >.rn a... o.o~ u.n~ ..on o.on o.rmu a.»¢n ~.~o- s.mu o.c. ~.r— o.om ».p_ ¢.om ~.n~ c.om m.nm woucu pone: b.0— c.9n n.nn ~ooo coon mono 0.0M ciao o.~> o.ocn >.op c.no n.- m.~o~ o.cn o.ce o.mm c.¢o_ n.oo «.mnnuo.ono n.0mw n.~>~ o.~nd o.~o~ booed ~.n- mecca o._.~ c.~p c.on. ~.~c ..oc m.sm ~.o_~ n.no ~.on o.oc~ n.om o.om a.~c o.n.—.n.n . o.ocn o.m~ ~.~o a... ..nns “.4 a. o.¢0| n.~ ”.mu n.oou mach «.mos —.co n.~m~ o.om~ n.n_s o.~ow o.oea o.ooo~o.-m 0.8 on ~n pm to no we .4 on an ~n ~n ¢~ ,n~ - _~ aopumw mu_pw<4m =z< mmmmam u:» «on zzzhmm mo mmh ~.~> o.No o.om. ~.rm~ ~.n0 «.00 o.«» 0.0. oorhp honma 0.0uu 0.00u o.Nu— ~.0o~ 333.3... .... . . 04! 0.MN~ bnlaN Nm up 0N MN m.can o.n»~ . 0.09 NN uN «chumm zo_hu=¢hmzou az< hzuzmu mxh mom zz=hum ma muh~. n.~o an ~.so~ o...— ..o.~ ».om~ ..~. .~ m...~ «.... ....s a...“ c.nn h~ ..oo~ a...“ n.noa ~.p- o.on - ..oas ~.o- >.r- ..~n— .... «a ... a... ~.om ...2. .— ~.n- «.0. ...~- n. ...N 0...- ~. «...- as m.mac 3cm. a... ...-...». «...: ......» .... a. s... o.o~ .0. o.- a... mm a... n.oo .9... n... m... «a o..o_ ..oo o.noa ~.~o~ a... "a a...“ o.oo. c.... o.«- N... .. ....— o.o- «.... ~.u«. m.oo no ~.~$ “.03 0.2.— 9.3 oz...— 3 n.po~ ~.o~. a.~ud a.... ...E— so .6! 0.02 9.00s .6: u... on m..o— ...». 0..“— u...“ ...» n. .... p.952 9.. «n 0.3.— 3: up ~.o ~ n.naa n a. «.mps p... an «.... s.o.~ n.no~ ¢.o.~ n..o. o. a...» o.c- m.cmm N...» a... n~ ...: rieimtw n.3— n..00 «a ~.~ao.n..- m..»~ s.na~ ..a. _~ n.o— u..- n..o c..- .. s.-~...~.a c..- n. a... m.... ~. m..¢- _. ._ n. a. .. co zaapwa up «a... 3.2.xa: 114C) .m0u..~0u 0.00: ..0.. 0.00- 0.0.- 0...: 0.00: ..00- ~.~0u o.-u 0.0.: 0.0.: 0.00- 0.0.- 0.00- 0.00- ..~0- ~.00u 0.00: ..00- ....u 0.0~- 0..0- ....n 0.00: 0.00- 0...- ..00- 0.00- ..0.. 0.00: 0.00- 0.00 0.00 0.0.: 0.o~c ~.0n ..00 0.000 0.o- ....0 0.000 0.000 ..m. .15 .! . «.... .... .y . ... ..0- 0.0- 0.0.: v.00: 0.0..r0..~ue0u«4. ..0 0.~ 0.00- ~.o.n 0.00: 0...: ..oul w. o 0.0 «.000 0.00- 0.0.- 0.00.2...0- 0.01 ..0 0...- ...0- «.00- 0...- n.~s ~.. 0.m~n 0.00- ...01 ...n 0.00 0.0.: «.00- 0.~0 0.~0 04000.01000 0.000 ...00. ~..0~ ..o. .1? . .11. 00 00 00 .. n. 0. 0. .n 00 «.0I 0.000 ....I ..pul 0.00 0.»: 0.00: 0.00: 0.00: 0.00 a..- 0.00- 0.0—0 0.00: 0.00 o.~l ~.h| 0.00 0.0- 0.00 0.0~ 0.00 ..0 0.. 0.00 0.00 0.0N 0.00 0.00 0.00 0.n~0 0.00 p.00 0.00 0.00 ~.c~0 0.00 0.00 0.00 0.00 0.00 0.00 0.0 0.0 0.00 ..I, 0.. .... .. 43. 0.~nn 0.-I 0. ~0 n.~ .. .. 0.0.1.8.. ...... ~.0I 0.00 .0..00 «.0 «.0 0.0 000 0.00 0.0 ~.0 0.0 ~.0 ..nu 0.00 0.0 0.0 9.0 0.0— 0.00 0.00 0.0 0.0 0.00 0.00 0.00 0.0m 0.0 0.00 0.00 0.00 0.00 ~.0 ~.h0 ~.~p— o.~0—.«900 0.0. 0.00 0.000 0.50 n.0h 0.00 0.0p 0.00 n.~n ~.0~ 0.- 0.00 ~.~o0 0.00 0.00 0.00 0.00 9.00.304...” . .00 ., .. ,7.-. 0.0.3... a.~0 0.0» p.0h0 NM 00 0~ MN - «chumm 020000n 0.000 0.00» 0.oc-0.0no ~.c¢-c.o—0 0.0h0 h.~h-o.~00 —.~o0-.00¢ ...V J . l A v. c.’ I U . .04 V.... , .I {on ..nuo.onu n.0nu o.p.u ”.mun 0.0m- ~.o .... «.0. n.~o o.p~- n.0nu p.00- . nu ~.o~u m.o— p.~m —.o~. 0.0.. 0.0.: 0.o0: m.ncv 0.0a..o.0n 0..» ~.op~ 5.0.0 ..-u ~.n.n ...w- n.no 0.o~0 ~..m~ o.~c~ «.0. ~.m~ 9.... ~.no~ n.no. ..on. o.nn o.oom n.o~. ~.n»> a..oa o.¢~n—p.ooo—~.nwm_..¢p~ o.o.~ n.-o~n.m~. ¢ . cocmon—ODOm ~.Gn . .1”... ... u ....1. .. In an '0 {0 n0 NO at cm Mn Nn p.00 towh v.00 ~.o~u 0.c- 0.00N «.000 ~.mn~ ~.h- .... 0.. 2 «.1. 0.00 p.00. ¢.o~— n.0h0 0.00« 0.000 c.~0¢ 0.000 hpihw 0.00 —n 0.~0 0.h0 0.00 0.00 code m.m> 0.004 0.00 o.sr~ h.0¢u ~.O~N 0.05— >.sh~ ~.0- 0.00— 0.00“ 0.0m“ P.¢c~ “0.0 ‘nwo. 0.0 0.0 Lima ~00 0.x 0.0» n.00 0.00 Gown 0.0—u «.00u m.~0— 0.0nu o.un~ h.ho~ c.¢0~ 0.0MN «ohmn.doco~ h.00~ d.co~ Oofidfl.N.miu o.0~ 0.c~ .aounu yuuwm..«qu. Noh~ 0N mm 0.00 cook ¢.~o ~.0~— 0.msu 0.00N c.00n 0.¢e~ n.00— .0060 0.00 n.~Q 0.000 c.0n0 «.00 co—uu b.0nu n.~0~ 0.000 0.00N 0.h—n o.m¢~ 0.00 ...... a...“ donuN 0.000 achumw mm-4~h¢mm mm» mom zzahuz mo mmh> 0.- 0.00 0.00 0.o~ NF o.H¢ 0.00 v.0» 0.00 0.~n an 0.~m_ 0.00— ~.mc 0.~0 p.00 0N p.00u 0.00, 5.0—» m.~0 ~.—0 m~ N.mo~ 0.00 0.00 ~.n~ m.c— «N ~.~0u ~.cm 0.00 0.00 0.0 as 0.0« n.«r o.rwl ~.oul 0. 0.0~ ~.~mu e.~nn 00 0.00: 0.00- ~— 0.00. ~— 0—000 aqua coco. 0.po 0.0. 0.0. _.m~ 00 n.0- 0.000 0.ho— n.—o ..N0 M0 comma n.p~— >.-u 0.~o~ p.09 N0 ~.o0~ ~.—0~ c.00— 0.00— «.00— —0 o.~—m 0.05m F.00~ c.~0— 0.00~ 00 0.~¢~ cou- 0.mo~ m.00~ p.0ou n0 0.0FN ~100N o.0- 0.00— ~.0r— «v ~.o- 0.00" 0.00— n.~0~ 0.-~ uc b.~0~ 0.000.06u0u ¢.0- —.0o 00 0.oc~ 0.00 0.00 0.00 «.00 mm nun—muaoututhoho -0.¢037b§00 ‘Nl ..en~ n.n~— n.00— ~.m~ a... 0n Fochn o.~0u dour» 0.00 0.00 ON p.00w 0.ho~ n.00u 0.00 ~.uh 0N .O3nda.finfifla0eo0o #000 o.~n UN mohaN hcnmu 0.00 n.0r m.- «N o.~0 h.h0 0.0 oo~0 c— ~.~0 0.00: ~.o—u nu ~.~0| «.00: um 0.0:! «0 0n an my ad co zuapuc no map-u 002—102 1112 .0! ~.0~I 0.00 c.o~l m.>~| o.-| ~.ml 0.00: n..n| ~.¢. 0.0m- c.0mn ~.00I 0.:0I 0.0NI .0! 0.0! ~.h 0.0—l n.0nl 0.0a o.—u 0.—~I O.o~l 0.0m 0.h~l 0.0Nl ~.u0l n.~0I —.0~l hx‘ M0 N0 ~0 00 n0 0.~nl 0.0! 0oh 0.0m- no~l n.0— F.0Mi ~.~ 0.0— 0.~0l 0.—I n.0u 0.00! 0.00 0.00 0.00! ~.h0 0.00u 0.00h 0.0mm 0.0N. n.-l 0.- 0.0N ~.0~I —.0— p.00 0.0Ni 0.0m p.00 0.00- n.p~ 0.0m o.~M| 0.00 ~.~0 ~.00I n.on~ n.~0— 0.000 0.n00 0.0ha ~0 «0 0n ~.m 0.0 0.0 ~.0 0.0 «.0. o.» —.0 0.~m 0.00 5.00 ~.00 s..0. o..0. n.o~ ~.0~ 0.0N0 0.00 L. 0.”. ~.0~ 0.m~ 0.n~ ~.0~ 0.0N 0.00 ..0~ 0.00 ~.~0 0.00 0.00 r.—0 0..0~ 0.00— 0.~0 0.00 0.00! 0.00 0.00 00 um o. 0: 0.0— ~.0~ 0.0a 0.hu o.hn 0.00 o.~0 0.»— 0.:u' 0.0! 0w096 an s.>u ~.n.u 0.»: 0.0—I ..0: 0...- 0.0. 0.0.: 0.0 p.0u 0.0 ..n: n.0~ ¢.h 0.n.c 0.n~n 0.~mu 0.00: 0.09- «.000 0.00- 0.00: 0.00! 00000 0.000 0.0 0.~ 0.0 ~.~ o..— ~.n 0.0 ... 0.0~ 0.~— >..n 0.0. 0.~0 o.o~ 0.0 0.0- 0.00I‘0.0No p.o.o ..o~u 77.115500 0.~nl 0.000 0.00I 0~ n~ ~.0.u 0.0a! ..0pt 0.h~| 0.00 0.0! 0.0 0.0NI ~.¢mu nJh0I 0.00- 5.00! P.0nl 0.0 0.0 0.. 0.0- 0.0 p... ..- 0.0.: anNv ~.-- 05.01 ~«pno «inn- 0.0.- «w 0.0- 0.0: 0.51 0.00 0.0I 0.— m... 0.0—I 0.0~o .010NI 0.00: 0.0“! 0.0.0 F.0N 0.00— ~.o 0.0 ~.o. 0.0 0.0— o.nN 0.00 «.0 0... ~..- ...»? ...- 0.00 0.80— uN achumm mu~=m0p ...0. ..n 0. ~.onn ..0.~ 0..». n. o.... ....n m. ~.mon .. 0.040 .cwa 0.0. m.o~ n.00 o.~. o... .0 c.o. 0..m ..m. ~.om ..o~ n0 ~.- 0.0n ~.r0 p.00 o..~ «0 ~..~ a... c.00 0.00 ~..~ .0 «.mm 0.00 o.~0 ~..p ~.o« .0 0.00 0.00 ...s 0.0. a... r. 0.~n ...~ 0.00 n.»o 0.~0 «0 ..nw 0.~0 ...0 0..» m.- .0 .... 0.~n 0.00 nw00 0.00 00 p... ~.o0 ..n0 0.05 0.~. an 0.0. 0.00 .00, 0.2. 0.04 .«n 0.- 0.~0 awo 0.p0. 0.0~ .n h.~0 0.00 n.~n. 0.00. p.00 0w 0.-. 0.~>. 0.p.~ 0..- ~.~0 n~. n.00~.o.0.n .1000 0on~n 0.0n - 0.000 ..000 o.... 0.000 0.00 .~ 0.0m. ..n00 0.00. ...~ 0. 0.000 ..~mm m.0~n m. 0.000 0.whl «a a.po- .. 0. n. u. .. oo zaapwa no nmyau 0.2.2:: 1413 .0000.000 0.000 0.000 0.0NI ~.000 0.000 0.000 «.000 0.—00 .000—.0N0 u.~00 «.000 00 —.0~0 0.000 0.000 0.000 0.000 ~.0~0 ~0 an 00 0.000 (.000 «.000 0.~00 0.~00 0.000 0.000 0.000 n.~n0 0.000 00 n.000 0.000 0.—00 ~.n00 0.000 0.000 0.hm0 0.000 0.000 0.000 0.000 5.000 ~0 ~.00 0.00 0.0~ N.~ 0.~m ~.0N 0.0 —.00 0.00 ~.um 0.00 h.nh 0.hC~ 0.Nh— 0.0—— 0.00N m.h0n 0.~0~ h.00k~0.P~N—0.un0 ooopm 0.0M— 0.Mu0 P.O~ 9.00 «.00 0.0~ $.00 0.00 0.0N 0.0» 0.00 0.00 u.00~ 0.000 0.00— F.0NN 0.00“ 0.0km ~.000 n.00~ 0.00000.0000’.000 0.000 0.uh~ 0.00 1.1.“. .440 ~0 Cm mm 0.r0 0.00 0.00 0.000 n.00u 0.00N ~.h00 0.00— 0.00 0.~0~ ~0 0.00 h.m~ 0.—0 p.h0 0.00 0.0- ~.~0~ b.00 0.0 u.0u 0.0~0 0.00 0.00 0.00 0.00 «.00— 0.00— 0.~0~ 0.00 0.0~ 0.00 0.>«0 an 0~00 mgm.- 0.0~ 0.0m 0.~0 0.00 0.0—. 0.0»— m.- 0.0~ 0.00 n.0~ 0.00— 0.00 «.00 0.00 0.00 c.0fln ~.n0~ 0.NM~ ~.50~ p.00 —.00 0.00 0.00— 0N «.mu ~.0~ 0..“ p.0. 0.00 0.00 0.0—— 0.00 ..p _.0 p.000 0.00 m.mmu 0N ~.- 0.50 0.- 0.0m 0.00 0.00 ~..o 0.~m N.0 ~.00 0.00 0.~00 ~.—l —.mn 0.00 0.00 0.00 0.~0 n.00u 0.00u 0.00 0.0N 0.0~ .n.0~ «.000 0.0~ NN 0.00 0.~r 0.00 ~.0. 0.00 ~.00 0.00 0.- 0.00 5.0. 0.00 c.~0 m.ra 0.000 0.00— ...mu 0.00. «.000 0.00— ~..c~ 0.00— ...0 0.0~_ 0.000 0.00 0.00 0.00 0.00 ~.p—~ 0.000 ~.0~ 0.0- 0.00— 0.-u ~.Fba 0.00— ~.p- 0.000 0.000 0.000 0.000 0.00m a.00«mh.00——0.0—0 0.00010.00~ 0.50 p.00 p.00 0.0. 0.0» 0.00 0.00 0.00 0.00~ 0.—0— 0.n~— 0.00— h.0- 0.000 0.00— 0.00~ 0.00— 0.000 ~.00~ 0.-~ 0.00~ n.0- 0.0m— 0.00~ 0.00— 0.00 0.000 ~.-u 0.0—_ 0.~0~ ~.>0_ 0.00— n.0ua 0.000 0.000 nanm~ 0.000 0.000 0.00~ 0.00~ m.n—0 0.000 0.000 n.~oo o.~n~ m.~o~ .... a... ..ndn .~ .. .. ~. 20:.»uc at mogumm hzm=m_=0m >>¢mz_=u o.ncn p.0cp ‘ _.nno~o.~o~p~.~no_a.o.o «nuiunocum0u~.ocs _ o.o o.~o “7 sooo .n.€€4 a». ; rgr» ..r . . . an «a .r cc re we .9. on no Np o... «.pu OoC' m.»c ..ms ..nn o.m»~ o.~o ~.¢ou c.~mw o.oon «can eo¢r 0050 c.00— mecca hooc oorwN coauu moral cowhi N000! «n ~.w~ coo~ «on» «.0: mchc comb ~.m¢~ romc~ s.~nu cocci coho- Ooh- 0.9: ~.nm can. —.o- cocwu coho“ pcxo~ ~osc~ oom~u comma nouou ngne~ ON ¢.¢~ _.F~ coom comm n.0m ~oco o.cu— ..hn ro~4c 0.001 0.00! can— c.cm| nomm p.00 ro—o o.mc 040: «amp comm— done Gown! earn! «omml hopn Gown! NN ~.cm w.nc o.~e c.pm m.cm o.¢m n.o¢ o.mo _..c p.mn m._o «..p c.oo «.om c.o¢ c.rm «.mo p.sc n.~» c.co s._c c.~c_ ~.mo c.—c o.~o ~.o¢ m.~o o.me c.~» «.on o.mo. c._- o.oc~ o.n- m.~c_ p.0o. o.o- m.mc~ ~.oo ».¢o p.o- o.- o.n~ c.a c.~ a..- 9.0— p.o~ n.~. ..e n.»~- ~.o. ~.- o.p ~..- n.nc. ..oo~ n.n~. ~.~o o.uo ~.oo_ n.o¢~ ..mc_ ~.- ~.no ¢.~po o.o_m a.cm~ r.o¢. ».«c o.oc~ p.oc~ c..« N.»— p.n. noon o.p~1 m.¢_- c.cm- c.ncn 9.0m c.o~ o.oo o.no ~.am o.oo ..sp c.cs —.oo m.om m.no o.cc~ o.oo ~.oo ~.os c.n- o.cn~ ~.m~_ m.~dd m.oo ~.cm_ o.~c' n.p«. o.s_. o.oo o.»u. n.~n_ ~..- ~.po. c.oo c.0ww ~.o- o.go~ ..Nsw.~.~e~ o.ae_ ~.oo~ o.oc_ n.m- n.~o_ n.~. m.mn n.mn c._n n.- 5..” o.~¢ ~.—c m.mn ~.m~ «.ou p.~r «.n« o.»« ..o. «.oo— n.-~ o..p~ o.o- o.~o ».om~ ~.~o~ 0.0:“ p.00” u.~p o.n»~d~.emo ”.mNn o.>o~ ».o- «33 64.3 n.3, boon o.nn o.>~ ~.~- o.o 0.».a p.~nu - .~ o— n. ~— zuarwa «a achuuw m4 an hooo nomw at oooor o.>o co h.no moor no newcu OJ: ~c o.mo~ «.00 do >.on ~oum en ~.cn nocm mp n.o~ ~.o~ ~n acaw coco up 0.0. not» o~ ~.m- o.oc~ n~ Doom n.nn «a con~ oom~ - ".0“ ~.n~ :— mcww c.~n nu cote» once «u n.0n nu ~u co v.95... .3259. 145 .Nniwohul «ovNI 0.00 0.0: 0.0»! .o..¢.oc "...- N.oo ? nu ~m 0.0 p.07 .0 o.m.- ..occ m.~.u c...- m.moq o.omu ~.o~u m.pou m.—ma u 0.001m03000. ~.~mu ~.mnu 04500.“.000 no~fii monhl oo~00 N.m¢l to at ~.0¢I {.muu o.h~ o.~— n.h¢l 0.00 ~.nm ~.¢~ 0.00! h.¢~l m.—n oouw ”.000 n.ht 0.00 0.00 0.00I n.00 wooed 0.00 ~.00I ho¢oa Ooo~m novhu ¢.oom~o.hc-o.h~¢ honno~b.co— ¢.«wl L 1.: .{d w .5: Neat- «out 0.90 0.00 0.000 0.0 —.00 0.00 0.0 0.00 0.00 ¢.hml ¢.o~ 0.00 o.uo o.>¢l b.9h 0.00— o.~r~ cocci 0.0- hoc~c h.nm~ 0.090—0.oon~0.m~0 ~.-n-.0c~ . ~.tan N0 «0 {a 00 ~.- m.m~ _.- n.0m 0.00 0.00— 0.00 ~.~m~ 0.0“. o.-— 0.0. 0.0: p.0nc ‘09—»..mwaw-u «dOI ,.1 ‘ «.2 18 0.00 n.0n N.cc 0.0N wooo hoom ~.0~— 0.~h n.¢0~ n.00— 0.00.0. 0.2.— 0.~o~ n.00 v.0» .m..~- 0.00 h.-l 3...... Nn an ... ~.~ ...“ o.o ~..~ ~.. o.- ~.- o.~n ...» a... o.nn ~..- o.mo a... m.- «.0! hohdo an- .. ... .2... .mawt v.00- 0&0»u.¢.0 .. «.mcl o.»~ p.00 nocr 0.0N u..n n.o~ 0.0¢ «.00 .... n.e. n..._ o.nc o.nr. ..o~. a... o.~n 9.3 0...... n.o~ o.” .0.~n ~.~¢ nova ~.0¢ ~.OP cooou hohnu cons ,o\nw m.nn 0m¥3 t~u~J.m)ON; 0 pm" u.¢~ 0.00 AOOQI mofin conch ¢N EN NN 0.0N Font o.¢n hocu ~.¢m momm none uoho cock 0.00 cone .o.m- noh~u o.mo~ «.00 corn— hoom mock ‘o.¢$ .0000 «.00 Oahpu Npfiuu hooow ..o~u,o.od~ m...— n...— ~.men ~.o~m n.wbn ..om~ ..ooo o.om~ ~.onn p.on~ ‘gb.00030wma~_0u~0~ ..m o.u. 1:: ..oc m.os o.~o ~.op ~.uo a... o.oo ..no m.co ~.mo 0.00 0... ~.- m.oou 0.». n... o..o~ _.»m~ o.n~. n.o- ~.~n~ o.o»~ o.nnu o.~md n.n»~ o.o- 0.09—‘0wnuu a..._ o.~a~ n.~.u.o.~.~ alofnéz «.3 9.3— o.~o ..ccg n.a~. ~.m- «.05 .0..¢~.~.ona.pwon.w o.~pa ~.oo~ a.»o~ m...“ ~.¢p~ o.ocm ~.o-.—.¢e~ p.000 tonoo 0.3%0‘3ygnig. 0.00. . ~.~n-~.~u~ m.~n~ ~.no 1.»! um on «shown ozmzmwmom oz_a=guz~ >om=44! n.00 0.0“ —.- s.—«! 0.0~ 0.0 0.0— 0.0! 0.00 b.0N 0.~n 0.0—I p.00 ~.0n 0.00 “.00 0.00“ >.u0 0.0h 0.000—n.00-~.00n ~.~0~ ~.ho0 0on0u o.nu~ ~.0n! «.m! N400 0.0 0.u0 °.~n 0.00 0.0 0.00 0.00 ~.00 0.0! h.~0 n.0~ 0.00 «.0 0.0» 0.~0 0.00 0.0 ~.h0 o.u0 0.00 N.00 ~.0- u.ku~ 0.-— N.>00u°.~h¢u~.u00 0.0~0 0.00-h.00u 0.F0~ 0.0N! 0.0— 0.00 we 00 00 NM 0.0 0.0— «.0 hoc~ 0.0N 0.00 0.~0~ 0.00 ~.0~! 0.00! ~.0~ 0.0m 0.h~ 0.00 0.0h 0.¢¢~ o.—0 cofl 0.um ..-., «0 NM-: mgm~ o.o .0300 0.0a 0.c~ 0.0a 0.40. 0.00m o.mm o..— ~.co «.0. 0oh0~ ~.~0 .0.0p¢—0.-~ b.mmu c.u0 0400 o... o.~. 0.—0 0.00. 0..» «.0. m..m 0.0._ «.05 0.«0 o.0- ~.oo~ ..op o.co p.o. c.90" 0.0» ».~. 0.00 0.00 ~.o~ u... «.3 0.0. ~.0m~ 0.0» ......n.u. o.0>0~0.00~ ~.w~! cu nu ..w. c.». .... on ».n~ a... o.e~ mm ...~ ~.- u..~ ~m ..." ~... c..~ an s.o~ o.o~ o.n~ .. 0.0. ~.o« o.~m a. c.oo ...m 0.0! ~. >.on ..o. a... n. 0.0 —.c n.- .n 0.00 0.0a. n.0— n: 0.0 ..o. ..m— ~n aged 04.4 0.~w gm 9.. o.~. o.o~ .N ...n ~.cn ..mn n~ ~.on p.nn ..on ~« 0900 0.00. 0.0... a... o.s~o o.m~- o.~ c. u.0~! ~.0 0.00 nu. ~..~ o... N. a , . o.—~ _. m_m«m 4.0: 0.00 p... ¢.pn on ...m "..n 0.0. mm 0.0. ....n a... un m.~. ..m. ..o. .m m... a... ..c. o. 0.0» ~.pn a... no awn. 0 .2. a. S no p... ~.»m ~.oo a. m¢~ a... .... 23. p.00 c.0n 0.~¢ an ..pwm0_;04mn upon an o.,. n.~. 0.0. .n ...m ..nn n.~. on o.~m ..cn u... n~ _. do 0.... The as. 7.. p..n~ n.n~g m.~d~ - p.0~! 0.0 ~.c~ on oqn! m..~ a... nu o.oo n.ce - m.~ou a. mu ,uu ‘ 00 za:»ux to «0.4: Adz—:0: 1¢L7 ...:~.mnu 0...! n...3 «.00! 0.00! 0.0~! 0.0! ~.0 ~.0~ 0.00 0.00 0.0m— 0.000 0.000 p.000 0.0- o..~ m.~m! m.mmu ~.mm! a.~m! n..—! o.~ o.oou ~.n~! ~.c.! o.~.u ..cNu ... ..Nou c.ma! ~.~mu ..n~ p... 0...! ..m.n n... ~.oo~ >.n.! p...“ n.-~ ~..~....mao ..son o.\.l.« . I ,JfLWaf. twh‘.‘.! ‘ t a. . .... .5 .9 ....Muf . .00!0.0NL n.~0l.0.~0! 0.00!.0.h0! 04-!\0.0, 00 ‘7 0.00 0.00! 0.00! 0.00! 0.00! 0.0 0.00! 0.00! 0.00! 0.00! «.0! 0.00! “.00! 0.00! 0.00 a.- n..~ a... 0.00! 0.00! «.00 0.00m a . ~0 —0 00 0.00! 0.00N 0.00N . \. 0.09000.000 0.000 n. ~. .. .p 0.00 N.00 «.00 0.00 0.00u ~.00N 0.500 h.~00 0.00N 00 0.00 «.00 0.0» 0.00 0.00 0.00 No00~ P.0uu 0.00M 0.0hu 0.000 «.00N 0.N0h 0.0~0 0.000 0.000 0.000 0.000 an00uobalh. 0.00! . ;.£.,xw.1010§u. 0.00 0.N0 0.00— 0.00 0.0—a 0.00 0.00N 0.00— 0.00 «.00 ..00 0.00 .... c... ..~. ~.m. 0.0» 0.00 0.00 0.0h ~.F_~ ~... o.~o_ o.... n.o.. ..mn— o..._ ~.o._ ~.o.~ n.n._ ..u.~ n.~.. o.~.m o.om~ ....N ..~.~ ....~ m.~.u ..o._ p.».. 0.00~ 0.~0u 0.00— 0.000 ~:n0n an... ~.~n~ ..-~_ ...m n.. o... ~.oo .JQv ...»-.h..- ..o~- .... ".mo. ....” ~.c.~ ...cn ~..~ a... m.~s a... p... .... o.n. ...o~ ..~o~ a... ...c. ..~__ o.oo_ ...n. c.~.. _..m~ ~..~m ...- c.n- “.... ...._ ....“ o.~.n n.~nn ...on ~.o.~ ».o.~ o.~n~ n..~. ...nn ~..m. n.~mn ..o~n ...~« 0.... ..~on «.... ~..n~ ...m~ ....~ ..~.a.o..pn a.-n ....N ....N ....N ~.ocono.on. c.~.n o..o_ s.»o~ m.~n~ n.n~n a... .w ~ ~.... p.no. .m.... a. a ~.~_. aqua; a..- .... p...— o...~ ~.>on r. . hut». ..“a N. we .~ .. ~. r. mopomm 02—2—2 02—024020 Ammhm 0:0 mam zmahmm mo mmhp. p... nu c.n.m s... - ..n~- .. m_m¢m 4.ma ..no. o.oo a... a... 9.“. .n o.~—— a... o.no n.~o. p... no n..~. ..«o. .... 0.0." ~.~c~ u. a.... ..pn_ ~.on_ ...._ m.cn_ .m .._—~ ~.o.— n..n. m.np. ...». .. ~.oo~ >.mo~ p.o.— ~..e~ ..oo. n. «.oun p.~.« n.-~ ~.n.« o.~_~ u. o...~ ~.oo— ~.o- ...o_ ..ap. a. ~...~ ~.~.— a...“ n.n._ a...“ .n n...~ ......n.n.— «..., o.o._ mm a.~nu m... r... ...o—...o. a. n.oo~ ~..u~ «..o‘ ».n«. n.o- .n ..o.~ o.~o. o._. ..n~. ...o. .~ p.-n ....u o.-. ...._ ~.m- nN nmflwagmmaou;as... .....-..... us ~ an o... ...p. c.od. m.~» - ..ca! «...! p... o.o. .— .... c.... a... nu ..oom m.nn~ a. ..o- uu .. m. ~— - co za:»w¢.uo mm... ..z..oz 148 no . -Nu Nu , ¢¢ no No No 3. 3 Na Na. ..N «N .2 --.. ...n ...v. .... a a .2 2 .Ncum.onu N.mn- ¢.Nc- m.nc- N.mmu o.ann o.Nu o.N_- N.N- N.oNu N.o- ..NN- o.v- N.N N.mN N.oN o.NN o.NN N.NN cu N.oNn N.NN- a.Ncn o.Nc- o.onu N.NN- N.o N.NN- o.N- o.m- o.Nu N.Nu o.a- n.» n.Nn N.NN N.oN S.NN o.NN Nu N.mNu o.ce- o.oon N.Noo N.on- N.o N.ou o.N o.N- N.N m.n- N.N N.NN m.oN N.on N.¢n o.NN N.NN Na . N.nou o.cm- o.ooa o.Ncu ¢.uN N.on N.N N50 :0.» o.Nu n.n o.oN N.mo Numn N..n ...» o.oN No o.Nc- N.NN- o.Nn- N.¢N n.NN ¢.NN n.oN n.oN N.o N.NN o..N a. no N.on o.nm n.oc o.on co ...»? :67 N3: N...» RS NSN ...RLQNN a...» ...NNN. vi. 9.? 35 ...... N.J.: no o.NoN N.oNN N.eo. o.NNN N.coN c.¢o N.on o.oo N.oo NNNNN o.NoN c.noN o.No N.uo No N.aoNNo.o¢N N.NoN N.oN N.oN NJNN N.ov N.oo NwoN: N.No o.Na N.No n.0m No iN. can o.oN- o.o_- .o- o.oN- N. N. ¢.oN mum" "mum Mum" o.No N.oN on .... ... . . ....-. . ......NdNN N. ..N. : 3.8. ...“.S «N. N . o. . . . ...... ... .2. N ... a NM: a. «N o.oN .....2: .....N S. N. N $11M”: 9” ......» ......u ..1 . .... sax; W. uh...‘ ..l...$..o . 2m ... . .. .. . I“ “MM” . ~... . . . . a ‘1‘..N§ «flu»... , . ,. Nash- Nana... N. a mi: N: N. No NJ» oN N.NoN o.NwN o.noc m.NNN o.'ua w. NoN o.pN n N.NNN o.ooN o.NoN N.noN N.NoN N.oN Lr1 i... fir . . ......fin. .... ......ng -.A. ......,....€.... ......” $3.33 . in: ......N - N.o¢uN ... n..N- 0N .V v . ’u. .\) v 1‘ . 3“ “fit N8 a... n“. s... . . o.o or NN. NW . .. . . ... N.NNn NN NNNNN Ncma ...-.r. . .. .. . , . .... .. an... :1}... .NeaNénu N6? NAN- c3? N.3- 3%.. a... 9.9. N... mi .13 «av. 39 0.: .6- n a“. 3.3, 3.8. .. N.oNu c. NNu o.N«- N.NNr N.Nc- N.NN- o.oN c.n n.oN N.NN N.oN o.o N.uN n.oN N..N .aum N mm N.Nm ago: M” . N..No o.oun N.unu a.nmn o.oNu e.NN 0.0 u.NN N.NN. N.oN N.NN NNNN N.Nn .no N.nm 0..» coon N.n¢ Na N.nn- o.o¢- N.no- n.NN- N.on n.NN o.oN m.oN N.oN 0.0. ..oN ..on N.¢N N.No N.No o.co N.on N» N.on- N.Non N.oN- a... N.cn o.Na o.oN N.No N. oN e.oo N.cm N.mo o.uN o.no N. «N o.No. no n.n¢u c.NN- N. ooN N. no o.Nc c.Nn N.oo c.o¢ N.No o.oo N.oNN n.no N.wo N.no o.NN no ...: cine on?“ N... ...: - _ .NN 123.83 39...!» N 3. ., N. NNNNo.NNN NoN N.NNN,mnmwN ammmo N. -N o N.coN «.mNN. :ma .oNN o. .2 u -N . . .0300-.. 3,- c.0u ouNN o.mr .noNN o.¢m NbNoN c.NN Noun o.cN N.Nm . . o.NoN o. N» N. No N.NN a. No N.oN o.omN o.nNN N.oNN o.ooN n.oN n 4y .. .1. c h. kt a ‘10 'N‘ F“. g”? .N‘J'gf .-Et N‘ 1‘ 5' H . ..r - c Nmz ..ou o- o .oNN N.N.N a «N o. NNN .. a NN .4. v ._ . N: -HS. n.noa o.on N... a .NaN M.onN counN o.NnN n.N¢ NN . o.ooN N.¢¢N 0. mon o. NNN o.N.N N.noN o.oNN NN 3...... . ... a. - ... «:4... ,w _ . ..i.#ix§u7:nn.l-2:3;Lu... . .19. ..N: .. F900" figfioflgdh. N .3... . 00% o. NNNNN.oon .o. NNN .NN N.oN NN -... N .. c. on- N.oN e.NN m» N b. N163 need . . nN “N.” N N» on any... 8. nflffiSfi. 35mm 35.8.5 92 5:6... mm.— gom i=5 “8 3:». an-.. HES .... 14¥9 ouOIOoONI ooONl no~cl noo~ «.00 count cocnl «arm! 0oh09 oanOoo—O ooo~l nomad nu noom an! moo Oon~l Noun! Outfit 0.000 an 00 »._ca o.cc- _.a~- o.~.u o.o_- o.~- c.-u p..- n.o~o o.o~u o.o~c o.o~- o.n~o ~.-- o.a_- ".~.. on p.nnu o.onu ».o.- o.~- p.ou ».~ o.nn c..- o.n~u a.o~- o.o.u ».u~- ~.~.n m.m_- «.o~- o.n‘- mm o.oc- m.om- o.««- p.ca a..- c.m o.o- c..- c.o~u o. n~- n.-u c.c~- o.n—- ~.r~- e.o_- F.m.- «a o.nmu c.nno o._~- n.oa ~.. .u.~. ~.nn v.0. u.o~v- .mwn o.o~u n.-u c.~.- n.¢.- a.»_- ~.c.- .u ¢.on- n.~¢- u.m o. ~m n. p~ o..n n.n~ o.c~ s.-- .ouu m.ou ¢.cc o.n- n.ou ~.~_u n.au co «.on- o.oe o... n.mn ..mo p.n~ o.n~ .maeu- ..nq..¢.on «.a; ..u- n.uu a... o.o- no ~.o~n o.nm~ n.o- n.n~. o.no c.co p.n.- o.n- ..n ~.p ~.m 0.0 c.n- o._- nc o.on_ o.~o o.oo «.ou o.c~ «.mnu _.c~¢ ~.¢_a «..- n.0t ...»- ~.a~. n.-- .o o'er Cool coon hooci m oml o awn ¢.0us n-o—I coowl pocwl Goons On ...... 331...: .14. 0‘ Mafia g; 1.. .«4 5...? ~.~qu am can“ .mon . an- F. - n. co- o.ncu .cmuo ouamw.mumwn o.nn- m.o~- N» ...... ,3xég --.: hint... 2 h. .. 1...}... 134.169.. -58. 5.. #195 ..u at: 7%": 3%.“? ..ocu :3- 7.3. an»: inn n37 o~ ...-..13. 9.: 1: ......3 ..on 3: R a.o- o..~ c... ...” o.nu a.n Nu m .. - ... . . ,4 . . rifleafiu nit 941.33.. «a. . n.._n~ ~.o~u ~.onu n.-- ed , - .o - 01am. m.not n.o~- .— a.~m- 0.0»- ~— o.~o a. m_m¢o a‘wa 91nun. .mmu,r.~nn o.0; coo o.e. m.o can c.o.c_n.ua1 ~.no o.u¢ "not nag, «..- n.»w co ~.m~u .on- ..uc «.0. q«p. ..o~ ~.¢_ «.p— o.... c.». o.~ n.n n.m . ~.o u.» an 735.13. ...—....uén .12 a... 7.: ...: 18.. ...-v ..7 >3 ..u 1.!. «.f a: no m.o¢. p.so- “.om. ..o~ ~.o~ .¢n p. nu c.c_ c.m~- .:- o.o o.o o.¢ c.~ o.o- n.~ .n n.~nu n.0au .a o.oo «4.. ..n-;. .mn a.rn o.»~. c pun. o.n— u.n~ fine ... ... co n.ar- «Hun upmw~ ”.9. .or .m.um ...n m... “an cmm— n.0w .o.na ~.n— v.0 n.~_ n: s.: o c. .. own _ » ~ ~. ... yoga .oo». a... N. + .w~ cauW.“ .m a H.pc m¢uc o.o~om nrlfl . .o ecu“ c.rw. ..n:. ~. m.m.. no .... .- ....r..........»....... mu. o.§u.2. a... “and. £91 chm: 33"}... M4139. a... .03- cu. . o.nod o.n . a on- c. ~.n- «.r—. o. o- . n.u- o.u- a. «u- 0.0- an .. {F o .. v -... 9 alhu O . N .n I F #5! 0mm...” N“ _. ...; ...... ......fmmrm. -Kmm." x #53”. 0..-..- _. .4.. x.. ~.oo». qoap- 0.09: o.‘~- c.-n s.o.- o..~s o.n_u c~ a.n- m.c¢_ o.c.~ c.0p o.mo c.o~ o.om n~ . ,1 J l. a. .. “mi, 0.44.1.3 v.3 Snai13 no: «a . n.oo o..~n ~.o o.nu «.0 an ...... o... ..«7 13. n3. 3 . .. o.-u ~.~nu o.». «a . - - ..n- . o..n- com a. . o.np _. _n¢..._......u¢,-. ..3. on. 3....-.6! mm}... c~ S 2 2. Z .3 . 1.3 S .13 235 ...... as... 3:5... mohumm mh¢Hho=OP=< az< u>_ho:c»=< m=h mom zxzhum mo muh<= mm-= m4mn ~.on ~.nq o.~v o.oo o.om .mo m.on p. "h m. on human Foam“ .oonH~-Hdood 0o- now run 0.0 :600 .udn 0.0 an- ~m mm-a m4m.m :.¢ um m.m g.e —m 499‘ QQQ. {(9 .- moo~ has. no aonw a.fi~ Ne Hiddnimoflduiddiill- ooo~u aoodu On mob—I n.~ul nn Aoadu,m0Qéfilnniilll nohuu mos—u an comaneoonarLaonauzahcgciquaun¢on+unnuus-u; o:u0 hooalm N~ s.c—u o.m_u ~.m~u «.~_- x.o~u —~ . :: a;«wm41: Juan ~o¢q¢;¢o-s c_-,;.. , _ ma- c.auc 91””: nd ‘ II' [...-2|, It \IIOI. . l . \ a 1‘] c o.-- ~.u.u uu ; ~¢mar.- ! m_wqa 44mm momN moAN I!» .nl mom~ aoo~ an rota .orn Nm hock aovk an Ounh 00°» '0 tone won: a. qqmq..~om4 «o a. -u «.mA. 0. pd- ¢.-- o.o~r o.o~- m.o~- n. «a- -.ouu m.~_- ¢.o~- m.o~- ¢.¢~u c.p_u ~. p“- cu , m.-r 0.0.- nanac.n.a~n +bu~uo «.an- o.nn «own. ~oo~ o.- o.n~- woqu c.on n.rc ~.~o o.~m ¢.cm o.~n N.om m.u¢ ..ce u.on n.om ..m» ~.c. e.o« m.~m 0.. ".uc .aanw o.«m o.~n. m«u~ ...wep a «can. u.~¢, .¢~¢ o.om ~.nn a}: coat 7!. n23 T1”. P...“ at? m§fid.~3mtn¢mn -4143- ¢.~ .. 0 ~. m m.¢ o.: o.m m.m 0.0 0.0 o.q (.3 son 9.0 9.0 .3: -Eo 3.11.” 6.3.14.3 ..dou, 9.9 o.c o.o o.o 0.0 0.0 . 9.0 o.o 0.0 o.o .o.o o.o o.o aowa .- - a¢a:. o.o u.a 2.0 0.3 o.o c.g o.o 9.0 0.0 .t- . - .awq- .uwa.--a.a one coo coo .:.. a.o\.- a . «4.:xu ..n .d ¢~ mm - - «a n. ~_ dd co zunhma $0 mwpdx 4~ o...~ - ~.m~o_..~.m N...” ..o~« o... .m .... s... p.50. m.>~ .fl ~.>~ o..m~ p... n. 0.... .... ~. w.csl ~— .. n. ~. _. .n an «n .m .N r~ - .N .— n— ~_ —. oo agapwa go «a... .«:.:oz achumw wmm<¢m>mm =z< ouu ~.no n. c.~fib¢h.~o~ o...~ .nocw 9.9. ..pou a... a... ..eu. ..o- ~.oo_ ~.~—~ ..oo. ..~o ~. p.... ~.«__ ....— m..n p... p... .... a... .... ...» .... a... .... .. .. . ..on- «.0» n.-- ... c.. ..o_. .... a... u.~m 0.». a... ..uo on o.o.~ m.~—- n... ~.- ..o~ n... a.~¢ 0.0. a... ..o. a... an o.ox- n.u-sn.m- ~.b. .9. «um. n.no —.nn. u.on n... um ~.n.. .... a... ~.o u ...._ ..n.— ..~n~ ..uou ...» um 4‘ . 9 60¢ noon doing «tutu c.¢¢«.nohN~ coco donfi ON Noro mono" Moe—N Noanu nomo~ comma won» nN .Al.. . . - ncdin tomnn Coafiu Conan Oadflu hokh NN ...¢~ m.—c~ ..o.. ..mo n... .~ . . . a... o.~o~ ~.n. o.n. .. ...». r.os ~..— .— o.o- o.nn- ~— ~.mo- nu an 2 S v. ... u. 3,. n3....fl ...»... an... L3 .3 - .3 3 2 u. 3 8 . .r . ...... . .. rd. .358 g. Act-tn! mxobmm 52.8 ._._< «9... 5:5». “5 “amps. «ML. 5mg. 153 57 alternatives out of 200, or 29 percent; and the poor sectors, 121 alternatives out of 200, or 60 percent. Rates of Return for the Strategy of No Reinvestment We already have indicated the reasons for studying the no reinvestment strategy. The section entitled "Market Indexes without Reinvestmenfl'presented the index obtained by this strategy, and those results now will be translated into rates of return. The no reinvestment strategy provided in the five-year period, as can be seen in Table 4-41, a rate of return of 62.5 percent in nominal terms and 36.4 percent in real terms. TABLE 4-39 SUMMARY OF THE RATES OF RETURN WITHOUT REINVESTMENT BY YEAR Real Rates Nominal Rates of Return of Return; Annual Cumulative Annual Cumulative 1968 7.0 7.0 29.5 29.5 1969 168.3 69.5 222.6 104.4 1970 20.4 51.2 43.6 81.7 1971 90.9 61.2 93.5 133.5 1972 - 24.2 36.4 - 12.9 62.5 Table 4-39 summarizes the results by year and indicates that 1969 provided the highest rate of return. In short-run investment timing strategies, the fluctuations were wider than in the long run. The best investment timing strategy was to invest from June to September 1969, and the worst period was June to September 1971. 154 In real terms there were 33 cases of negative rates of return out of 200 alternatives, or 17 percent. In terms of a hedge against inflation, this strategy with this index was no worse than the one with reinvestment. Rates of Return for the BOVESPA We translated the BOVESPA index into rates of return, and our conclusions upon examining the rates of return are the same as those presented in the section entitled "Comparison of the Market Index IS with the BOVESPA Index," when we were comparing the BOVESPA index with the total market index IS. The rates of return provided by the BOVESPA shown in Table 4-42 are very close to the ones reported for the total market. The number of negative real rates of return were 33 out of 200, or 17 percent. ‘Rgtes of Return for Reinvestment in the Market Portfolig_ As was also shown in the section entitled " Market Indexes with Reinvestment," the strategy of reinvestment in the market portfolio did not provide results different from those of the strategy of re- investing the proceeds in the same security. Table 4-43 shows the rates of return for this strategy. The differences with the alterna- tive strategy are of no significance. ‘Rgtes of Return with Reigyestment of Proceeds but with the Same Weight for all Securities We are now in a position to analyze and compare in terms of rates of return the impact of both weighting systems. These rates of return are shown in Table 4-44. For the entire period the nominal rate of return was 76.9 percent, and in real terms 48.5 percent, both 155 of which are superior to the alternative strategy. TABLE 4-40 SUMMARY OF THE RATES OF RETURN WITH REINVESTMENT BUT WITH EQUAL WEIGHT FOR ALL SECURITIES Real ROR Nominal ROR For Until the For Until the Year Year Year Year 1968 20.3 20.3 _45.5 45.5 1969 163.6 78.1 217.0 114.8 1970 34.9 62.3 60.8 95.0 1971 146.8 80.3 195.5 116.4 1972 - 31.5 48.5 - 20.9 76.9 Note also under this strategy the wide discrepancies of return among the five years, and note that 1969 was a better year than 1971. The potential gains and losses were very substantial. The highest possible return in real terms was in the first quarter of 1971, and the worst in the second quarter of the same year. Under this policy, there were only 24 cases of negative real rates of return out of 200. When compared with the strategy of weighting according to the market value, note how important was the role played by small companies and the potential for gains that they showed. Risk and Return Analysis We have discussed the ways in which the different indexes were constructed as well as their performance pattern. From these in- dexes, which include everything from individual securities to the 1556 .o~-m.sm- w.mwu o.om- ~.q~- n..m- c..- m.c_ ~.- ..mw ~.p~ o... a... 0.3m ~.o¢ a... o... ¢.~. ..a. ...m «m ...m- ....u o..mu ...N- ..pn- N..- ...NN ..QN ..mm «.51 «.1. m.oa ...» ~.~m m..n a... a... 2.m: a... ma ...w- ...n- a.o~u ~.a¢u c..- m.~m N... ~.m. ~.m~ p.a~ ~.a~ ~.m. m.o. c... a... m... a... x... ~m a..- o..- ~.~mn «... w.~o o.mo .... o.c. o... m..n ..co m.o~ 3... ..~. ..c. ...o a... _m o.n o.~cn s..~ o.mo. o.oo ~.no 3.0“ .mm «.0. ..oo o.~o ~.em ~.~m m.n~ 0.3» ~.~o co ..pou ~.~. m.oe_ ~.-1 p.n- m.om o... m.o. a... ..m:. o.co o.om c.0m ~.~. o.mo no ..o~m o.owm ..-m ».~m~ m.o~_ ¢._a~ a... m.~.p 3.... o.~«~ one.” r. o. ...o— a... N. - -. - ~.now-o.o«~-a.~o. n.ac o.op .dapt ~..o .~.-4 maod~ ~q~¢~ uo.m 8.3. do ~.m~ o.om w.n ..oN n.m m.¢m a... m.o~ e... o.mo ~.mc a... «n ~.mo_ o.»~n m.o ~.n- c.om ~.~o e... ..m. ...o o._o ~.o¢ «« ..- I- 1.3- -.. Tli.-i- --id.~du..nad~- ~4~H1mfi5~3 :33 HWJAE .3. «J... 31..--.. .... ~.~_ o..~a n.3c. 3.5.3 ~.m- ..coa a... a... an m.o~- ~.mm~ o.n¢~ m.mo~ c.cm~ w.oo~ o.no m.o. ¢~ - - -. ,u.omp H.¢mo o.nan-n.mHN1u4~na oamwdnpoam ,n~:- o..mm ...». m.c- m..m ...» N... - n.- m.mm o.- m..~ m.:_ - . -«om. «baa. ~.m~ o.~ . cps. , o.o- a... a..- n3 ~.on c..- «a - - r x - - - ..... 2 - .p-- - .. 2i--. ooqnt #3.! meme. name .an n.¢u ~..~u ~.o.u w.-u ~.¢~u a.“ e.~n o.m¢ m.~m ~.qm «.cn ~.¢m smuon o.n~ .o.- u.--ld.qa m.ma u-ua .cm a: m..~u _.mnu m.-- o.._- ~.p~u ~.o a.m. ~._m m.oo m.om a... ...m ¢.~o ..ao .... p... n... .... .... «m ..mmu m..~- o.¢~- m.opu o..~ a... a... o.- ..o. A.Nm _... m._h o.~o a... ~..x o.~o a.~m a... ~m m.o~ o.n~ a._~a w.vn a..o— n.oo_ c.co~ o.oo ~.n~ o.~o m.~o .~.m«a.~.oo~ m.aaa.u1-I-.¢.Hm NAM: -anlt- m.- c.nnc 0.3m m.nn~ o.m~a ~.~n. 3.0» ".mm o.»o c.no~ ~.o~—.~.-. ~.c- c.~ofi o.mo~ n.mo cc ~.~o1 ~.~p o.no~ m.mo~ o..o~ u.~o ~.mo «.mp «paw» can: .n.om. o.o- snob. o.v.~ o.co~ no .1 -4.mso «.w—~.o¢qo..n.and-o.ma~ m.on~ o.maa u.moa 0.3 a¢4m~;wom44:H.QWA.m.«q4:nom- ~4... _..o~ a..am ..mnm w.mo~ o.m01 0.». ..ans 0.... ..1m_ m...1 m.cm~ _.n- 1.... a. ...o m..- ..m~ o.m. a... ..mc ...Na ..._u 0.0.” o.po «.co p.1m on - ,.. - - 2--..-.2 793. “5.3.1.3.- 0.3.- a; «43.413833...an - «...- 0.»- «...- a... o.-~ ~.H~d ~.me~ m.~¢ ~.oo .... ~n :. m..a_ o.mn o...“ ~.nm~ m..a~ ~.o.~ m. ~.c.wm~ «.mo~ an .e.... -1. e : -.ndodn.mqmam o.~«n:ag- alwqqdaldwx.i o.~.o~o.omo o.moc o.¢m~ ..neu o.as_ ~.~m~ n~ ~.m.c ....N ....H ...,a c.o.a a... - ..o. a.om o.n¢ ;¢.om. ..mm q~=_ m.oo m._e m.mm m.o~ c. ~.sa a... m.._ mu ".3: ...4; ~— p..~u 3. mm Nm 3. c. m. _. «m mm m. _. c. m~ NN .N .2 M" Na "3 as ngw« no mmhca 4<2~xoz Haua m4m

z_m¢ oz .hmx¢<: 4om amp mom zzzhmz mo mm~<¢ N:-= m4m

~u ”.mm 0.00 ~.mm coca hooo ~00- m.-~ x.mm~ nocw cool Num~l 0.00: 0.00 u.m~ «.00 0.x”: m.m~ 0.0m 0.00 «out o.u¢ h.o¢ u.b t.¢m 0.03 0.00 _.ma0 0.00 0.000 ~.o~0 0.000 0.00 ~.0c0 moosd ~.~00 0.000 0.000 ~.~0000.~rrm iqwooa¢¢oerHq~mN 0.-0 0.000 ¢.mm~ o.~o «.mn v.00 0.~m ~.n 0.m¢ Foam 0.~0 m.¢ 0.0c o.c0 0.00 0.o0 o.~n0 n.0n0 0.000 0.00 0.000 90000 ~.00— ~00¢ h.~o~ noon~ novww 0.0000000000c.0n0 0.000 c.00~00.000 0.00m Ooocu @.cc0 . 0.0- 0th, -m w 00 «M um um «m 0.00 0.00 0.0~ .00 0.00 0.00 0.00 0.00 ~.00 00 0.00 0.0m 0.00 0.00 0.00 0.00 0.00 ..00 0.00 00 0.00 0.0. 0.00 0.00 0.00 0.00 0.00 0.00 1.00 00 0.00 0.00 0.00 0.0: 0.00 0.;0 ..00 0.00 0.0: 00 0.00 0.00 0.00 0.00 0.000 0.00 .0400 0.00 0.00 00 0.00 0.00 0.00 0.000 0.~00 0.00 0.00 0.00 0.00 00 0.000 0.000 0.000 0.0wvuoan0ayciama,00. 0 0.000 0.00 ~0 0:00-.q¢n0..da009;oq0 0.0~0 0.000 0 m. 0.00-00.00‘ 00 0.0~ 0.00 ~.00 0.00 0.00 0.00 0.00 0.00 0.00 00 0.0 0.0- 0.00 0.00 0.00 0.00 0.00 0.00 0.00 00 0.00- 0.00- 0.00 0.00 0.00. 0.00 0.00 0.00 0.00 ~0 0.000 0.o~ 0.00 0.000 c.0mm ~.000 0.00 0.00 0.00 00 0.004 0.00 «.000 mnummlm.000 000 0.00 0.00 00 ....... - . .a.0.040-q4~00:«10 .000- -04000g0.00 n~ . 0.000 0.000 0.000 0.00 0.00 0.00 - 0.000 0.00 0.00 0.00 0.00 00 00.0- 0.0V 00.0 0.0- .00 0.0- 0.00 0.0- 00 0.00 0.0- «0 . . _ 0.00- 00 0.000 0000 0.00 0.00 0.00 0.00 0.00 0.00 ;0400..0¢00: 0.00-.00;.n1.. 0..0 0.~0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 00 0.00 0.00 ~.00 0.00 0.00 0.00 0.00 0.00 0.00 «0 ~qn0 0.00 0100 n.0~0 0.0~0 0.000 04000 0.000.0000. 40- 0:: 0.000 0.00 0.000 0.000 0.000 0.000 00000 0.~00 ~.00 00 0.-0 0.00 0.m~0 0n 0 0.000 0.000 00000 0.0~0 0.000 00 0.00~ 0.000 o0qm0 0. - 0.00~ 0.000.0.~0«.0.000 mqana.~4 - 0.000 0.00 0.000 0.000 0.000 0.000 0.000 0.000 0.000 .0 0.00 0.00 0.00 0.000 0.0~0 0.000 0.00 0.00 0.00 00 0.00.0n10«.r0000.;0.~00;0.0~0-mamo0 0.00 0400 10.00 .MM. .4; 0.00» ~.0uu ~.00 0.00 0.000 0.00 0.00 0.00 0.00 «a 0.000 0000; 0.000 0.000 0.00Naa.~00.00d00.nc0~0 ono._4ni 0- 0.000.. 0.000 ~.~0~. 010010: 0.310.301 .0330. 30.- 0 .--: momom mouse Oohuo focmN conho 0.00» vooo~ .E mdflmn ~1dN ~00— 0~ MN N~ am ¢~ m— Ooema u.~o~ nowuu mm oowwu 0000— m.0m «w .udmm .Nomm ~om¢ «N {emu m.om 00~a cu does come wand nu Jom~. {QMA Nu 0.00: 00 ~0 00 no -i. I‘.l. if! ...ld‘ll: .l.: .1 200000 00 00000 0010022 o00omh¢om00mx¢<= mzh 20 mammuoxm =mz~m¢ 00mx¢ pomcl Doers #:ort norm hoccp coco not QoNNI oohdu mcwo~ Oocmu Nom¢l ~amo~ Now—m m.-~ o.nmo~g.~no~o.o>c 0.0m: comma co~m rw «w ~m «c no N: u! on «r Oo1r (end weer comp powmy mower «crow (coc— «.~u ho—cp o.mo ~.¢~ o.mm OoC—p cocc~ m.c_m hocam p.mmm 0.0“" ~.~on «K m.~m c.>w ¢on¢ o.mm 0.00 o.r~— m.om— m.mo —.rr o.¢n g.w~n ooer New: «.00 '.?¢ c.>~— ".hw— coom~ o.cm~ {.00 m.¢c a.~—u pr (.wr mos» c._c momw fiowa o.co o.¢m. «ouw Oo¢n mocn «co c.0r noon —.ro ooco oomc o.a- ~.c¢~ domo~ doc—— «occ s.mo ro0~ ..No 0o¢m eo—m coca b «c C #1 cock soc—v (our roam noo— cool u.-| coo: ~.om n.oo ~.e> ~.¢o Q.¢- b.~o~ «.oo ~.m¢ m.mq n.“— ~.m~ m.mo «o noir h._c a.m¢ «ohm «oar aowa c.0n~ c.a~ £o¢¢ hobo m.or o.pm q.om ¢oo¢~ o.~o noon aces howm o.m- o.mn~ ~oo- "om—— ~.r» u.¢« cokv. m.~o cope" m.h¢« No mmmhmm=umm 44< mom h:c_mx m=z~mm ~pmxm- 0.00N “Ono“ comm how o.mn v.0m o.mm n.~n .n._o_ hoec Mowm somm ooNc~ come (.00 ~oo- ¢o0- uomC— Ooh¢n mownu 000N~ noocm coo¢~ ¢9m¢~ Oo—~N seemu comhr mohm~ m.or~ Newm— momor cowwp covey «ocm— Nooww —om- .OOONu coo—u henc— Nokhu c.m¢~ Nomra OofiaN CoMOfi moo¢u bopkm OoFmN toFOp nomwn hoflON noQOn ~o¢¢¢ cou¢~ m.¢- hatN p00¢ Womb 0s Mu Nu Zxahwa uc ForU ¢o¢¢ ¢m «.wr ~.~m «u ¢.cm meow um poor o.rc pr ¢.¢m «.0c «e n.¢o oosm no ~.c#_ ¢.~;~ me c.mm m.or ~c p.>c mono tr mock acme an ooeo m.rr ~m coca o.~h an a.cm ~.m~ «N 5.0—" oomo n~ coco coca - cone oo~m - o.c~ a.o~ c~ «.0o o.mn my ¢.- ow¢~ ~— o.¢~ ~— mumqa aqua moo» .oocb cm 00mm womc Fm wouo coho Nm comcw 0.00 mm 0o-~ {comm ct moem~ moomu me nooom boom" No ..¢- moo—n ue ...op coro en 5000— moco mm n¢p0 Dunc «a comdu Nomc~ ~m eomwu o.¢- cm scrtu moocu mm Nofinu uohuu mm 0.00 worm - m.ho wove cu r.co ~.mm Md rote cow: - 6009 ya u. co vmhdc aum a ooumnoa NH sa.o mm.~ m.mm o.~o aofium0fiasaaouaama a uaoaafisum Hausuuumam 0H em.o mm.o H.5H- m.Hu muumm .aou=< ecu o>fluoaou=< ma en.o km.o N.MH m.em wcfinuoao a uaauxms «a oo.o mm.o «.mm A.Nm mafia“: mafieafloafl Hmoum no as.o 35.0 «.ma S.Nm moaufiaaus change NH sk.c am.o «.mm S.Nm mafiwuom mascaaoafl oswuafimumz Ha mc.o NN.H m.~m S.Nm mHmoHamaoouumm a mHmuaemno .Hfio OH m~.o mo.H o.mq H.kn namaafisam g>mmm a kumaaeumz so mm.o ma.o H.o- o.ma assuage a “meme .noos mo mm.o mn.o m.mq H.m~ “mafiHHuumm Bo o~.o mm.o m.mH m.em mafiafimumm weansfloafi manna co as.o 30.0 m.m~ m.ms coauuauumaou a unmamo no ss.o no.0 S.NH m.mm mafiummflm can “spasm so mm.o Ha.o m.mH A.Ns soon mo sq.o No.H ~.sm o.mm mcosuausumnH Hmsoamaam a means Ho moaomm wm mMMDm