Knowledge that Transforms

A perfect capital market is a key assumption in recent theories of security pricing. It is assumed that the costs of transactions, information-gathering, and portfolio management are all zero, and that no investor is so large as to exert an appreciable effect on either the risk-free interest rate or the yield on risky securities. If, in this perfect capital market, investors have identical decision horizons and homogeneous expectations, then there is a unique optimal portfolio of risky securities. Since this unique portfolio must include every security in proportion to its relative valuation in the capital market, it is referred to as the “market” portfolio. When the capital market reaches equilibrium, the expected return of every security will be a linear function of the expected return of the market portfolio. From this relationship Lintner and Mossin have separately derived valuation formulas that express the market price of a security as a function of the security[s end-of-period expected value, its risk as measured by the variance and covariances of this end-of-period value, the market price of risk within the portfolio, and the risk-free rate of interest.

The advent of the computer has permitted financial theorists to collect and analyze large amounts of financial data. In the field of investments some of the most important work has focused on historical rates of return in investments in common stocks. The classical study in this area is the Fisher-Lorie study [8, 9] in which intern al rates of return were calculated for every security listed on the New York Stock Exchange from 1926–1965. Other studies related to the area have been complicated by Herzog [10], Fisher [6, 7], Latané and Young [11], Soldofsky and Biderman [12], and Evans [3, 4].

Some recent empirical studies have concluded that the common stock investor can virtually eliminate diversifiable risk with a portfolio that contains a “small” number of separate common stock issues [5, 6, 10, 11, 13]. The conclusion has several important implications. One of the inherent limitations of a portfolio manager is his inability to evaluate an infinite number of securities. The seriousness of this problem is directly related to the risks associated with a “small” portfolio. The economic function of a mutual fund industry is to provide diversification and professional management. If it is assured that a “small” portfolio can virtually eliminate diversifiable risk, the necessity of these functions may be questioned. In addition, the strategy of concentration may be less “risky” than is commonly supposed. Finally, the modern portfolio models generally assume that portfolio additions are costless.

The results of this study indicate that the individual common stocks in the Dow-Jones. Industrial Average were not consistent inflation hedges. Assuming an 8.2 percent normal required rate of return, none of the common stocks was a complete inflation hedge during all three recent inflationary periods tested. Even assuming a zero normal required rate of return á la traditional investment theory, only six (20 percent) of the thirty common stocks sampled were inflation hedges during all three inflationary periods.

We have discussed some of the effects of rate regulation in the property and casualty insurance industry. One consequence of the regulatory environment is that an optimal capital structure may clearly exist in this industry. If the rate of return to the insureds is generally deficient, we would expect that property and casualty stock companies would have an incentive to lever themselves to the maximum extent permissible by selling insurance. The classic monopoly of the economic literature finances its lucrative investment opportunities in a competitive capital market. The stock insurance company invests in that market, but the relative distribution of the return earned there may be less than equitable due to the process and standards of rate regulation.

This paper has discussed the importance of stationary data in statistical applications and has at the same time suggested one method for testing for stationarity. An application of the testing procedure is made to common stock prices. The results indicate that these data could be nonstationary in the usual sense of stability of the mean and mean-square values despite efforts to transform the data into a stationary form using first differences.

Efficiency analysis is concerned with isolating the efficient subset of investments (portfolios) for all investors belonging to a specified group. In order to construct a meaningful efficiency criterion, i.e., one which holds for more than one investor, care must be exercised to ensure that the investors' efficient set is independent of their wealth.

This paper presents the results of a study which sought to determine whether the status of large member banks as owner-controlled or management-controlled has borne a significant relation to bank profit rates during recent years. The impetus for the study was provided by the view, encountered frequently in the literature, that management-controlled firms may place less emphasis on profit rate than owner-controlled firms, sacrificing it for performance goals regarded as more consistent with management interest. W. Baumo.1 [1, p. 4 and pp. 101–104], for example, has argued that management-controlled firms may sacrifice profit rate in order to achieve higher growth rate and reduced risk acceptance. R. Monsen and A. Downs [11] suggest that such firms may sacrifice both profit rate and growth rate for reduced risk acceptance. K. Cohen and S. Reid, in their study of bank merger activity during 1952–1961 [5], argue that bank managers, as compared to bank owners, place more emphasis on growth rate and less emphasis on profit-associated variables. Other possibilities present themselves. Management-controlled firms may sacrifice profit rate directly for management salaries, bonuses, and fringe benefits, including benefits associated with management prestige. The management-controlled firms may simply pursue efficiency less vigorously.

It is well known that present institutional arrangements do not permit investors to use the proceeds of short sales to finance the purchase of other stocks. On the contrary, investors must place the proceeds of short sales in escrow, and they must also affirmatively invest (deposit) an additional amount equal to margin requirements (which may be as much as 100 percent) of the “proceeds” of the short sales. These escrowing and depositing requirements together will be referred to as “short-sales escrowing requirements.” These escrowing requirements not only involve forced or “by-product” holdings of the (nominally) riskless asset, they also change the structure of the investor's wealth constraint by requiring the substitution of absolute values for the natural number of shares when short sales are made.

When measures such as the average or the midrange are used to report a typical value for the price series in each interval, the stochastic character of the underlying price process is subtly transformed. Fortunately, the spurious serial dependence introduced by averaging measures is sufficiently well understood to allow direct tests of many hypotheses to be made from averaged data. Moreover, a simple autoregressive transformation of the averaged data can be used to unscramble the effects of averaging on the lower-frequency components of the spectrum of the underlying process. These statistical devices are presented and are then illustrated by applications to the Cowles Commission Common- Stock Indexes, a massive collection of New York Stock Exchange price indexes tabulated in the form of monthly midranges.