Knowledge that Transforms

In his recent paper in this Journal, Miller [3] proposed, following Adler's results [1], that “the investor exhibits decreasing absolute risk aversion with respect to expected wealth if, as increased holding σ constant, the slope of the indifference loci decreases” [3, p. 301]. He further attempted to have shown that in general the sign of () is the same as the sign of r'(W) (the derivative of the absolute risk aversion measure), but this is not proved.

Professor Schwartz's [6] attempt to provide an economic model of trade credit is to be applauded. I am in complete accord with his statement [6, p. 656] that “the aggregate importance of trade credit and the economic effects generated by changes in trade credit flows suggest that greater attention should be given to this source of funds.” For too long, thorough qualitative and quantitative analyses applied to the phenomenon of trade credit have been somewhat neglected. In his attempt to remedy this situation, Schwartz is to be complimented.

Stable distributions are becoming increasingly popular as appropriate models for stock price changes and other economic phenomena. As a result, there is an expanding body of literature on inferential procedures for this family of distributions. Computationally simple estimators for the parameters of symmetric stable distributions have been provided by Fama and Roll. Little attention, though, has been given to goodness-of-fit tests for members of this family other than the normal.It is the purpose of this paper to discuss simple goodness-of-fit hypothesis tests using kurtosis, b2, to distinguish among members of the stable family. The b2 tests of hypothesis comprise: 1) a null normal versus a nonnormal symmetric stable alternative; 2) a null nonnormal symmetric stable versus a normal alternative; and 3) a null nonnormal stable versus another nonnormal stable alternative. Tables that give the percentage points of b2 and that are necessary for these tests of hypothesis are given. Apart from providing critical values for the tests, the tables allow the researcher to calculate the power. It will be seen that the b2 test exhibits excellent power.It is then hoped that computational convenience will make b2 an important tool for researchers and practitioners in finance. It is also hoped that the procedures we provide will aid these researchers and practitioners in the construction of appropriate financial models.

H. Russell Fogler, William A. Groves, James G. Richardson, Bond Portfolio Strategies, Returns, and Skewness: A Note, The Journal of Financial and Quantitative Analysis, Vol. 12, No. 1 (Mar., 1977), pp. 127-140

A set of theorems was derived based on the following set of axioms: (1) financial management seeks to maximize the wealth of existing shareholders; (2) all projects being considered at period 0 are of one period duration and possess the attribute that their adoption or rejection by the firm will not affect the business risk of the firm's asset portfolio; and (3) the ratio of debt to total book capital is given as α, and r and k reflect the firm's business and financial risk however perceived by investors.It was shown that the NPV of any project satisfying the above conditions could be evaluated for accept-reject purposes with a CC involving book weights. This CC yielded an NPV numerically equal to the NPV using market value weights under special circumstances, namely, when k = r (1 − λ) or when M0/V0 = 1 − α, a special case of which is M0 = (1 −α)c0, i.e., if the firm were at its investment margin. After determining the book value CC, which is denoted as β, it was shown that it can be applied repeatedly for testing period 0 projects satisfying our axioms, even if these projects are unknown to management at the outset of the period. A market value CC, denoted as γ, was derived which gives identical accept-reject signals as the procedure.

Allen J. Michel, Municipal Bond Ratings: A Discriminant Analysis Approach, The Journal of Financial and Quantitative Analysis, Vol. 12, No. 4, Proceedings of the 1977 Western Finance Association Meeting (Nov., 1977), pp. 587-598

The problem of bond portfolio selection may be viewed as consisting of two parts. The first is concerned with the maturity profile of the total cash flows (the after-tax coupons and principal repayments) which the investor requires; in general there will be many portfolios of bonds which provide the desired cash flow profile. Accordingly, the second problem is the choice of a particular portfolio of bonds which provides these cash flows in some optimal fashion. If bonds are default free, future taxes are known, and differences in marketability and callability among issues can be ignored, then price is the only relevant criterion in choosing among alternative portfolios. This paper describes a simple linear programming model for this last problem of selecting the portfolio which provides a given pattern of cash flows at minimum cost. This provides a method for improving any initial portfolio, where such improvement is possible, by increasing its yield without reducing any future after-tax cash flows.

Since its inception the single-index market model has been the subject of a large body of theoretical and empirical research. This study deals with the very difficult issue surrounding the practical implementation of the model in portfolio analysis where significant, nonmarket sources of covariation in security returns are believed to be present.

In this paper we have extended the Bierman-Hass model to include the effect of a second parameter, the terms of settlement in the event of default. The addition of this second factor was found to not alter the independence between a bond's risk differential and its maturity. Our analysis of the required risk differential for various borrower credit characteristics demonstrates the tradeoff between p and γ. Throughout, we have assumed the loan size does not affect p or γ.

Steven F. Maier, David W. Peterson, James H. Vander Weide, A Monte Carlo Investigation of Characteristics of Optimal Geometric Mean Portfolios, The Journal of Financial and Quantitative Analysis, Vol. 12, No. 2 (Jun., 1977), pp. 215-233