Recent papers by Lamoureux and Poon (1987) and Brennan and Copeland (1988) document a significant permanent increase in average beta subsequent to stock split ex-dates. This paper demonstrates that the shift in estimated beta following ex-dates decays as the measurement interval is lengthened. There is no statistically significant difference between pre- and post-split betas using the Scholes-Williams (1977) estimator and weekly return data, or using monthly returns. We conclude that Lamoureux and Poon's and Brennan and Copeland's results can be attributed to a bias created by using too short a return measurement interval to estimate beta.

This paper considers the capital structure and debt maturity choice for a value-maximizing corporation. In the model, interest expense is tax deductible, bankruptcy is costly, and debt is fairly priced at issue. In contrast to the results of Kane, Marcus, and McDonald (1985), optimal debt maturity does not always approach zero in the absence of transaction costs, and is increasing in the volatility of the assets of the firm. The model predicts a positive association between the value of leverage and total risk in some circumstances.

Don B. Panton, The Relevance of the Distributional Form of Common Stock Returns to the Construction of Optimal Portfolios: Comment, The Journal of Financial and Quantitative Analysis, Vol. 24, No. 1 (Mar., 1989), pp. 129-130

The mean-variance model is precisely consistent with the expected utility hypothesis only in the special cases of normally distributed security returns or quadratic utility functions. There is little evidence, however, that security returns follow normal distributions (see [13] for references) and quadratic preferences can be shown to generate implausible results, exhibiting increasing absolute risk aversion in the Pratt [ll]–Arrow [1, 2] sense and displaying negative marginal utility after some finite wealth level. In addition, Hakansson [4] has shown that single–period, mean-variance-efficient portfolios can have disastrous consequences over time—even when return distributions are stationary. Such criticisms of the mean-variance approach within the Von Neumann-Morgenstern framework have prompted several writers to suggest that investors maximize the expected value of utility functions with more “realistic” properties, while others have criticized the single-period focus of the model. One popular alternative utility function is the logarithmic function which exhibits decreasing absolute risk aversion and (conveniently) leads to myopic decision processes through time (i.e., investors treat each period as if it were the last, basing investment decisions on that period's wealth and return distributions only [8, 4]). (Other utility functions with constant relative risk aversion—such as the power function—also imply myopic decision rules within a multiperiod setting.)

Lawrence B. Smith, Comment: Brueggeman-Peiser and Noland Papers, The Journal of Financial and Quantitative Analysis, Vol. 14, No. 4, Proceedings of 14th Annual Conference of the Western Finance Association, June 21-23, 1979 (Nov., 1979), pp. 801-803

Christopher B. Barry, Effects of Uncertain and Nonstationary Parameters Upon Capital Market Equilibrium Conditions, The Journal of Financial and Quantitative Analysis, Vol. 13, No. 3 (Sep., 1978), pp. 419-433

issue of this Journal, Bierman 2 and Hass (BH) construct a steam roller for the purpose of cracking a nut.BH's paper is essentially an attempt to use subjective probabilities to set yields on new bond issues.I am concerned primarily with the first two-thirds of their paper (pp.757-67), which, in my view, contains a number of statements that are seriously misleading.The first section of this comment will briefly summarize those portions of pp.757-67 of their paper.The second section contains the comment itself, plus a few observations on the final portion of their paper. I.(1) Assuming a risk-neutral buyer of debt issues and given what they call the "probability of survival" (P), BH show how to obtain the "required" yield on a new risky perpetuity (their equation 4, p. 759).They use a perpetuity in order to avoid, at the outset, the complications created by the fact that (risky) borrowers must also, in every case, make not only interest payments but also payments on principal.They then state as their conclusions to this initial section of their paper that: Deceased, formerly University of North Carolina, Chapel Hill.The

The finance literature has devoted considerable attention to the study of yields, yield spreads, and rating classification for fixed income securities. In the corporate market, authors such as Hickman [6], Johnson [7], Sloane [9], and Van Home [12] have investigated the behavior of yields and yield spreads over time. Johnson found that the yield differential, defined as the corporate yield minus the equal maturity Treasury rate, was unrelated to maturity. Van Home found that this differential widened during recessionary periods; he interpreted this to reflect either a higher default probability or greater investor risk aversion. In his important paper published in 1959, Lawrence Fisher [4] employed cross-sectional data at five points in time to relate corporate yield spreads to four key variables which serve as proxies for default and marketability risks. Pogue and Soldofsky [8] extended Fisher's approach to explain not corporate bond yield spreads but rather bond ratings. As explanatory variables, Pogue and Soldofsky chose several measures of the firm's income and debt capacity.

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.

Rashmi B. Thakkar, Comment: "Dynamics of Corporate Debt Management, Decision Rules, and Some Empirical Evidence", The Journal of Financial and Quantitative Analysis, Vol. 9, No. 6 (Dec., 1974), pp. 1065-1066