This paper examines the effect of classifying a firm's equity or debt into subclasses of unequal seniority on the total expected tax burden of the firm and its security holders in a world with no agency and no bankruptcy costs. It is shown that, when positive income is taxed at a higher rate than that allowed on realized capital losses, expected taxes are minimized and the value of the firm is maximized if the firm has only one class of equity and, at most, one class of debt. This result helps to explain the common practice of issuing corporate bonds under open indentures. In fact, our empirical results indicate that before the advent of a differentiated capital gains tax in 1921, a great majority of publicly traded long-term industrial bonds were issued under closed indentures. By 1951, nearly all such debt was issued under single indentures (i.e., there was only one class of creditor).

A comparison of single and multifactor portfolio performance methodologies using Value Line and size-ranked portfolios indicates that although both methodologies provide unbiased estimates of portfolio performance, there are systematic differences in the power of the two methodologies. The predictive power of the multifactor methodology is superior for well-diversified portfolios but inferior for less diversified portfolios.

In this paper, we examine the pricing of European call options on stocks that have variance rates that change randomly. We study continuous time diffusion processes for the stock return and the standard deviation parameter, and we find that one must use the stock and two options to form a riskless hedge. The riskless hedge does not lead to a unique option pricing function because the random standard deviation is not a traded security. One must appeal to an equilibrium asset pricing model to derive a unique option pricing function. In general, the option price depends on the risk premium associated with the random standard deviation. We find that the problem can be simplified by assuming that volatility risk can be diversified away and that changes in volatility are uncorrelated with the stock return. The resulting solution is an integral of the Black-Scholes formula and the distribution function for the variance of the stock price. We show that accurate option prices can be computed via Monte Carlo simulations and we apply the model to a set of actual prices.

This paper derives and tests a new linear programming (LP) approach to bond portfolio management. The model elicits possible tax-clientele effects in the pricing of U.S. Government coupon bonds and simultaneously derives the optimal tax-specific bond portfolio. Analytically, the model derives these results by exploiting, for a given tax bracket, the price differential of an after-tax stream of cash flows. It accomplishes this objective by purchasing at the ask price “underpriced” bonds (for the specific tax bracket), while simultaneously selling at the bid price “overpriced” bonds. The model requires that the net cash flow, inclusive of purchased and sold bonds, be nonnegative at all future dates; the problem's formulation standardizes the position taken in each bond to a maximum of one unit. One of the model's appealing features is the parsimonious number of required calculations: only one LP program need be run per tax bracket. In addition to obtaining an “optimally” chosen tax-specific bond portfolio, the model also measures the after-tax term structure of spot U.S. Government interest rates for both tax-exempt and taxable investors. Finally, the superior monthly holding-period rates of return on the optimal taxspecific bond portfolio demonstrate an important property of the model's output.

Despite substantial debate, there has been little empirical analysis of the economic arguments concerning commercial bank expansion into securities activities. This paper uses the stock price response of commercial banking firms and securities firms to examine the risk and return effects of the announcement of bank entry into one such activity, discount brokerage. Our findings indicate that, while bank profitability and risk were largely unaffected by such entry, securities firms experienced a significant decline in market value. These results indicate that the objection of the securities industry to bank discount brokerage expansion was largely self-motivated and that bank safety and soundness would not be imperiled by such expansions.

This study examines daily price reactions to initial reviews of securities by the Value Line Investment Survey. The reviews are found to convey information to the market as significant abnormal returns are found over a 3-day period around release of the information. Furthermore, there is no statistically significant subsequent price reation after this 3-day period, consistent with market efficiency.

This paper extends a recent study by Malatesta [14] on measuring abnormal performance using joint generalized least squares. For monthly data and a random sample of securities, Malatesta finds that there is little benefit in using more sophisticated econometric techniques to identify abnormal returns. The current study extends these results using a design that is more amenable to the benefits of the generalized methods and is consistent with actual event studies. Most notably, the study uses a sample of securities experiencing an actual event and tests both monthly and daily data. In addition, iterative techniques are compared to the ordinary least squares and estimated generalized least squares methods. The results of this study support the original conclusions of Malatesta, indicating no measurable gain in using any of the systems methods for event study applications.

In this paper, we compare the robustness in application of the Gaussian assumption of security return distributions to the robustness of the general stable assumption. Using actual stock return data to simulate the “real world,” a stock market is constructed in which stock returns conform to a Gaussian distribution as well as to a stable Pareto-Levy distribution. Using these two sets of stock returns, efficient frontiers are generated under both assumptions of parametric environments. It is shown that the Gaussian assumption, and its incumbent statistical techniques, is preferable to the general stable assumption.