Professor McCraw surveys the state of the art of understanding regulatory commissions in American history, evaluating the relevant literature in history, economics, political science, and law.

The appearance of large, integrated industrial firms at the turn of the century encouraged the introduction of innovative accounting practices. Professor Johnson examines the centralized management accounting system that made it possible for one such firm, the DuPont Powder Co., to plan its long-term development and to avoid the internal inefficiency that sometimes accompanies enormous size.

Professor Jennings, in his recent article [2], developed a model to estimate convertible bond premiums. The model incorporates the capital asset pricing model to evaluate convertible bonds. The purpose of this comment is not to criticize the general development of the model but to point out flaws in its implementation which influence Jennings' empirical results.

Numerous empirical studies have appeared in recent years concerning the behavior of stock market prices. Cootner's book [2] presents an excellent summary of pre-1964 efforts, while Fama's paper [5] discusses some of the more recent work. While a few writers believe that certain price trends and patterns exist which enable the investor to make better predictions of the expected value of future stock price changes, the majority of these studies conclude that past price data alone cannot form the basis for the prediction of the expected value of price movements in the stock market.

In Gonedes [5], the results of an empirical analysis of accounting-based and market-based estimates of systematic risk were presented. These results suggested that there is, in general, a “statistically significant” relationship between accounting-based and market-based estimates of systematic risk at the level of individual securities, if the accounting-based estimates are conditional upon first-differences or scaled first-differences of the accounting numbers. The differencing transformation seemed to induce relatively better specified models for the accounting numbers.

The Stable (or Pareto-Lévy) distribution has been of considerable interest in describing the behavior of security prices ever since the important work by Mandelbrot [6], [7] and Fama [1]. The aforementioned contributions focused on the empirical hypothesis that security price data are better fitted by theoretical distributions with infinite variance rather than finite variance. Specifically, in the case of Stable distributions, the “characteristic exponent” is less than two, and the data are not adequately fitted by a normal distribution. Remarkably, however, although almost the entire body of literature addressing empirical questions with respect to the distribution of security prices investigages the behavior of the (natural) logarithm of security price relatives, to this author's knowledge no paper exists which analyzes the portfolio choice implications of the assumption that the logarithm of the asset returns has a symmetric Stable distribution with infinite variance. Thus, in Fama [2], Samuelson [10], and Ziemba [12], where the problem of selecting an optimal portfolio in Stable markets is the object of concern, one finds that it is assumed that the price-relatives (returns) have a Stable distribution; this rather than the logarithm of the price relatives. And it should be noted that none of these authors suggests that the untransformed price-relatives are better-fitted by a symmetric Stable distribution as compared with the logarithm of the price-relatives.

The purpose of this paper is to examine the intertemporal relationship between variations in the prices of individual common stocks and variations in the rest of the stock market. Empirical data are analyzed to determine the frequency with which stock prices precede, occur simultaneously, and follow movements in the market average.