The search for an economically sound procedure for estimating an appropriate rate of return on equity consistent with the Supreme Court's ruling in the Hope case [13] has led many economists, financial experts, and public service commissions to estimate the rate of return on equity with the capital asset pricing model (CAPM) (see [30], [19], and [21]). The popularity of the CAPM in regulatory proceedings was reported by Harrington [15] who, in a survey of public service commissions, found that 38 states were considering or had seen the CAPM used, two jurisdictions preferred the CAPM, Oregon required the CAPM, and South Carolina would require the CAPM in all future cases. Hence, given the popularity of the CAPM and the tremendous economic impact that outcomes of regulatory proceedings have on the financial well-being of both the regulated firm and the consumer, it is critical that if the CAPM is used in regulatory proceedings that it be applied in the best manner possible and that any limitations associated with the CAPM be recognized fully.

Pamela P. Peterson, Gary A. Benesh, A Reexamination of the Empirical Relationship Between Investment and Financing Decisions, The Journal of Financial and Quantitative Analysis, Vol. 18, No. 4 (Dec., 1983), pp. 439-453

In 1959, Henry Lataná [2] proposed an approximation to the geometric mean that was a simple function of the arithmetic mean and variance, thereby indicating a mathematical relationship between the risky investment choice model of Bernoulli and the Markowitz mean-variance model. In 1969, Young and Trent [4] presented empirical test results of the Latané approximation, as well as a set of other approximations to the geometric mean based on moments, and concluded that the Latane formula yielded a quite accurate approximation to the geometric mean. In Jean's 1980 paper [1] relating the geometric mean model to stochastic dominance models, the infinite series representation of the geometric mean used suggests a more accurate approximation with moments of the geometric mean than that contained in the earlier papers may be possible. Various forms of that series expressed in alternate-origin moments are tested empirically below, and the results confirm that this later series does yield the greatest accuracy of the three approaches.

William Stein, Roger Pfaffenberger, P. C. Kumar, On the Estimation Risk in First-Order Stochastic Dominance: A Note, The Journal of Financial and Quantitative Analysis, Vol. 18, No. 4 (Dec., 1983), pp. 471-476

Robert M. Bowen, Richard P. Castanias, Lane A. Daley, Intra-Industry Effects of the Accident at Three Mile Island, The Journal of Financial and Quantitative Analysis, Vol. 18, No. 1 (Mar., 1983), pp. 87-111