This note shows that a linear market model is sufficient to derive a linear relationship between beta and expected return. Furthermore, the slope of the relationship will be identical with that of the Capital Asset Pricing Model if the return on the market portfolio is normally distributed. However, results from characterization theory suggest that the linear market model assumption is close to that of multivariate normality.

Abstract During the past decade the organizations responsible for regulating the form and content of accounting disclosures have become increasingly active. As a result of this activity, the authoritative pronouncements in accounting have become increasingly technical and intricate in nature. This has caused a problem for accounting education: it has become very difficult to cover all, or even most, of the pronouncements within the standard accounting curriculum. This paper examines the approach adopted in law schools, where this problem has existed for some time. The basic approach, a blend of general-principles courses with applied research courses, is found to be adaptable to accounting education. Specifically, this paper recommends that accounting education should include applied accounting research techniques in its curricula to provide students with the means of dealing with a detailed and cumbersome body of authoritative literature. The paper also provides a suggested research design for conducting applied accounting research.

[Forward and spot exchange rates are modelled as an unrestricted bivariate autoregression from weekly data on the New York foreign exchange market for June, 1973 to April, 1980. The null hypothesis that the forward exchange rate is an unbiased estimate of the corresponding future spot exchange rate is tested by means of a nonlinear Wald test and is rejected for all six currencies considered. The results cast doubt on a central assumption in many current models of exchange rate behavior.]

One of the validity of a scientific hypothesis its forecasting accuracy. Thus one of the hypothesis that the market can be used to allocate manpower to defense, as to any other occupation, its ability to predict voluntary enlistments. In our earlier paper, a simple model of accessions and enlistments to the U.S. armed forces was estimated, the conclusion being that the allvolunteer force (A VF) is an experiment in market economics which, far from having failed, has not yet been put to the test (McNown et al., 1980, p. 130). Although one may not be particularly sanguine about the prospects for testing the market experiment itself, one can at least expose the hypothesis to further scrutiny. This paper reports the results of an accuracy analysis of forecasts generated by the model, and, since the results on the whole are encouraging and the topic remains of considerable interest to the public and to policymakers alike,1 also presents updated estimates of the personnel supply elasticities. I. A Military Personnel Supply Model

A solution method and an estimation method for nonlinear rational expectations models are presented in this paper.The solution method can be used in forecasting and policy applications and can handle models with serial correlation and multiple viewpoint dates.When applied to linear models, the solution method yields the same results as those obtained from currently available methods that are designed specifically for linear models.It is, however, more flexible and general than these methods.The estimation method is based on the maximum likelihood principal.It is, as far as we know, the only method available for obtaining maximum likelihood estimates for nonlinear rational expectations models.The method has the advantage of being applicable to a wide range of models, including, as a special case, linear models.The method can also handle different assumptions about the expectations of the exogenous variables, something which is not true of currently available approaches to linear models.