[An integrated econometric view of maximum likelihood methods and more traditional two-pass approaches to estimating beta-pricing models is presented. Several aspects of the well-known "errors-in-variables problem" are considered, and an earlier conjecture concerning the merits of simultaneous estimation of beta and price of risk parameters is evaluated. The traditional inference procedure is found, under standard assumptions, to overstate the precision of price of risk estimates and an asymptotically valid correction is derived. Modifications to accommodate serial correlation in market-wide factors are also discussed.]

This paper provides a simple proof of a recent theorem presented by Haim Reisman (1992) concerning the use of proxies for the factors in the return-generating process of the arbitrage pricing theory. In the single-factor case, the theorem asserts that any variable correlated with the factor can serve as the benchmark in an approximate arbitrage pricing theory expected return relation. The significance of this result is considered and a new direction for empirical work on "arbitrage pricing" is outlined.

An integrated econometric view of maximum likelihood methods and more traditional two-pass approaches to estimating beta-pricing models is presented. Several aspects of the well-known “errors-in-variables problem ” are considered, and an earlier conjecture concerning the merits of simultaneous estimation of beta and price of risk parameters is evaluated. The traditional inference procedure is found, under standard assumptions, to overstate the precision of price of risk estimates and an asymptotically valid correction is derived. Modifications to accommodate serial correlation in market-wide factors are also discussed Sharpe (1964) and Lintner (1965) demonstrate that, in equilibrium, a financial asset’s expected return must be positively linearly related to its “beta, ” a measure of systematic risk or co-movement with the market portfolio return: 1 This article is an extension of the second chapter of my doctoral dissertation at Carnegie Mellon University. Recent versions were presented in seminars

This paper provides a simple proof of a recent theorem presented by In the single-factor case, the theorem asserts that any variable correlated with the factor can serve as the benchmark in an approximate APT expected return relation. The significance of this result is considered and a new direction for empirical work on "arbitrage pricing" is outlined.

ABSTRACT This paper provides a simple proof of a recent theorem presented by Reisman (1992) , concerning the use of proxies for the factors in the return‐generating process of the arbitrage pricing theory (APT). In the single‐factor case, the theorem asserts that any variable correlated with the factor can serve as the benchmark in an approximate APT expected return relation. The significance of this result is considered and a new direction for empirical work on “arbitrage pricing” is outlined.

This paper examines the extent to which aggregate stock return variation is explained by variables chosen to reflect revisions in expectations of future dividends. In effect, we decompose realized dividend growth into expected and unexpected components using information in aggregate investment, dividend yield, and future returns. A parsimonious specification accounts for over 70% of annual return variation. We also conduct a cross-sectional experiment using portfolios formed on the basis of annual return performance. This analysis shows that nearly 90% of the portfolio return variation is explained by dividend and expected return variables.