Portfolio Inefficiency and the Cross-Section of Mean Returns (Revised: 6-94)

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Abstract
In a generalized-least-squares (GLS) regression of mean returns on betas, the slope and R-squared are determined uniquely by the mean-variance location of the market index relative to the minimum-variance boundary. In contrast to ordinary-least-squares, GLS gives a zero slope only if the mean return on the market index equals that of the global minimum-variance portfolio. When fitted mean returns from a cross-sectional regression on any variables serve as inputs to standard portfolio optimization, GLS regression provides the optimal inputs, and that regression’s R-squared depends on the relative efficiency of the optimized portfolio.

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