Abstract
This paper advocates two ways to make more efficient use of available information in reducing the bias of the risk premium estimate in two‐pass tests of the CAPM. First, explicit modelling of the time‐variability of betas can improve the accuracy of the beta forecasts. Second, the cross‐sectional information available can be exploited more efficiently using individual stocks instead of portfolios provided that noisy beta predictions are given a smaller weight than more accurate ones. This paper proposes an adjustment of the cross‐sectional regressions of excess returns against betas to give larger weights to more reliable beta forecasts. A significant positive relationship between returns and the beta forecast is obtained when the proposed approach is applied to data from the Helsinki Stock Exchange, while the traditional Fama–MacBeth approach as such finds no relationship at all.