Accounting for the Accuracy of Beta Estimates in CAPM Tests on Assets with Time‐varying Risks
提出两种方法提高CAPM两阶段测试中风险溢价估计的准确性：显式建模贝塔的时变性，以及利用个股信息并赋予更可靠的贝塔预测更大权重。应用于赫尔辛基证券交易所数据，新方法发现了显著的正向关系，而传统Fama-MacBeth方法则未发现。
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.