Estimating Market Model Betas: A Comparison of Random Coefficient Methods and Their Ability to Correctly Identify Random Variation
比较了最大似然法和广义最小二乘法在估计市场模型贝塔时的表现，发现两种方法在合理变异水平下均无法稳定识别随机系数过程，提示此前观察到的显著随机系数可能更普遍。
When estimating market model betas using random coefficient methods, the rather fine distinction between significance or insignificance, as argued in recent studies, overlooks two important factors. First, the maximum likelihood method has not been tested in comparison to the generalized least squares approximation. Second, and more importantly, the ability of these methodologies to correctly identify a known random coefficient process has not been examined in the context of the market model. Using both simulations and subsequent empirical tests, this study shows that, for reasonable levels of variation in beta, neither method can consistently identify a random coefficient process. These results suggest that the nominal level of significant random coefficients previously observed could be indicative of a much more predominant phenomenon.