A Full-Information Approach for Estimating Divisional Betas
提出一种基于理论、利用全部可用信息且数据需求精简的部门贝塔估计新方法，可用简单统计工具实现，结果清晰可解释。基于大样本股票数据的实证表明，该方法比现有方法更准确。
A new approach for estimating divisional betas is developed in this study. The approach is based on a sound theoretical foundation; utilizes all available information, yet still has parsimonious data requirements; can be implemented with simple statistical tools; and provides unambiguously interpretable results. The proposed methodology is applied to a large sample of stocks. The results indicate that the proposed methodology can more accurately estimate divisional betas than other approaches previously advocated in the finance literature.