Predicting Risk: Some New Generalizations
利用规模和行业等先验信息，通过多重收缩方法改进传统风险调整技术，提升了对单个企业系统性风险的预测效果。
Existing adjustment techniques for forecasting systematic risk of individual firms have been based on relatively uniformative prior knowledge about the cross-sectional distribution of risk estimates. This study introduces prior information in the form of size and industry-based cross-sectional distributions of risk estimates. Such information is incorporated into forecasts using familiar and generalized adjustment techniques, the latter being based on recently developed multiple shrinkage methods. Improved forecast performance results.