资本资产定价模型
计量经济学
风险溢价
因子分析
估计员
经济
可见的
资产(计算机安全)
数学
统计
计算机科学
计算机安全
量子力学
物理
作者
Stefano Giglio,Dacheng Xiu
摘要
Standard estimators of risk premia in linear asset pricing models are biased if some priced factors are omitted. We propose a three-pass method to estimate the risk premium of an observable factor, which is valid even when not all factors in the model are specified or observed. The risk premium of the observable factor can be identified regardless of the rotation of the other control factors if together they span the true factor space. Our approach uses principal components of test asset returns to recover the factor space and additional regressions to obtain the risk premium of the observed factor.
科研通智能强力驱动
Strongly Powered by AbleSci AI