Comparing Cross-Section and Time-Series Factor Models
Comparing Cross-Section and Time-Series Factor Models
复制标题
比较横截面和时间序列因子模型
DOI：
10.2139/ssrn.3255748
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
K. French
中科院分区：
文献类型：
--
作者：
E. Fama;K. French
我们使用法马和MacBeth（1973）的横截面回归方法来构建与法马和French（2015）的时间序列因子相对应的横截面因子。仅使用横截面因子的时间序列模型比使用时间序列因子的时间序列模型更好地描述了平均收益。当我们施加常数因子载荷时，当我们使用时变载荷（对于时间序列因子是自然的）和时变载荷（对于横截面因子是自然的）时，情况就是这样。
作者提供了一个互联网附录，可在牛津大学出版社的网站上找到，旁边是最后发表的论文的链接。
We use the cross-section regression approach of Fama and MacBeth (1973) to construct cross-section factors corresponding to the time-series factors of Fama and French (2015). Time-series models that use only cross-section factors provide better descriptions of average returns than time-series models that use time-series factors. This is true when we impose constant factor loadings and when we use time-varying loadings that are natural for time-series factors and time-varying loadings that are natural for cross-section factors.
Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
影响因子：
6.1
作者：
GIBBONS, MR;ROSS, SA;SHANKEN, J
通讯作者：
SHANKEN, J