时间：2020年7月19日（周日）晚上6:30

形式：钉钉群视频会议

题目：Shrinking the cross-section

期刊：JFE

作者：Serhiy Koza, Stefan Nagel, Shrihari Santosh

摘要：We construct a robust stochastic discount factor(SDF) summarizing the joint explana-tory power of a large number of cross-sectional stock return predictors. Our method achieves robust out-of-sample performance in this high-dimensional setting by imposing an economically motivated prior on SDF coefficients that shrinks contributions of low-variance principal components of the candidate characteristics-based factors. We find that characteristics-sparse SDFs formed from a few such factors--e.g., the four- or five-factor models in the recent literature--cannot adequately summarize the cross-section of ex-pected stock returns. However, an SDF formed from a small number of principal compo- nents performs well.

主讲人：朱雅蓓 博士研究生