数字经济前沿文献讨论会第7期：Dissecting Characteristics Nonparametrically
222 时间：2020年8月9日（周日）晚上6:30
形式：钉钉群视频会议
题目：Dissecting Characteristics Nonparametrically
期刊：The Review of Financial Studies
作者：Joachim Freyberger，Andreas Neuhierl，MichaelWeber
摘要：We propose a nonparametric method to study which characteristics provide incremental information for the cross-section of expected returns. We use the adaptive group LASSO to select characteristics and to estimate how selected characteristics affect expected returns nonparametrically. Our method can handle a large number of characteristics and allows for a flexible functional form. Our implementation is insensitive to outliers. Many of the previously identified return predictors don't provide incremental information for expected returns, and nonlinearities are important. We study our method's properties in simulations and find large improvements in both model selection and prediction compared to alternative selection methods.
主讲人：林思慧 博士生
