Measuring skewness premia

• 成果类型: Article
• 署名作者: Langlois, Hugues
• 署名单位: Hautes Etudes Commerciales (HEC) Paris
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/j.jfineco.2019.06.002
• 发表日期: 2020
• 页码: 399-424
• 关键词: Systematic skewness; COSKEWNESS; Idiosyncratic skewness; Large panel regression; forecasting

摘要

We provide a new methodology to empirically investigate the respective roles of systematic and idiosyncratic skewness in explaining expected stock returns. Using a large number of predictors, we forecast the cross-sectional ranks of systematic and idiosyncratic skewness, which are easier to predict than their actual values. Compared to other measures of ex ante systematic skewness, our forecasts create a significant spread in ex post systematic skewness. A predicted systematic skewness risk factor carries a significant and robust risk premium that ranges from 6% to 12% per year. In contrast, the role of idiosyncratic skewness in pricing stocks is less robust. (C) 2019 Elsevier B.V. All rights reserved.