| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w23227 |
| 来源ID | Working Paper 23227 |
| Dissecting Characteristics Nonparametrically | |
| Joachim Freyberger; Andreas Neuhierl; Michael Weber | |
| 发表日期 | 2017-03-13 |
| 出版年 | 2017 |
| 语种 | 英语 |
| 摘要 | We propose a nonparametric method to test which characteristics provide independent information for the cross section of expected returns. We use the adaptive group LASSO to select characteristics and to estimate how they affect expected returns nonparametrically. Our method can handle a large number of characteristics, allows for a flexible functional form, and is insensitive to outliers. Many of the previously identified return predictors do not provide incremental information for expected returns, and nonlinearities are important. Our proposed method has higher out-of-sample explanatory power compared to linear panel regressions, and increases Sharpe ratios by 50%. |
| 主题 | Econometrics ; Estimation Methods ; Financial Economics ; Portfolio Selection and Asset Pricing |
| URL | https://www.nber.org/papers/w23227 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/580901 |
| 推荐引用方式 GB/T 7714 | Joachim Freyberger,Andreas Neuhierl,Michael Weber. Dissecting Characteristics Nonparametrically. 2017. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w23227.pdf（2873KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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