| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w26418 |
| 来源ID | Working Paper 26418 |
| Measuring \u201cDark Matter\u201d in Asset Pricing Models | |
| Hui Chen; Winston Wei Dou; Leonid Kogan | |
| 发表日期 | 2019-12-02 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | We formalize the concept of “dark matter” in asset pricing models by quantifying the additional informativeness of cross-equation restrictions about fundamental dynamics. The dark matter measure captures the degree of fragility for models that are potentially misspecified and unstable: a large dark matter measure signifies that the model lacks internal refutability (weak power of optimal specification tests) and external validity (high overfitting tendency and poor out-of-sample fit). The measure can be computed at low cost even for complex dynamic structural models. To illustrate its applications, we provide quantitative examples applying the measure to (time-varying) rare-disaster risk and long-run risk models. |
| 主题 | Econometrics ; Estimation Methods ; Microeconomics ; Economics of Information ; Macroeconomics ; Business Cycles ; Financial Economics ; Portfolio Selection and Asset Pricing |
| URL | https://www.nber.org/papers/w26418 |
| 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/584170 |
| 推荐引用方式 GB/T 7714 | Hui Chen,Winston Wei Dou,Leonid Kogan. Measuring \u201cDark Matter\u201d in Asset Pricing Models. 2019. |
| 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 | ||
| w26418.pdf（957KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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