| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w21329 |
| 来源ID | Working Paper 21329 |
| Backtesting Strategies Based on Multiple Signals | |
| Robert Novy-Marx | |
| 发表日期 | 2015-07-13 |
| 出版年 | 2015 |
| 语种 | 英语 |
| 摘要 | Strategies selected by combining multiple signals suffer severe overfitting biases, because underlying signals are typically signed such that each predicts positive in-sample returns. “Highly significant” backtested performance is easy to generate by selecting stocks on the basis of combinations of randomly generated signals, which by construction have no true power. This paper analyzes t-statistic distributions for multi-signal strategies, both empirically and theoretically, to determine appropriate critical values, which can be several times standard levels. Overfitting bias also severely exacerbates the multiple testing bias that arises when investigators consider more results than they present. Combining the best k out of n candidate signals yields a bias almost as large as those obtained by selecting the single best of nᵏ candidate signals. |
| 主题 | Econometrics ; Estimation Methods ; Financial Economics ; Portfolio Selection and Asset Pricing |
| URL | https://www.nber.org/papers/w21329 |
| 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/579002 |
| 推荐引用方式 GB/T 7714 | Robert Novy-Marx. Backtesting Strategies Based on Multiple Signals. 2015. |
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