Abstract
We propose a model selection method to systematically evaluate the contribution to asset pricing of any new factor, above and beyond what a high‐dimensional set of existing factors explains. Our methodology accounts for model selection mistakes that produce a bias due to omitted variables, unlike standard approaches that assume perfect variable selection. We apply our procedure to a set of factors recently discovered in the literature. While most of these new factors are shown to be redundant relative to the existing factors, a few have statistically significant explanatory power beyond the hundreds of factors proposed in the past.
| Original language | English |
|---|---|
| Pages (from-to) | 1327-1370 |
| Journal | The Journal of Finance |
| Volume | 75 |
| Issue number | 3 |
| Online published | 24 Jan 2020 |
| DOIs | |
| Publication status | Published - Jun 2020 |
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