Adaptive Strategy of Testing Alphas in High Dimensional Linear Factor Pricing Models
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866909165574684672 |
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| author | Zhao, Chenxi Zhao, Ping Feng, Long Wang, Zhaojun |
| author_facet | Zhao, Chenxi Zhao, Ping Feng, Long Wang, Zhaojun |
| contents | In recent years, there has been considerable research on testing alphas in high-dimensional linear factor pricing models. In our study, we introduce a novel max-type test procedure that performs well under sparse alternatives. Furthermore, we demonstrate that this new max-type test procedure is asymptotically independent from the sum-type test procedure proposed by Pesaran and Yamagata (2017). Building on this, we propose a Fisher combination test procedure that exhibits good performance for both dense and sparse alternatives. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_06984 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Adaptive Strategy of Testing Alphas in High Dimensional Linear Factor Pricing Models Zhao, Chenxi Zhao, Ping Feng, Long Wang, Zhaojun Methodology In recent years, there has been considerable research on testing alphas in high-dimensional linear factor pricing models. In our study, we introduce a novel max-type test procedure that performs well under sparse alternatives. Furthermore, we demonstrate that this new max-type test procedure is asymptotically independent from the sum-type test procedure proposed by Pesaran and Yamagata (2017). Building on this, we propose a Fisher combination test procedure that exhibits good performance for both dense and sparse alternatives. |
| title | Adaptive Strategy of Testing Alphas in High Dimensional Linear Factor Pricing Models |
| topic | Methodology |
| url | https://arxiv.org/abs/2404.06984 |