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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2018
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/1808.02953 |
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| _version_ | 1866913365895413760 |
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| author | Chakrabarti, Arnab Sen, Rituparna |
| author_facet | Chakrabarti, Arnab Sen, Rituparna |
| contents | For high dimensional data, some of the standard statistical techniques do not work well. So modification or further development of statistical methods are necessary. In this paper, we explore these modifications. We start with the important problem of estimating high dimensional covariance matrix. Then we explore some of the important statistical techniques such as high dimensional regression, principal component analysis, multiple testing problems and classification. We describe some of the fast algorithms that can be readily applied in practice. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1808_02953 |
| institution | arXiv |
| publishDate | 2018 |
| record_format | arxiv |
| spellingShingle | Some Statistical Problems with High Dimensional Financial data Chakrabarti, Arnab Sen, Rituparna Statistical Finance For high dimensional data, some of the standard statistical techniques do not work well. So modification or further development of statistical methods are necessary. In this paper, we explore these modifications. We start with the important problem of estimating high dimensional covariance matrix. Then we explore some of the important statistical techniques such as high dimensional regression, principal component analysis, multiple testing problems and classification. We describe some of the fast algorithms that can be readily applied in practice. |
| title | Some Statistical Problems with High Dimensional Financial data |
| topic | Statistical Finance |
| url | https://arxiv.org/abs/1808.02953 |