High dimensional estimator of the maximum Sharpe ratio with and without short sales
A cross-validated weighted estimator is proposed for the population maximum Sharpe ratio with and without short sales. The estimator is an optimal linear combination of a factor analysis-based estimator and a linear shrinkage estimator, which is expected to remain competitive in various covariance s...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/140169 |
| _version_ | 1824453770802626560 |
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| author | Li, Qinyu |
| author2 | Pan Guangming |
| author_facet | Pan Guangming Li, Qinyu |
| author_sort | Li, Qinyu |
| collection | NTU |
| description | A cross-validated weighted estimator is proposed for the population maximum Sharpe ratio with and without short sales. The estimator is an optimal linear combination of a factor analysis-based estimator and a linear shrinkage estimator, which is expected to remain competitive in various covariance structures. Simulation results imply that the weighted estimator outperforms at least one of its constituting estimators under certain covariance structure and the difference is significant, especially when the dimension is large or close to the sample size. |
| first_indexed | 2025-02-19T03:11:42Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/140169 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:11:42Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1401692023-02-28T23:18:26Z High dimensional estimator of the maximum Sharpe ratio with and without short sales Li, Qinyu Pan Guangming School of Physical and Mathematical Sciences GMPAN@ntu.edu.sg Science::Mathematics A cross-validated weighted estimator is proposed for the population maximum Sharpe ratio with and without short sales. The estimator is an optimal linear combination of a factor analysis-based estimator and a linear shrinkage estimator, which is expected to remain competitive in various covariance structures. Simulation results imply that the weighted estimator outperforms at least one of its constituting estimators under certain covariance structure and the difference is significant, especially when the dimension is large or close to the sample size. Bachelor of Science in Mathematical Sciences 2020-05-27T03:38:31Z 2020-05-27T03:38:31Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/140169 en application/pdf Nanyang Technological University |
| spellingShingle | Science::Mathematics Li, Qinyu High dimensional estimator of the maximum Sharpe ratio with and without short sales |
| title | High dimensional estimator of the maximum Sharpe ratio with and without short sales |
| title_full | High dimensional estimator of the maximum Sharpe ratio with and without short sales |
| title_fullStr | High dimensional estimator of the maximum Sharpe ratio with and without short sales |
| title_full_unstemmed | High dimensional estimator of the maximum Sharpe ratio with and without short sales |
| title_short | High dimensional estimator of the maximum Sharpe ratio with and without short sales |
| title_sort | high dimensional estimator of the maximum sharpe ratio with and without short sales |
| topic | Science::Mathematics |
| url | https://hdl.handle.net/10356/140169 |
| work_keys_str_mv | AT liqinyu highdimensionalestimatorofthemaximumsharperatiowithandwithoutshortsales |