Bayesian estimation and optimization for learning sequential regularized portfolios
This paper incorporates Bayesian estimation and optimization into a portfolio selection framework, particularly for high-dimensional portfolios in which the number of assets is larger than the number of observations. We leverage a constrained \ell 1 minimization approach, called the linear programmi...
Автори: | , |
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Інші автори: | |
Формат: | Journal Article |
Мова: | English |
Опубліковано: |
2023
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Предмети: | |
Онлайн доступ: | https://hdl.handle.net/10356/169279 |