Dutta, S and Jain, S (2024) Shrinkage and thresholding approaches for expected utility portfolios: An analysis in terms of predictive ability. In: Finance Research Letters, 64 .
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Abstract
In this paper, we estimate Expected Utility Portfolios (EUPs) in high-dimensional, low-sample settings using various covariance matrix estimation methods, including shrinkage and thresholding-based methods. We perform synthetic experiments comparing these methods, using Average Out-of-Sample Variance (AOV) for Global Minimum Variance (GMV) portfolios and Average Out-of-Sample Utility (AOU) for EUPs. Additionally, we propose a practical method for fund managers to select optimal models based on empirical data, relying on AOV and AOU performance measures. The results indicate that shrinkage-based methods outperform thresholding-based ones in high-dimensional settings, with non-linear shrinkage being particularly effective. © 2024 Elsevier Inc.
Item Type: | Journal Article |
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Publication: | Finance Research Letters |
Publisher: | Elsevier Ltd |
Additional Information: | The copyright for this article belongs to Elsevier Ltd. |
Department/Centre: | Division of Interdisciplinary Sciences > Management Studies |
Date Deposited: | 20 May 2024 11:45 |
Last Modified: | 20 May 2024 11:45 |
URI: | https://eprints.iisc.ac.in/id/eprint/84748 |
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