Please use this identifier to cite or link to this item:
https://doi.org/10.1287/opre.2019.1858
DC Field | Value | |
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dc.title | Portfolio Construction by Mitigating Error Amplification: The Bounded-Noise Portfolio | |
dc.contributor.author | Zhao, Long | |
dc.contributor.author | Chakrabarti, Deepayan | |
dc.contributor.author | Muthuraman, Kumar | |
dc.date.accessioned | 2023-07-17T05:53:28Z | |
dc.date.available | 2023-07-17T05:53:28Z | |
dc.date.issued | 2019-07-01 | |
dc.identifier.citation | Zhao, Long, Chakrabarti, Deepayan, Muthuraman, Kumar (2019-07-01). Portfolio Construction by Mitigating Error Amplification: The Bounded-Noise Portfolio. OPERATIONS RESEARCH 67 (4) : 965-983. ScholarBank@NUS Repository. https://doi.org/10.1287/opre.2019.1858 | |
dc.identifier.issn | 0030-364X | |
dc.identifier.issn | 1526-5463 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/243143 | |
dc.description.abstract | We address the problem of poor portfolio performance when a minimumvariance portfolio is constructed using the sample estimates. Estimation errors are mostly blamed for the poor portfolio performance. However, we argue that even small unbiased estimation errors can lead to significantly bad performance because the optimization step amplifies errors, in a nonsymmetric way. Instead of trying to independently improve the estimation step or fix the optimization step for robustness, we disentangle the well-estimated aspects from the poorly estimated aspects of the covariancematrix. By using a single parameter held constant over all data sets and time periods, our method achieves excellent performance both empirically and in the simulation.We also show how to use information from the sample mean to construct mean-variance portfolios that have higher out-of-sample Sharpe ratios. | |
dc.language.iso | en | |
dc.publisher | INFORMS | |
dc.source | Elements | |
dc.subject | Social Sciences | |
dc.subject | Science & Technology | |
dc.subject | Technology | |
dc.subject | Management | |
dc.subject | Operations Research & Management Science | |
dc.subject | Business & Economics | |
dc.subject | portfolio choice | |
dc.subject | estimation error | |
dc.subject | NAIVE DIVERSIFICATION | |
dc.subject | NONLINEAR SHRINKAGE | |
dc.subject | MARKOWITZ | |
dc.subject | SELECTION | |
dc.subject | PERFORMANCE | |
dc.subject | VARIANCE | |
dc.subject | MARKET | |
dc.subject | TESTS | |
dc.type | Article | |
dc.date.updated | 2023-07-14T07:51:35Z | |
dc.contributor.department | ANALYTICS AND OPERATIONS | |
dc.description.doi | 10.1287/opre.2019.1858 | |
dc.description.sourcetitle | OPERATIONS RESEARCH | |
dc.description.volume | 67 | |
dc.description.issue | 4 | |
dc.description.page | 965-983 | |
dc.published.state | Published | |
Appears in Collections: | Elements Staff Publications |
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File | Description | Size | Format | Access Settings | Version | |
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final_Jan2019 copy.pdf | Accepted version | 967.6 kB | Adobe PDF | OPEN | Post-print | View/Download |
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