Asset Performance Evaluation with Mean-Variance Ratio
Bai, et al. (2011c) develop the mean-variance-ratio (MVR) statistic to test the performance among assets for small samples. They provide theoretical reasoning to use MVR and prove that our proposed statistic is uniformly most powerful unbiased. In this paper we illustrate the superiority of our prop...
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sg-smu-ink.lkcsb_research-41552018-07-10T04:14:40Z Asset Performance Evaluation with Mean-Variance Ratio Bai, Zhidong PHOON, Kok Fai Wang, Keyan Wong, Wing-Keung Bai, et al. (2011c) develop the mean-variance-ratio (MVR) statistic to test the performance among assets for small samples. They provide theoretical reasoning to use MVR and prove that our proposed statistic is uniformly most powerful unbiased. In this paper we illustrate the superiority of our proposed test over the Sharpe ratio (SR) test by applying both tests to analyze the performance of Commodity Trading Advisors (CTAs). Our findings show that while the SR test concludes most of the CTA funds being analyzed as being indistinguishable in their performance, our proposed statistics show that some funds outperform the others. On the other hand, when we apply the SR statistic on some other funds in which the recent difference between the two funds is insignificant and even changes directions, the SR statistic indicates that one fund is significantly outperforming another fund whereas the MVR statistic could detect the change. 2011-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/lkcsb_research/3156 https://ink.library.smu.edu.sg/context/lkcsb_research/article/4155/viewcontent/2011PBFEAM_115.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Sharpe ratio hypothesis testing uniformly most powerful unbiased Finance and Financial Management Management Sciences and Quantitative Methods |
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Sharpe ratio hypothesis testing uniformly most powerful unbiased Finance and Financial Management Management Sciences and Quantitative Methods Bai, Zhidong PHOON, Kok Fai Wang, Keyan Wong, Wing-Keung Asset Performance Evaluation with Mean-Variance Ratio |
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Bai, et al. (2011c) develop the mean-variance-ratio (MVR) statistic to test the performance among assets for small samples. They provide theoretical reasoning to use MVR and prove that our proposed statistic is uniformly most powerful unbiased. In this paper we illustrate the superiority of our proposed test over the Sharpe ratio (SR) test by applying both tests to analyze the performance of Commodity Trading Advisors (CTAs). Our findings show that while the SR test concludes most of the CTA funds being analyzed as being indistinguishable in their performance, our proposed statistics show that some funds outperform the others. On the other hand, when we apply the SR statistic on some other funds in which the recent difference between the two funds is insignificant and even changes directions, the SR statistic indicates that one fund is significantly outperforming another fund whereas the MVR statistic could detect the change. |
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Bai, Zhidong PHOON, Kok Fai Wang, Keyan Wong, Wing-Keung |
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Bai, Zhidong PHOON, Kok Fai Wang, Keyan Wong, Wing-Keung |
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Bai, Zhidong |
title |
Asset Performance Evaluation with Mean-Variance Ratio |
title_short |
Asset Performance Evaluation with Mean-Variance Ratio |
title_full |
Asset Performance Evaluation with Mean-Variance Ratio |
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Asset Performance Evaluation with Mean-Variance Ratio |
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Asset Performance Evaluation with Mean-Variance Ratio |
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asset performance evaluation with mean-variance ratio |
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Institutional Knowledge at Singapore Management University |
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2011 |
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https://ink.library.smu.edu.sg/lkcsb_research/3156 https://ink.library.smu.edu.sg/context/lkcsb_research/article/4155/viewcontent/2011PBFEAM_115.pdf |
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