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基于预期效用-熵基金评级方法的投资组合表现

Performance of Portfolios Based on the Expected Utility-Entropy Fund Rating Approach.

作者信息

Chiew Daniel, Qiu Judy, Treepongkaruna Sirimon, Yang Jiping, Shi Chenxiao

机构信息

Business School, The University of Western Australia, Perth 6009, Australia.

School of Economics and Management, Beihang University, Beijing 100083, China.

出版信息

Entropy (Basel). 2021 Apr 18;23(4):481. doi: 10.3390/e23040481.

DOI:10.3390/e23040481
PMID:33919622
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8072692/
Abstract

Yang and Qiu proposed and reframed an expected utility-entropy (EU-E) based decision model. Later on, a similar numerical representation for a risky choice was axiomatically developed by Luce et al. under the condition of segregation. Recently, we established a fund rating approach based on the EU-E decision model and Morningstar ratings. In this paper, we apply the approach to US mutual funds and construct portfolios using the best rating funds. Furthermore, we evaluate the performance of the fund ratings based on the EU-E decision model against Morningstar ratings by examining the performance of the three models in portfolio selection. The conclusions show that portfolios constructed using the ratings based on the EU-E models with moderate tradeoff coefficients perform better than those constructed using Morningstar. The conclusion is robust to different rebalancing intervals.

摘要

杨和邱提出并重新构建了一个基于期望效用-熵(EU-E)的决策模型。后来,卢斯等人在隔离条件下公理化地开发了一种类似的风险选择数值表示。最近,我们基于EU-E决策模型和晨星评级建立了一种基金评级方法。在本文中,我们将该方法应用于美国共同基金,并使用评级最高的基金构建投资组合。此外,我们通过考察这三种模型在投资组合选择中的表现,来评估基于EU-E决策模型的基金评级相对于晨星评级的表现。结论表明,使用具有适度权衡系数的基于EU-E模型的评级构建的投资组合,其表现优于使用晨星评级构建的投资组合。该结论对于不同的再平衡间隔具有稳健性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17ae/8072692/e33c34b6ce71/entropy-23-00481-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17ae/8072692/2eb45f5b4508/entropy-23-00481-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17ae/8072692/9f3d16bd1eca/entropy-23-00481-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17ae/8072692/6b0c90cd417f/entropy-23-00481-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17ae/8072692/3de693bcf908/entropy-23-00481-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17ae/8072692/de2898f9014d/entropy-23-00481-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17ae/8072692/e33c34b6ce71/entropy-23-00481-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17ae/8072692/2eb45f5b4508/entropy-23-00481-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17ae/8072692/9f3d16bd1eca/entropy-23-00481-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17ae/8072692/6b0c90cd417f/entropy-23-00481-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17ae/8072692/3de693bcf908/entropy-23-00481-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17ae/8072692/de2898f9014d/entropy-23-00481-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17ae/8072692/e33c34b6ce71/entropy-23-00481-g006.jpg

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本文引用的文献

1
Entropy-Based Risk Control of Geological Disasters in Mountain Tunnels under Uncertain Environments.不确定环境下山区隧道地质灾害的熵基风险控制
Entropy (Basel). 2018 Jul 1;20(7):503. doi: 10.3390/e20070503.
2
The predictive ability of the expected utility-entropy based fund rating approach: A comparison investigation with Morningstar ratings in US.基于预期效用-熵的基金评级方法的预测能力:与美国晨星评级的比较研究
PLoS One. 2019 Apr 19;14(4):e0215320. doi: 10.1371/journal.pone.0215320. eCollection 2019.
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Entropy-based financial asset pricing.
基于熵的金融资产定价
PLoS One. 2014 Dec 29;9(12):e115742. doi: 10.1371/journal.pone.0115742. eCollection 2014.