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Comparison and Research on Diversified Portfolios with Several Entropy Measures Based on Different Psychological States
In previous studies, there were few portfolio models involving investors’ psychological states, market ambiguity and entropy. Some entropy can make the model have the effect of diversifying investment, which is very important. This paper mainly studies four kinds of entropy. First, we obtained four...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597257/ https://www.ncbi.nlm.nih.gov/pubmed/33286894 http://dx.doi.org/10.3390/e22101125 |
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author | Deng, Xue Lin, Tao Chen, Chuangjie |
author_facet | Deng, Xue Lin, Tao Chen, Chuangjie |
author_sort | Deng, Xue |
collection | PubMed |
description | In previous studies, there were few portfolio models involving investors’ psychological states, market ambiguity and entropy. Some entropy can make the model have the effect of diversifying investment, which is very important. This paper mainly studies four kinds of entropy. First, we obtained four definitions of entropy from the literature, and gave the function of fuzzy entropy in different psychological states through strict mathematical proof. Then, we construct a fuzzy portfolio entropy decision model based on the investor’s psychological states, and compared it with the possibilistic mean–variance model. Then we presented a numerical example and compared the five different models established. By comparing the results, we find that: (a) The possibilistic mean–Shannon entropy model solves the problem of the possibility of excessive concentration in the possibilistic mean–variance model, but the dispersion is not enough. Conversely, the possibilistic mean–Yager entropy is over–emphasized due to the definition of its own function, such that it gave an investment pattern of equal weight distribution or approximate average distribution. (b) The results of possibilistic mean–proportional entropy can be said to be the middle status of the portfolios of possibilistic mean–Shannon entropy and possibilistic mean–Yager entropy. This portfolio not only achieves a certain rate of return, but also disperses the risk to some extent. (c) The lines of satisfaction for portfolios derived from different models are approximately U–shaped with the increase in return preference. (d) The possibilistic mean–Shannon entropy model tends to have the highest portfolio satisfaction with the same psychological state of the investor. |
format | Online Article Text |
id | pubmed-7597257 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75972572020-11-09 Comparison and Research on Diversified Portfolios with Several Entropy Measures Based on Different Psychological States Deng, Xue Lin, Tao Chen, Chuangjie Entropy (Basel) Article In previous studies, there were few portfolio models involving investors’ psychological states, market ambiguity and entropy. Some entropy can make the model have the effect of diversifying investment, which is very important. This paper mainly studies four kinds of entropy. First, we obtained four definitions of entropy from the literature, and gave the function of fuzzy entropy in different psychological states through strict mathematical proof. Then, we construct a fuzzy portfolio entropy decision model based on the investor’s psychological states, and compared it with the possibilistic mean–variance model. Then we presented a numerical example and compared the five different models established. By comparing the results, we find that: (a) The possibilistic mean–Shannon entropy model solves the problem of the possibility of excessive concentration in the possibilistic mean–variance model, but the dispersion is not enough. Conversely, the possibilistic mean–Yager entropy is over–emphasized due to the definition of its own function, such that it gave an investment pattern of equal weight distribution or approximate average distribution. (b) The results of possibilistic mean–proportional entropy can be said to be the middle status of the portfolios of possibilistic mean–Shannon entropy and possibilistic mean–Yager entropy. This portfolio not only achieves a certain rate of return, but also disperses the risk to some extent. (c) The lines of satisfaction for portfolios derived from different models are approximately U–shaped with the increase in return preference. (d) The possibilistic mean–Shannon entropy model tends to have the highest portfolio satisfaction with the same psychological state of the investor. MDPI 2020-10-04 /pmc/articles/PMC7597257/ /pubmed/33286894 http://dx.doi.org/10.3390/e22101125 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Deng, Xue Lin, Tao Chen, Chuangjie Comparison and Research on Diversified Portfolios with Several Entropy Measures Based on Different Psychological States |
title | Comparison and Research on Diversified Portfolios with Several Entropy Measures Based on Different Psychological States |
title_full | Comparison and Research on Diversified Portfolios with Several Entropy Measures Based on Different Psychological States |
title_fullStr | Comparison and Research on Diversified Portfolios with Several Entropy Measures Based on Different Psychological States |
title_full_unstemmed | Comparison and Research on Diversified Portfolios with Several Entropy Measures Based on Different Psychological States |
title_short | Comparison and Research on Diversified Portfolios with Several Entropy Measures Based on Different Psychological States |
title_sort | comparison and research on diversified portfolios with several entropy measures based on different psychological states |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597257/ https://www.ncbi.nlm.nih.gov/pubmed/33286894 http://dx.doi.org/10.3390/e22101125 |
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