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A combined CFAHP‐FTOPSIS approach for portfolio selection

A combined CFAHP‐FTOPSIS approach for portfolio selection Purpose – Owing to the importance of the portfolio problem in modern financial investment fields, the aim of this paper is to rank and choose suitable stocks in stock markets under vague environment. Design/methodology/approach – Many new principles and methods have been introduced to help the investor to decide which stocks are worth to be chosen. In real word, people prefer to express their attributes by using linguistic terms, so the used data are often imprecise and vague. In this paper, the second method of constrained fuzzy analysis hierarchy process (CFAHP) is used to evaluate the relative weights of the criteria and rank alternatives by fuzzy technique for order preference by similarity to an ideal solution (FTOPSIS). Findings – In this paper, empirical result shows that the proposed method is capable of helping investor to allocate asset in portfolio problems under vague environment. Research limitations/implications – The proposed method gives a new mathematical framework for portfolio selection. Investors can decide the asset allocation by using the combination of CFAHP and FTOPSIS. Practical implications – Besides the benefit of sorting feature, the proposed method can be used to obtain the asset allocation. Social implications – The aim of the portfolio selection theory is to rank and decide the asset allocations. But it is still a difficult task in deciding which assets should be selected under uncertain environment. The proposed method in this paper has been proved to be an efficient method to deal with vague information in decision‐making programs. Originality/value – This study analyzes the effectiveness of the combined method of CFAHP and TOPSIS in portfolio problem. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png China Finance Review International Emerald Publishing

A combined CFAHP‐FTOPSIS approach for portfolio selection

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Publisher
Emerald Publishing
Copyright
Copyright © 2013 Emerald Group Publishing Limited. All rights reserved.
ISSN
2044-1398
DOI
10.1108/CFRI-12-2012-0113
Publisher site
See Article on Publisher Site

Abstract

Purpose – Owing to the importance of the portfolio problem in modern financial investment fields, the aim of this paper is to rank and choose suitable stocks in stock markets under vague environment. Design/methodology/approach – Many new principles and methods have been introduced to help the investor to decide which stocks are worth to be chosen. In real word, people prefer to express their attributes by using linguistic terms, so the used data are often imprecise and vague. In this paper, the second method of constrained fuzzy analysis hierarchy process (CFAHP) is used to evaluate the relative weights of the criteria and rank alternatives by fuzzy technique for order preference by similarity to an ideal solution (FTOPSIS). Findings – In this paper, empirical result shows that the proposed method is capable of helping investor to allocate asset in portfolio problems under vague environment. Research limitations/implications – The proposed method gives a new mathematical framework for portfolio selection. Investors can decide the asset allocation by using the combination of CFAHP and FTOPSIS. Practical implications – Besides the benefit of sorting feature, the proposed method can be used to obtain the asset allocation. Social implications – The aim of the portfolio selection theory is to rank and decide the asset allocations. But it is still a difficult task in deciding which assets should be selected under uncertain environment. The proposed method in this paper has been proved to be an efficient method to deal with vague information in decision‐making programs. Originality/value – This study analyzes the effectiveness of the combined method of CFAHP and TOPSIS in portfolio problem.

Journal

China Finance Review International – Emerald Publishing

Published: Oct 25, 2013

Keywords: Finance; Constrained fuzzy analysis hierarchy process; Fuzzy TOPSIS; Multiple criteria decision making; Stocks selection

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