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FN-TOPSIS: fuzzy networks for ranking traded equities

Fuzzy systems consisting of networked rule bases, called fuzzy networks, capture various types of imprecision inherent in financial data and in the decision-making processes on them. This paper introduces a novel extension of the Technique for Ordering of Preference by Similarity to Ideal Solution (...

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Main Authors: Yaakob, Abdul Malek, Serguieva, Antoaneta, Gegov, Alexander
Format: Article
Language:English
Published: IEEE 2016
Subjects:
QA Mathematics
Online Access:http://repo.uum.edu.my/22925/1/TFS-2015-0580_FINAL_PAPER.pdf
http://repo.uum.edu.my/22925/
https://doi.org/10.1109/TFUZZ.2016.2555999
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spelling my.uum.repo.229252017-09-18T00:24:00Z http://repo.uum.edu.my/22925/ FN-TOPSIS: fuzzy networks for ranking traded equities Yaakob, Abdul Malek Serguieva, Antoaneta Gegov, Alexander QA Mathematics Fuzzy systems consisting of networked rule bases, called fuzzy networks, capture various types of imprecision inherent in financial data and in the decision-making processes on them. This paper introduces a novel extension of the Technique for Ordering of Preference by Similarity to Ideal Solution (TOPSIS) method and uses fuzzy networks to solve multi criteria decision-making problems where both benefit and cost criteria are presented as subsystems. Thus the decision maker evaluates the performance of each alternative for portfolio optimisation and further observes the performance for both benefit and cost criteria. This approach improves significantly the transparency of the TOPSIS methods, while ensuring high effectiveness in comparison to established approaches. The proposed method is further tested here on portfolio selection problems covering developed and emergent financial markets. The ranking produced by the method is validated using Spearman rho rank correlation. Based on the case study, the proposed method outperforms the existing TOPSIS approaches in term of ranking performance. IEEE 2016-04-21 Article PeerReviewed application/pdf en http://repo.uum.edu.my/22925/1/TFS-2015-0580_FINAL_PAPER.pdf Yaakob, Abdul Malek and Serguieva, Antoaneta and Gegov, Alexander (2016) FN-TOPSIS: fuzzy networks for ranking traded equities. IEEE Transactions on Fuzzy Systems, 25 (2). pp. 315-332. ISSN 1063-6706 https://doi.org/10.1109/TFUZZ.2016.2555999 10.1109/TFUZZ.2016.2555999
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Yaakob, Abdul Malek
Serguieva, Antoaneta
Gegov, Alexander
FN-TOPSIS: fuzzy networks for ranking traded equities
description Fuzzy systems consisting of networked rule bases, called fuzzy networks, capture various types of imprecision inherent in financial data and in the decision-making processes on them. This paper introduces a novel extension of the Technique for Ordering of Preference by Similarity to Ideal Solution (TOPSIS) method and uses fuzzy networks to solve multi criteria decision-making problems where both benefit and cost criteria are presented as subsystems. Thus the decision maker evaluates the performance of each alternative for portfolio optimisation and further observes the performance for both benefit and cost criteria. This approach improves significantly the transparency of the TOPSIS methods, while ensuring high effectiveness in comparison to established approaches. The proposed method is further tested here on portfolio selection problems covering developed and emergent financial markets. The ranking produced by the method is validated using Spearman rho rank correlation. Based on the case study, the proposed method outperforms the existing TOPSIS approaches in term of ranking performance.
format Article
author Yaakob, Abdul Malek
Serguieva, Antoaneta
Gegov, Alexander
author_facet Yaakob, Abdul Malek
Serguieva, Antoaneta
Gegov, Alexander
author_sort Yaakob, Abdul Malek
title FN-TOPSIS: fuzzy networks for ranking traded equities
title_short FN-TOPSIS: fuzzy networks for ranking traded equities
title_full FN-TOPSIS: fuzzy networks for ranking traded equities
title_fullStr FN-TOPSIS: fuzzy networks for ranking traded equities
title_full_unstemmed FN-TOPSIS: fuzzy networks for ranking traded equities
title_sort fn-topsis: fuzzy networks for ranking traded equities
publisher IEEE
publishDate 2016
url http://repo.uum.edu.my/22925/1/TFS-2015-0580_FINAL_PAPER.pdf
http://repo.uum.edu.my/22925/
https://doi.org/10.1109/TFUZZ.2016.2555999
_version_ 1644283651555328000
score 13.211869

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