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Open AccessArticle

Modeling the Performance Indicators of Financial Assets with Neutrosophic Fuzzy Numbers

1
Department of Finance and Banks, University of Oradea, 410087 Oradea, Romania
2
Department of Informatics and Cybernetics, Bucharest University of Economic Studies, 010552 Bucharest, Romania
*
Author to whom correspondence should be addressed.
Symmetry 2019, 11(8), 1021; https://doi.org/10.3390/sym11081021
Received: 18 July 2019 / Revised: 2 August 2019 / Accepted: 5 August 2019 / Published: 7 August 2019
PDF [882 KB, uploaded 7 August 2019]

Abstract

This research sets the basis for modeling the performance indicators of financial assets using triangular neutrosophic fuzzy numbers. This type of number allows for the modeling of financial assets performance indicators by taking into consideration all the possible scenarios of their achievement. The key performance indicators (KPIs) modeled with the help of triangular fuzzy neutrosophic numbers are the return on financial assets, the financial assets risk, and the covariance between financial assets. Thus far, the return on financial assets has been studied using statistical indicators, like the arithmetic and geometric mean, or using the financial risk indicators with the help of the squared deviations from the mean and covariance. These indicators are well known as the basis of portfolio theory. This paper opens the perspective of modeling these three mentioned statistical indicators using triangular neutrosophic fuzzy numbers due to the major advantages they have. The first advantage of the neutrosophic approach is that it includes three possible symmetric scenarios of the KPIs achievement, namely the scenario of certainty, the scenario of non-realization, and the scenario of indecision, in which it cannot be appreciated whether the performance indicators are or are not achieved. The second big advantage is its data series clustering, representing the financial performance indicators by which these scenarios can be delimitated by means of neutrosophic fuzzy numbers in very good, good or weak performance indicators. This clustering is realized by means of the linguistic criteria and measuring the belonging degree to a class of indicators using fuzzy membership functions. The third major advantage is the selection of risk mitigation analysis scenarios and the formation of financial assets’ optimal portfolios.
Keywords: fuzzy numbers; neutrosophic numbers; neutrosophic symmetric scenarios; performance indicators; financial assets fuzzy numbers; neutrosophic numbers; neutrosophic symmetric scenarios; performance indicators; financial assets
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Bolos, M.-I.; Bradea, I.-A.; Delcea, C. Modeling the Performance Indicators of Financial Assets with Neutrosophic Fuzzy Numbers. Symmetry 2019, 11, 1021.

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