4.2 Article

A Comparative Performance Evaluation on Bipolar Risks in Emerging Capital Markets Using Fuzzy AHP-TOPSIS and VIKOR Approaches

Journal

INZINERINE EKONOMIKA-ENGINEERING ECONOMICS
Volume 26, Issue 2, Pages 118-129

Publisher

KAUNAS UNIV TECHNOL
DOI: 10.5755/j01.ee.26.2.3591

Keywords

Emerging economies; capital markets; fuzzy; AHP; VIKOR; TOPSIS

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Effective decision making in the financial markets is an important issue for individual and institutional investors in a competitive and risky environment. However, the majority of the investors do not integrate conflict hazards with financial risks in this environment. Accordingly, the best way to select the right market for profitable investments requires the evaluation of bipolar risks covering conflict risk and financial risk using multi-criteria decision-making approaches. The aim of the paper is to discover the comparative performance of emerging markets based on the bipolar risks of the capital markets using hybrid multi-criteria decision analysis methods in economics. Fuzzy AHP-TOPSIS ( FAHP) and Fuzzy AHP-VIKOR methods were used to analyze the financial and conflict risk-based performance levels of selected emerging economies. The seven determinants in this model have been derived from the Advanced and Emerging Market Financial Stress Index and Conflict risk index. The findings demonstrate that the comprehensive performance results of the emerging markets vary based on the competencies of the bipolar risks. The two methods, with different steps for ordering the alternatives, had the same performance results in ranking the emerging economies. The overall performance of each method demonstrates that both methods give coherent results in ranking the E7 economies under the fuzzy environment. The originality of the study is that the FAHP gives more sensitive results than classic AHP method in evaluating the alternatives under a fuzzy environment. In addition, a comparative analysis was applied to evaluate the bipolar risk-based performance results using a hybrid approach under the fuzzy environment.

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