Cryptocurrency investment decision-making: A hyperbolic fuzzy MCDM approach

Abstract

Cryptocurrencies have grown as one of the significant technological advancements in today’s digital age. Investors all around the globe have shown a growing interest in cryptocurrencies in recent times because of their potential to bring huge profits. This paper tries to determine the best cryptocurrencies for investment by evaluating six leading cryptocurrencies, selected based on market capitalization and global relevance. Cryptocurrencies are ranked using six important evaluation criteria using two multi-criteria decision-making (MCDM) techniques: Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), employed under hyperbolic fuzzy set (HyFS) settings. In addition, a closeness coefficient is introduced in TOPSIS method to enhance decision precision and sensitivity. Although the results obtained by the two methods are very close, investors would not want to have any doubt about the investment they are considering. The rankings from each procedure are then combined using a social choice function: the Borda Count method. Combining these approaches, the findings indicate that Bitcoin and Ethereum emerge as the most favorable cryptocurrencies for investment among the selected alternatives. To ensure the consistency of the obtained rankings, statistical analyses were conducted. Spearman’s rank correlation coefficient (ρ), Kendall’s tau (τ), and the Wilcoxon Signed-Rank Test were utilized to measure the degree of agreement between the rankings generated by Hyperbolic Fuzzy TOPSIS and Hyperbolic Fuzzy VIKOR. Combining these approaches to create a trustworthy decision-making model for cryptocurrency selection makes this work novel.