An integrated model for evaluating the risk factors of crypto-currencies under fuzzy environment

While blockchain technology and cryptocurrencies offer numerous advantages and innovations, it is essential to be aware that their implementation processes are fraught with a myriad of risk factors. A study in which risks in cryptocurrencies are evaluated using quantitative data is an important need for investors and academics. As far as it is known from the literature, although blockchain technology is frequently used in different fields, there is no study examining the risks in cryptocurrencies with fuzzy set theory. Unlike the common return and security focused studies in the literature, a comprehensive risk factor determination has been made by evaluating a total of 21 criteria that directly and indirectly affect this virtual currency. Within the study, investors have been provided with insights into the alternatives relevant to the risks under determined through the utilization of an alternative set of considerable magnitude, uncommonly encountered in the existing literature. Considering the complexity and uncertainty of the problem, an Analytic Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution method integrated with Spherical fuzzy sets have been used. The most preferred cryptocurrencies have been evaluated according to a set of criteria ranging from their financial structures to their environmental impacts. Ethereum, which stands out with its blockchain structure, has been the best choice. Tether, designed to provide a stable price point, and Dogecoin, designed as a payment system, appeared to be the worst ones.