A novel method for analyzing financial market efficiency through fuzzy set theory

This paper introduces the Fuzzy Market Inefficiency Measure (FMIM), a novel approach for evaluating financial market efficiency by leveraging fuzzy set theory. FMIM addresses limitations in traditional metrics by modeling inefficiency as a triangular fuzzy number, capturing the inherent uncertainties and non-linear dynamics of financial markets. The methodology incorporates fuzzy regression with triangular membership functions and employs a straightforward optimization framework for parameter estimation. Empirical analysis across diverse asset classes—including equities, commodities, and cryptocurrencies—demonstrates FMIM's robustness, particularly during periods of heightened market uncertainty, such as the 2008 financial crisis and the 2020 COVID-19 pandemic. FMIM not only detects pronounced inefficiencies during turbulence but also provides nuanced insights into subtle variations under stable conditions. By introducing a flexible and adaptive framework, FMIM offers researchers, analysts, and policymakers a powerful tool for advancing the understanding of inefficiency dynamics in complex financial environments.