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.

中文翻译：

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一种基于模糊集理论分析金融市场效率的新方法


本文介绍了模糊市场效率测量 （FMIM），这是一种利用模糊集理论评估金融市场效率的新方法。FMIM 通过将效率低下建模为三角模糊数来解决传统指标的局限性，从而捕获金融市场固有的不确定性和非线性动态。该方法将模糊回归与三角隶属函数相结合，并采用简单的优化框架进行参数估计。对不同资产类别（包括股票、大宗商品和加密货币）的实证分析表明了 FMIM 的稳健性，尤其是在市场不确定性加剧的时期，例如 2008 年金融危机和 2020 年 COVID-19 大流行。FMIM 不仅可以检测湍流过程中明显的效率低下，还可以对稳定条件下的细微变化提供细致入微的见解。通过引入灵活和适应性的框架，FMIM 为研究人员、分析师和政策制定者提供了一个强大的工具，以促进对复杂金融环境中效率低下动态的理解。