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<p>Stock market efficiency is central to informed investment decisions and risk management. This study evaluates the efficiency of 78 international stock markets using daily data from December 31, 2021, to February 27, 2025. Four key indicators namely Return Autocorrelation, Volatility, Market Liquidity, and Long-term Memory are measured to capture different dimensions of inefficiency. Return Autocorrelation is estimated using an autoregressive model, volatility through the GARCH framework, liquidity via the bid–ask spread estimator, and long-term memory using the Hurst exponent. These indicators are subsequently aggregated through Principal Component Analysis to construct a Broad-Based Market Inefficiency Index, offering a consolidated measure of the overall inefficiency level of each market. Index score ranges from 0.11 to 0.84, indicating substantial cross-country variation in market functioning, informational quality, and microstructural behaviour. In addition, the study applies Fuzzy C-Means clustering using the four indicators of efficiency. The result indicates three clusters with 40 markets in cluster 1 representing moderate efficiency, 19 markets in cluster 2 highly efficiency, and 19 markets in cluster 3 representing low efficiency. The findings show that highly efficient markets exhibit low return autocorrelation, stable volatility, narrow bid–ask spreads, and weak long-term memory, whereas less efficient markets display persistent volatility clustering and stronger memory effects. By integrating a composite inefficiency index with indicator-based clustering, the study provides a comprehensive and coherent assessment of global stock market efficiency, offering valuable insights for both investors seeking informed portfolio allocation and policymakers aiming to improve market performance.</p>

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A Multidimensional Approach To the Measurement and Classification of Stock Market Inefficiency Across Economies

  • 期刊论文

  • 发表日期：

    2026年2月2日

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  • Amlan Alok Pradhan,
  • Soumyaranjan Jena,
  • Sayel Basel

摘要

Stock market efficiency is central to informed investment decisions and risk management. This study evaluates the efficiency of 78 international stock markets using daily data from December 31, 2021, to February 27, 2025. Four key indicators namely Return Autocorrelation, Volatility, Market Liquidity, and Long-term Memory are measured to capture different dimensions of inefficiency. Return Autocorrelation is estimated using an autoregressive model, volatility through the GARCH framework, liquidity via the bid–ask spread estimator, and long-term memory using the Hurst exponent. These indicators are subsequently aggregated through Principal Component Analysis to construct a Broad-Based Market Inefficiency Index, offering a consolidated measure of the overall inefficiency level of each market. Index score ranges from 0.11 to 0.84, indicating substantial cross-country variation in market functioning, informational quality, and microstructural behaviour. In addition, the study applies Fuzzy C-Means clustering using the four indicators of efficiency. The result indicates three clusters with 40 markets in cluster 1 representing moderate efficiency, 19 markets in cluster 2 highly efficiency, and 19 markets in cluster 3 representing low efficiency. The findings show that highly efficient markets exhibit low return autocorrelation, stable volatility, narrow bid–ask spreads, and weak long-term memory, whereas less efficient markets display persistent volatility clustering and stronger memory effects. By integrating a composite inefficiency index with indicator-based clustering, the study provides a comprehensive and coherent assessment of global stock market efficiency, offering valuable insights for both investors seeking informed portfolio allocation and policymakers aiming to improve market performance.