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An Entropy Approach to Measure the Dynamic Stock Market Efficiency

Author

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  • Subhamitra Patra

    (VIT Business School, Vellore Institute of Technology)

  • Gourishankar S. Hiremath

    (Indian Institute of Technology Kharagpur)

Abstract

We measure stock market efficiency by drawing the comprehensive sample from Asia, Europe, Africa, North–South America, and Pacific Ocean regions and rank the cross-regional stock markets according to their level of informational efficiency. The study period spans from January 1, 1994, to August 3, 2017. We employ the approximate entropy approach and find that stock market efficiency evolves over the period. The degree and nature of evolution vary across regions and the development stage of the markets. The global, regional, domestic economic, and non-economic factors influence the adaptive nature of the stock markets. The emerging stock markets have improved efficiency by financial liberalization policy but are adversely affected by global shocks. The estimates validate the relevance of the adaptive market framework to describe the rejection of random walk without excess returns. The results suggest the growing presence of technical analysis and active portfolio managers. The emerging markets in Asia hold policy lessons for their peers. The findings suggest that global investors need to overcome the homogeneity bias as returns opportunities exist within the region and types of markets.

Suggested Citation

  • Subhamitra Patra & Gourishankar S. Hiremath, 2022. "An Entropy Approach to Measure the Dynamic Stock Market Efficiency," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(2), pages 337-377, June.
    • Handle: RePEc:spr:jqecon:v:20:y:2022:i:2:d:10.1007_s40953-022-00295-x
    DOI: 10.1007/s40953-022-00295-x
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    Cited by:

    1. Samuel Tabot ENOW, 2023. "A Non-linear Dependency Test for Market Efficiency: Evidence from International Stock Markets," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 7(1), pages 1-12.
    2. Radhika Prosad Datta, 2023. "Leveraging Sample Entropy for Enhanced Volatility Measurement and Prediction in International Oil Price Returns," Papers 2312.12788, arXiv.org.

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    More about this item

    Keywords

    EMH; Entropy; AMH; Adaptive markets; Financial crises; Portfolio management;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G4 - Financial Economics - - Behavioral Finance
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G01 - Financial Economics - - General - - - Financial Crises

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