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An Entropy Approach to Measure the Dynamic Stock Market Efficiency
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An Entropy Approach to Measure the Dynamic Stock Market Efficiency
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An Entropy Approach to Measure the Dynamic Stock Market Efficiency
An Entropy Approach to Measure the Dynamic Stock Market Efficiency
Journal Article

An Entropy Approach to Measure the Dynamic Stock Market Efficiency

2022
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Overview
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.