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Towards a new framework on efficient markets

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  • Verheyden, Tim
  • De Moor, Lieven
  • Van den Bossche, Filip

Abstract

Academic research on the efficiency of financial markets goes back several decades. Empirical evidence is mixed and academia is torn between two opposing convictions: the efficient market hypothesis (EMH) vs. behavioural finance. The recent Nobel Prize awarded to scholars from both sides of the debate confirms the stalemate. We apply multiple state-of-the-art efficiency tests in rolling windows of one year to leading global stock market indices to test the adaptive markets hypothesis (AMH), a proposed reconciling framework. We find the idea of dynamic and time-variant efficiency to be valid. Also the theoretical pattern of efficiency predicted by the AMH is in line with our results. Furthermore, we find that the effect of the most recent financial crisis on weak form market efficiency is most prominent on the U.S. stock market. The European and Japanese markets appear more consistently efficient over the course of the last 15 years.

Suggested Citation

  • Verheyden, Tim & De Moor, Lieven & Van den Bossche, Filip, 2015. "Towards a new framework on efficient markets," Research in International Business and Finance, Elsevier, vol. 34(C), pages 294-308.
    • Handle: RePEc:eee:riibaf:v:34:y:2015:i:c:p:294-308
    DOI: 10.1016/j.ribaf.2015.02.007
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    5. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "Adaptive Markets Hypothesis for Islamic Stock Portfolios: Evidence from Dow Jones Size and Sector-Indices," Post-Print hal-01526483, HAL.
    6. Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu & Yoon, Seong-Min, 2017. "A multifractal detrended fluctuation analysis of financial market efficiency: Comparison using Dow Jones sector ETF indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 182-192.
    7. Hill, Jonathan B. & Motegi, Kaiji, 2019. "Testing the white noise hypothesis of stock returns," Economic Modelling, Elsevier, vol. 76(C), pages 231-242.
    8. 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.
    9. Türker Şimşek & Oktay Özkan, 2021. "The Time-Varying Impact of Covid-19 on Stock Returns: Evidence on Developed Countries from a Bootstrap Rolling Window Causality Method," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 5(SI), pages 1-12.
    10. Oktay Ozkan, 2020. "Time-varying return predictability and adaptive markets hypothesis: Evidence on MIST countries from a novel wild bootstrap likelihood ratio approach," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 34(2), pages 101-113.
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