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Efficient or adaptive markets? Evidence from major stock markets using very long run historic data

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  • Urquhart, Andrew
  • Hudson, Robert

Abstract

This paper empirically investigates the Adaptive Market Hypothesis (AMH) in three of the most established stock markets in the world; the US, UK and Japanese markets using very long run data. Daily data is divided into five-yearly subsamples and subjected to linear and nonlinear tests to determine how the independence of stock returns has behaved over time. Further, a five-type classification is proposed to distinguish the differing behaviour of stock returns. The results from the linear autocorrelation, runs and variance ratio tests reveal that each market shows evidence of being an adaptive market, with returns going through periods of independence and dependence. However, the results from the nonlinear tests show strong dependence for every subsample in each market, although the magnitude of dependence varies quite considerably. Thus the linear dependence of stock returns varies over time but nonlinear dependence is strong throughout. Our overall results suggest that the AMH provides a better description of the behaviour of stock returns than the Efficient Market Hypothesis.

Suggested Citation

  • Urquhart, Andrew & Hudson, Robert, 2013. "Efficient or adaptive markets? Evidence from major stock markets using very long run historic data," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 130-142.
  • Handle: RePEc:eee:finana:v:28:y:2013:i:c:p:130-142
    DOI: 10.1016/j.irfa.2013.03.005
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    1. repec:eee:intfin:v:51:y:2017:i:c:p:190-208 is not listed on IDEAS
    2. Aviral Kumar Tiwari & Rangan Gupta & Stelios Bekiros, 2016. "Chaos in G7 Stock Markets using Over One Century of Data: A Note," Working Papers 201678, University of Pretoria, Department of Economics.
    3. Urquhart, Andrew & Gebka, Bartosz & Hudson, Robert, 2015. "How exactly do markets adapt? Evidence from the moving average rule in three developed markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 127-147.
    4. Huai-Long Shi & Zhi-Qiang Jiang & Wei-Xing Zhou, 2016. "Time-varying return predictability in the Chinese stock market," Papers 1611.04090, arXiv.org.
    5. Hiremath, Gourishankar S & Kumari, Jyoti, 2014. "Stock returns predictability and the adaptive market hypothesis in emerging markets: evidence from India," MPRA Paper 58378, University Library of Munich, Germany.
    6. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
    7. Jasman Tuyon & Zamri Ahmada, 2016. "Behavioural finance perspectives on Malaysian stock market efficiency," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 16(1), pages 43-61, March.
    8. repec:bla:ecorec:v:93:y:2017:i::p:38-56 is not listed on IDEAS
    9. repec:ove:journl:aid:11556 is not listed on IDEAS
    10. Hiremath, Gourishankar S & Kumari, Jyoti, 2013. "Stock Returns Predictability and the Adaptive Market Hypothesis: Evidence from India," MPRA Paper 52581, University Library of Munich, Germany.
    11. 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.
    12. repec:eee:phsmap:v:483:y:2017:i:c:p:182-192 is not listed on IDEAS
    13. Alda, Mercedes, 2017. "The relationship between pension funds and the stock market: Does the aging population of Europe affect it?," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 83-97.
    14. Urquhart, Andrew & McGroarty, Frank, 2014. "Calendar effects, market conditions and the Adaptive Market Hypothesis: Evidence from long-run U.S. data," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 154-166.
    15. Mirzaee Ghazani, Majid & Khalili Araghi, Mansour, 2014. "Evaluation of the adaptive market hypothesis as an evolutionary perspective on market efficiency: Evidence from the Tehran stock exchange," Research in International Business and Finance, Elsevier, vol. 32(C), pages 50-59.
    16. Aumeboonsuke, Vesarach & Dryver, Arthur L., 2014. "The importance of using a test of weak-form market efficiency that does not require investigating the data first," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 350-357.
    17. Semei Coronado-Ram'irez & Pedro Celso-Arellano & Omar Rojas, 2014. "Adaptive Market Efficiency of Agricultural Commodity Futures Contracts," Papers 1412.8017, arXiv.org, revised Mar 2015.
    18. Lanouar Charfeddine & Karim Ben Khediri & Goodness C. Aye & Rangan Gupta, 2017. "Time-Varying Efficiency of Developed and Emerging Bond Markets: Evidence from Long-Spans of Historical Data," Working Papers 201771, University of Pretoria, Department of Economics.
    19. Urquhart, Andrew & McGroarty, Frank, 2016. "Are stock markets really efficient? Evidence of the adaptive market hypothesis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 39-49.
    20. repec:eee:pacfin:v:44:y:2017:i:c:p:97-112 is not listed on IDEAS

    More about this item

    Keywords

    Adaptive markets hypothesis; Market efficiency; Nonlinear tests; US stock market; UK stock market;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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