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An analysis of the weak form efficiency, multifractality and long memory of global, regional and European stock markets

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  • Mensi, Walid
  • Tiwari, Aviral Kumar
  • Al-Yahyaee, Khamis Hamed

Abstract

This study investigates the time varying efficiency of five European GIPSI stock markets, compared to global and regional U.S. markets. Using the MF-DFA approach, we show evidence of long memory in both short and long term for all markets. Furthermore, the long memory is more pronounced in the long term than in the short term. Finally, Greece is the highest inefficient market, whatever is the time horizons, while Portugal and Ireland markets are the least inefficient in the short and long term, respectively. Global and regional stock markets are less efficient than GIPSI (except Greece) markets in the short term.

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  • Mensi, Walid & Tiwari, Aviral Kumar & Al-Yahyaee, Khamis Hamed, 2019. "An analysis of the weak form efficiency, multifractality and long memory of global, regional and European stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 168-177.
  • Handle: RePEc:eee:quaeco:v:72:y:2019:i:c:p:168-177
    DOI: 10.1016/j.qref.2018.12.001
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    as
    1. Robert J. Shiller, 1984. "Stock Prices and Social Dynamics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 15(2), pages 457-510.
    2. E. Dockery & M. G. Kavussanos, 1996. "Testing the efficient market hypothesis using panel data, with application to the Athens stock market," Applied Economics Letters, Taylor & Francis Journals, vol. 3(2), pages 121-123.
    3. Mensi, Walid & Tiwari, Aviral Kumar & Yoon, Seong-Min, 2017. "Global financial crisis and weak-form efficiency of Islamic sectoral stock markets: An MF-DFA analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 135-146.
    4. Harvey, Campbell R, 1995. "Predictable Risk and Returns in Emerging Markets," The Review of Financial Studies, Society for Financial Studies, vol. 8(3), pages 773-816.
    5. repec:cii:cepiie:2014-q4-140-60 is not listed on IDEAS
    6. Walid Mensi & Makram Beljid & Shunsuke Managi, 2014. "Structural breaks and the time-varying levels of weak-form efficiency in crude oil markets: Evidence from the Hurst exponent and Shannon entropy methods," International Economics, CEPII research center, issue 140, pages 89-106.
    7. MacDonald, R. & Power, D., 1993. "Stock prices, efficiency and cointegration: The case of the UK," International Review of Economics & Finance, Elsevier, vol. 2(3), pages 251-265.
    8. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-273, April.
    9. Chen, Cheng & Wang, Yudong, 2017. "Understanding the multifractality in portfolio excess returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 346-355.
    10. Di Matteo, T. & Aste, T. & Dacorogna, M.M., 2003. "Scaling behaviors in differently developed markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 183-188.
    11. Thomas Lux, 1996. "Long-term stochastic dependence in financial prices: evidence from the German stock market," Applied Economics Letters, Taylor & Francis Journals, vol. 3(11), pages 701-706.
    12. Ahmad, Wasim & Sehgal, Sanjay & Bhanumurthy, N.R., 2013. "Eurozone crisis and BRIICKS stock markets: Contagion or market interdependence?," Economic Modelling, Elsevier, vol. 33(C), pages 209-225.
    13. Sensoy, Ahmet & Tabak, Benjamin M., 2016. "Dynamic efficiency of stock markets and exchange rates," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 353-371.
    14. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    15. Summers, Lawrence H, 1986. "Does the Stock Market Rationally Reflect Fundamental Values?," Journal of Finance, American Finance Association, vol. 41(3), pages 591-601, July.
    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. Anagnostidis, P. & Varsakelis, C. & Emmanouilides, C.J., 2016. "Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 116-128.
    18. Cajueiro, Daniel O. & Gogas, Periklis & Tabak, Benjamin M., 2009. "Does financial market liberalization increase the degree of market efficiency? The case of the Athens stock exchange," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 50-57, March.
    19. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Yoon, Seong-Min, 2018. "Efficiency, multifractality, and the long-memory property of the Bitcoin market: A comparative analysis with stock, currency, and gold markets," Finance Research Letters, Elsevier, vol. 27(C), pages 228-234.
    20. G. Geoffrey Booth & Gregory Koutmos, 1998. "Volatility and autocorrelation in major European stock markets," The European Journal of Finance, Taylor & Francis Journals, vol. 4(1), pages 61-74.
    21. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    22. John T. Barkoulas & Christopher F. Baum & Nickolaos Travlos, 1996. "Long Memory in the Greek Stock Market," Boston College Working Papers in Economics 356., Boston College Department of Economics.
    23. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    24. Jacobsen, Ben, 1996. "Long term dependence in stock returns," Journal of Empirical Finance, Elsevier, vol. 3(4), pages 393-417, December.
    25. Zhang, Guofu & Li, Jingjing, 2018. "Multifractal analysis of Shanghai and Hong Kong stock markets before and after the connect program," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 611-622.
    26. Katsuragi, Hiroaki, 2000. "Evidence of multi-affinity in the Japanese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 278(1), pages 275-281.
    27. repec:cii:cepiei:2014-q4-140-6 is not listed on IDEAS
    28. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
    29. Zhu, Huijian & Zhang, Weiguo, 2018. "Multifractal property of Chinese stock market in the CSI 800 index based on MF-DFA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 497-503.
    30. Cao, Guangxi & Cao, Jie & Xu, Longbing, 2013. "Asymmetric multifractal scaling behavior in the Chinese stock market: Based on asymmetric MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 797-807.
    31. Wang, Yudong & Liu, Li & Gu, Rongbao, 2009. "Analysis of efficiency for Shenzhen stock market based on multifractal detrended fluctuation analysis," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 271-276, December.
    32. Hasan, Rashid & Mohammad, Salim M., 2015. "Multifractal analysis of Asian markets during 2007–2008 financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 746-761.
    33. Benoit Mandelbrot & Adlai Fisher & Laurent Calvet, 1997. "A Multifractal Model of Asset Returns," Cowles Foundation Discussion Papers 1164, Cowles Foundation for Research in Economics, Yale University.
    34. Cheung, Yin-Wong & Lai, Kon S., 1995. "A search for long memory in international stock market returns," Journal of International Money and Finance, Elsevier, vol. 14(4), pages 597-615, August.
    35. Zunino, L. & Tabak, B.M. & Figliola, A. & Pérez, D.G. & Garavaglia, M. & Rosso, O.A., 2008. "A multifractal approach for stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6558-6566.
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    More about this item

    Keywords

    Stock markets; Multifractality; Long memory; Efficiency; MF-DFA; Hurst exponent;
    All these keywords.

    JEL classification:

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

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