IDEAS home Printed from https://ideas.repec.org/a/eee/quaeco/v72y2019icp168-177.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S106297691830156X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.qref.2018.12.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    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. repec:cii:cepiei:2014-q4-140-6 is not listed on IDEAS
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. Jacobsen, Ben, 1996. "Long term dependence in stock returns," Journal of Empirical Finance, Elsevier, vol. 3(4), pages 393-417, December.
    33. 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.
    34. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Duan, Kun & Li, Zeming & Urquhart, Andrew & Ye, Jinqiang, 2021. "Dynamic efficiency and arbitrage potential in Bitcoin: A long-memory approach," International Review of Financial Analysis, Elsevier, vol. 75(C).
    2. Haider Ali & Faheem Aslam & Paulo Ferreira, 2021. "Modeling Dynamic Multifractal Efficiency of US Electricity Market," Energies, MDPI, vol. 14(19), pages 1-16, September.
    3. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    4. Yao, Can-Zhong & Mo, Yi-Na & Zhang, Ze-Kun, 2021. "A study of the efficiency of the Chinese clean energy stock market and its correlation with the crude oil market based on an asymmetric multifractal scaling behavior analysis," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    5. Shrestha, Keshab & Naysary, Babak & Philip, Sheena Sara Suresh, 2023. "Fintech market efficiency: A multifractal detrended fluctuation analysis," Finance Research Letters, Elsevier, vol. 54(C).
    6. Adekoya, Oluwasegun B. & Asl, Mahdi Ghaemi & Oliyide, Johnson A. & Izadi, Parviz, 2023. "Multifractality and cross-correlation between the crude oil and the European and non-European stock markets during the Russia-Ukraine war," Resources Policy, Elsevier, vol. 80(C).
    7. Mensi, Walid & Sensoy, Ahmet & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Pricing efficiency and asymmetric multifractality of major asset classes before and during COVID-19 crisis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    8. Duan, Kun & Gao, Yang & Mishra, Tapas & Satchell, Stephen, 2023. "Efficiency dynamics across segmented Bitcoin Markets: Evidence from a decomposition strategy," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    9. Mensi, Walid & Lee, Yun-Jung & Vinh Vo, Xuan & Yoon, Seong-Min, 2021. "Does oil price variability affect the long memory and weak form efficiency of stock markets in top oil producers and oil Consumers? Evidence from an asymmetric MF-DFA approach," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Choi, Sun-Yong, 2021. "Analysis of stock market efficiency during crisis periods in the US stock market: Differences between the global financial crisis and COVID-19 pandemic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    2. Deniz Erer & Elif Erer & Selim Güngör, 2023. "The aggregate and sectoral time-varying market efficiency during crisis periods in Turkey: a comparative analysis with COVID-19 outbreak and the global financial crisis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-25, December.
    3. 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.
    4. Chenyu Han & Yiming Wang & Yingying Xu, 2019. "Efficiency and Multifractality Analysis of the Chinese Stock Market: Evidence from Stock Indices before and after the 2015 Stock Market Crash," Sustainability, MDPI, vol. 11(6), pages 1-15, March.
    5. Mensi, Walid & Hamdi, Atef & Yoon, Seong-Min, 2018. "Modelling multifractality and efficiency of GCC stock markets using the MF-DFA approach: A comparative analysis of global, regional and Islamic markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1107-1116.
    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. Diniz-Maganini, Natalia & Diniz, Eduardo H. & Rasheed, Abdul A., 2021. "Bitcoin’s price efficiency and safe haven properties during the COVID-19 pandemic: A comparison," Research in International Business and Finance, Elsevier, vol. 58(C).
    8. Stosic, Dusan & Stosic, Darko & de Mattos Neto, Paulo S.G. & Stosic, Tatijana, 2019. "Multifractal characterization of Brazilian market sectors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 956-964.
    9. Ali, Sajid & Shahzad, Syed Jawad Hussain & Raza, Naveed & Al-Yahyaee, Khamis Hamed, 2018. "Stock market efficiency: A comparative analysis of Islamic and conventional stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 139-153.
    10. Diniz-Maganini, Natalia & Rasheed, Abdul A. & Sheng, Hsia Hua, 2023. "Price efficiency of the foreign exchange rates of BRICS countries: A comparative analysis," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(1).
    11. A. Sensoy & Benjamin M. Tabak, 2013. "How much random does European Union walk? A time-varying long memory analysis," Working Papers Series 342, Central Bank of Brazil, Research Department.
    12. Diniz-Maganini, Natalia & Rasheed, Abdul A. & Sheng, Hsia Hua, 2021. "Exchange rate regimes and price efficiency: Empirical examination of the impact of financial crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    13. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    14. Lee, Min-Jae & Choi, Sun-Yong, 2024. "Insights into the dynamics of market efficiency spillover of financial assets in different equity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 641(C).
    15. 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.
    16. Lee, Minhyuk & Song, Jae Wook & Kim, Sondo & Chang, Woojin, 2018. "Asymmetric market efficiency using the index-based asymmetric-MFDFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1278-1294.
    17. Yao, Can-Zhong & Mo, Yi-Na & Zhang, Ze-Kun, 2021. "A study of the efficiency of the Chinese clean energy stock market and its correlation with the crude oil market based on an asymmetric multifractal scaling behavior analysis," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    18. Mensi, Walid & Hamdi, Atef & Shahzad, Syed Jawad Hussain & Shafiullah, Muhammad & Al-Yahyaee, Khamis Hamed, 2018. "Modeling cross-correlations and efficiency of Islamic and conventional banks from Saudi Arabia: Evidence from MF-DFA and MF-DXA approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 576-589.
    19. 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.
    20. Li, Songsong & Xu, Nan & Hui, Xiaofeng, 2020. "International investors and the multifractality property: Evidence from accessible and inaccessible market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:quaeco:v:72:y:2019:i:c:p:168-177. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620167 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.