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Stock market efficiency analysis using long spans of Data: A multifractal detrended fluctuation approach

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  • Tiwari, Aviral Kumar
  • Aye, Goodness C.
  • Gupta, Rangan

Abstract

This paper investigates the multifractality and efficiency of stock markets in eight developed (Canada, France, Germany, Italy, Japan, Switzerland, UK and USA) and two emerging (India and South Africa) countries for which long span of data, covering over or nearly a century in each case, is available to avoid sample bias. We employ the Multifractal Detrended Fluctuation Analysis (MF-DFA) based on the generalized Hurst exponents to compare the relative efficiency between short- and long-run horizons and small and large fluctuations. Our findings show that the stock markets are multifractal and mostly long-term persistent. Most markets are more efficient in the long-term than in the short-term. The findings are robust to small and large fluctuations. Overall, although efficiency level varies over time in these markets, the markets are not weakly efficient in both short- and long-term. We draw the economic implications of these results.

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  • Tiwari, Aviral Kumar & Aye, Goodness C. & Gupta, Rangan, 2019. "Stock market efficiency analysis using long spans of Data: A multifractal detrended fluctuation approach," Finance Research Letters, Elsevier, vol. 28(C), pages 398-411.
  • Handle: RePEc:eee:finlet:v:28:y:2019:i:c:p:398-411
    DOI: 10.1016/j.frl.2018.06.012
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    1. Rizvi, Syed Aun R. & Arshad, Shaista, 2017. "Analysis of the efficiency–integration nexus of Japanese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 296-308.
    2. 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.
    3. Cajueiro, Daniel O & Tabak, Benjamin M, 2004. "The Hurst exponent over time: testing the assertion that emerging markets are becoming more efficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(3), pages 521-537.
    4. Aye, Goodness C. & Gil-Alana, Luis A. & Gupta, Rangan & Wohar, Mark E., 2017. "The efficiency of the art market: Evidence from variance ratio tests, linear and nonlinear fractional integration approaches," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 283-294.
    5. Arshad, Shaista & Rizvi, Syed Aun R. & Ghani, Gairuzazmi Mat & Duasa, Jarita, 2016. "Investigating stock market efficiency: A look at OIC member countries," Research in International Business and Finance, Elsevier, vol. 36(C), pages 402-413.
    6. Stakić, Nikola & Jovancai, Ana & Kapor, Predrag, 2016. "The efficiency of the stock market in Serbia," Journal of Policy Modeling, Elsevier, vol. 38(1), pages 156-165.
    7. Vasilios Plakandaras & Rangan Gupta & Luis A. Gil-Alana & Mark E. Wohar, 2019. "Are BRICS exchange rates chaotic?," Applied Economics Letters, Taylor & Francis Journals, vol. 26(13), pages 1104-1110, July.
    8. Hull, Matthew & McGroarty, Frank, 2014. "Do emerging markets become more efficient as they develop? Long memory persistence in equity indices," Emerging Markets Review, Elsevier, vol. 18(C), pages 45-61.
    9. Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "Efficiency of Thai stock markets: Detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 204-209.
    10. Subrata Kumar Mitra & Manojit Chattopadhyay & Parikshit Charan & Jaslene Bawa, 2017. "Identifying periods of market inefficiency for return predictability," Applied Economics Letters, Taylor & Francis Journals, vol. 24(10), pages 668-671, June.
    11. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    12. 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.
    13. 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.
    14. 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.
    15. Sensoy, Ahmet & Aras, Guler & Hacihasanoglu, Erk, 2015. "Predictability dynamics of Islamic and conventional equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 222-248.
    16. 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.
    17. Goodness C. Aye & Tsang Yao Chang & Wen†Yi Chen & Rangan Gupta & Mark Wohar, 2018. "Testing the Efficiency of the Art Market Using Quantile†Based Unit Root Tests with Sharp and Smooth Breaks," Manchester School, University of Manchester, vol. 86(4), pages 488-511, July.
    18. 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.
    19. Rizvi, Syed Aun R. & Dewandaru, Ginanjar & Bacha, Obiyathulla I. & Masih, Mansur, 2014. "An analysis of stock market efficiency: Developed vs Islamic stock markets using MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 86-99.
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    13. 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.
    14. Maciel, Leandro, 2021. "A new approach to portfolio management in the Brazilian equity market: Does assets efficiency level improve performance?," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 38-56.
    15. Oliveira, Alexandre Silva de & Ceretta, Paulo Sergio & Albrecht, Peter, 2023. "Performance comparison of multifractal techniques and artificial neural networks in the construction of investment portfolios," Finance Research Letters, Elsevier, vol. 55(PA).
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    21. Suchetana Sadhukhan & Poulomi Sadhukhan, 2022. "Sector-wise analysis of Indian stock market: Long and short-term risk and stability analysis," Papers 2210.09619, arXiv.org.
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    23. Han, Chenyu & Wang, Yiming & Ning, Ye, 2019. "Comparative analysis of the multifractality and efficiency of exchange markets: Evidence from exchange rates dynamics of major world currencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).

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    More about this item

    Keywords

    Stock market; Efficiency; Short-term; Long-term; Multifractal detrended fluctuation analysis; Hurst exponent;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • 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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