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Revisiting the Long Memory in Global Stock Market Returns: An Empirical Analysis

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  • Ashok Kumar Mishra
  • Sibanjan Mishra

Abstract

We present a multifarious view on the presence of long memory across 33 countries, subsampled as developed, emerging and frontier economies for the period 2000–2018. We employ the classical rescaled range test, and two semi-parametric tests proposed by Geweke Porter-Hudak (1983) and the frequency domain test proposed by Robinson (1995) to decipher the presence of long memory. The results confirm that while there exists no long-range dependence for developed countries, the return series in the emerging and the frontier countries display long memory characteristics. The rationale for such result emerges from market quality parameters such as size, liquidity, trading and settlement mechanism or sound regulatory framework. These results are of importance for the global investor community for asset allocation, risk management and portfolio diversification purposes.

Suggested Citation

  • Ashok Kumar Mishra & Sibanjan Mishra, 2025. "Revisiting the Long Memory in Global Stock Market Returns: An Empirical Analysis," Global Business Review, International Management Institute, vol. 26(1), pages 24-38, February.
    • Handle: RePEc:sae:globus:v:26:y:2025:i:1:p:24-38
    DOI: 10.1177/0972150920966879
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    1. Myung Jig Kim & Charles R. Nelson & Richard Startz, 1991. "Mean Reversion in Stock Prices? A Reappraisal of the Empirical Evidence," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 515-528.
    2. Mensi, Walid & Hammoudeh, Shawkat & Shahzad, Syed Jawad Hussain & Shahbaz, Muhammad, 2017. "Modeling systemic risk and dependence structure between oil and stock markets using a variational mode decomposition-based copula method," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 258-279.
    3. John Elder & Hyun J. Jin, 2009. "Fractional Integration in Commodity Futures Returns," The Financial Review, Eastern Finance Association, vol. 44(4), pages 583-602, November.
    4. Richardson, Matthew & Stock, James H., 1989. "Drawing inferences from statistics based on multiyear asset returns," Journal of Financial Economics, Elsevier, vol. 25(2), pages 323-348, December.
    5. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    6. repec:fth:calaec:13-89 is not listed on IDEAS
    7. Peter Nystrup & Henrik Madsen & Erik Lindström, 2017. "Long Memory of Financial Time Series and Hidden Markov Models with Time‐Varying Parameters," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(8), pages 989-1002, December.
    8. Lu, Yang K. & Perron, Pierre, 2010. "Modeling and forecasting stock return volatility using a random level shift model," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 138-156, January.
    9. Richardson, Matthew, 1993. "Temporary Components of Stock Prices: A Skeptic's View," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 199-207, April.
    10. Assaf, Ata, 2008. "Nonstationarity in real exchange rates using unit root tests with a level shift at unknown time," International Review of Economics & Finance, Elsevier, vol. 17(2), pages 269-278.
    11. Barkoulas, John T & Labys, Walter C & Onochie, Joseph I, 1999. "Long Memory In Futures Prices," The Financial Review, Eastern Finance Association, vol. 34(1), pages 91-100, February.
    12. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    13. 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.
    14. L.A. Gil‐Alana, 2006. "Fractional integration in daily stock market indexes," Review of Financial Economics, John Wiley & Sons, vol. 15(1), pages 28-48.
    15. Lennart Berg & Johan Lyhagen, 1998. "Short and long-run dependence in Swedish stock returns," Applied Financial Economics, Taylor & Francis Journals, vol. 8(4), pages 435-443.
    16. Fernandez, Viviana, 2010. "Commodity futures and market efficiency: A fractional integrated approach," Resources Policy, Elsevier, vol. 35(4), pages 276-282, December.
    17. Marco Corazza & A. G. Malliaris, 2005. "Multi-Fractality in Foreign Currency Markets," World Scientific Book Chapters, in: Economic Uncertainty, Instabilities And Asset Bubbles Selected Essays, chapter 11, pages 151-184, World Scientific Publishing Co. Pte. Ltd..
    18. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    19. Nuno Crato & Bonnie K. Ray, 2000. "Memory in returns and volatilities of futures' contracts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 20(6), pages 525-543, July.
    20. LeRoy, Stephen F, 1989. "Efficient Capital Markets and Martingales," Journal of Economic Literature, American Economic Association, vol. 27(4), pages 1583-1621, December.
    21. Elie Bouri & Luis A. Gil‐Alana & Rangan Gupta & David Roubaud, 2019. "Modelling long memory volatility in the Bitcoin market: Evidence of persistence and structural breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 412-426, January.
    22. Stevenson, Richard A & Bear, Robert M, 1970. "Commodity Futures: Trends or Random Walks?," Journal of Finance, American Finance Association, vol. 25(1), pages 65-81, March.
    23. Phillip, Andrew & Chan, Jennifer & Peiris, Shelton, 2019. "On long memory effects in the volatility measure of Cryptocurrencies," Finance Research Letters, Elsevier, vol. 28(C), pages 95-100.
    24. Aditi Singh & Madhumita Chakraborty, 2017. "Examining Efficiencies of Indian ADRs and their Underlying Stocks," Global Business Review, International Management Institute, vol. 18(1), pages 144-162, February.
    25. Jerry Coakley & Neil Kellard & Jian Wang, 2016. "Commodity futures returns: more memory than you might think!," The European Journal of Finance, Taylor & Francis Journals, vol. 22(14), pages 1457-1483, November.
    26. Jacobsen, Ben, 1996. "Long term dependence in stock returns," Journal of Empirical Finance, Elsevier, vol. 3(4), pages 393-417, December.
    27. Benoit B. Mandelbrot, 1972. "Statistical Methodology for Nonperiodic Cycles: From the Covariance To R/S Analysis," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 3, pages 259-290, National Bureau of Economic Research, Inc.
    28. Guglielmo Maria Caporale & Luis Gil-Alana & Alex Plastun, 2018. "Short-Term Price Overreactions: Identification, Testing, Exploitation," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 913-940, April.
    29. Poterba, James M. & Summers, Lawrence H., 1988. "Mean reversion in stock prices : Evidence and Implications," Journal of Financial Economics, Elsevier, vol. 22(1), pages 27-59, October.
    30. Barkoulas, John T. & Baum, Christopher F., 1996. "Long-term dependence in stock returns," Economics Letters, Elsevier, vol. 53(3), pages 253-259, December.
    31. Mirko Abbritti & Luis A. Gil-Alana & Yuliya Lovcha & Antonio Moreno, 2016. "Term Structure Persistence," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 331-352.
    32. Dusak, Katherine, 1973. "Futures Trading and Investor Returns: An Investigation of Commodity Market Risk Premiums," Journal of Political Economy, University of Chicago Press, vol. 81(6), pages 1387-1406, Nov.-Dec..
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