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Do emerging markets become more efficient as they develop? Long memory persistence in equity indices

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  • Hull, Matthew
  • McGroarty, Frank

Abstract

It seems reasonable to expect financial market efficiency to be related to the economic development level. We study a 16year sample, covering 22 countries. The Hurst–Mandelbrot–Wallis rescaled range is our efficiency measure, which we apply to returns and volatility. We find strong evidence of long memory persistence in volatility over time, which is unsurprising. However, unlike previous researchers, we could not find evidence of rescaled ranges trending down over time. However, we introduce an alternative measure of economic development, namely, whether FTSE (2011) classify an emerging market as ‘advanced’ or ‘secondary’. This measure shows greater efficiency in returns and volatility for ‘advanced’ emerging markets.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ememar:v:18:y:2014:i:c:p:45-61
    DOI: 10.1016/j.ememar.2013.11.001
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    as
    1. Geert Bekaert & Campbell R. Harvey, 2000. "Foreign Speculators and Emerging Equity Markets," Journal of Finance, American Finance Association, vol. 55(2), pages 565-613, April.
    2. GabJin Oh & Cheol-Jun Um & Seunghwan Kim, 2006. "Statistical Properties of the Returns of Stock Prices of International Markets," Papers physics/0601126, arXiv.org.
    3. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
    4. Kim, Jae H. & Shamsuddin, Abul, 2008. "Are Asian stock markets efficient? Evidence from new multiple variance ratio tests," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 518-532, June.
    5. Dilip Abreu & Markus K. Brunnermeier, 2003. "Bubbles and Crashes," Econometrica, Econometric Society, vol. 71(1), pages 173-204, January.
    6. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    7. Yin-Wong Cheung & Menzie D. Chinn & Ian W. Marsh, 2004. "How do UK-based foreign exchange dealers think their market operates?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 9(4), pages 289-306.
    8. 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.
    9. Mandelbrot, Benoit B, 1971. "When Can Price Be Arbitraged Efficiently? A Limit to the Validity of the Random Walk and Martingale Models," The Review of Economics and Statistics, MIT Press, vol. 53(3), pages 225-236, August.
    10. Jussi Tolvi, 2003. "Long memory and outliers in stock market returns," Applied Financial Economics, Taylor & Francis Journals, vol. 13(7), pages 495-502.
    11. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    12. 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.
    13. Bentes, Sónia R. & Menezes, Rui & Mendes, Diana A., 2008. "Long memory and volatility clustering: Is the empirical evidence consistent across stock markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3826-3830.
    14. 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.
    15. Suk-Joong Kim & Eliza Wu, 2018. "Sovereign Credit Ratings, Capital Flows and Financial Sector Development in Emerging Markets," World Scientific Book Chapters, in: Information Spillovers and Market Integration in International Finance Empirical Analyses, chapter 13, pages 431-466, World Scientific Publishing Co. Pte. Ltd..
    16. 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.
    17. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    18. Perron, Pierre & Qu, Zhongjun, 2010. "Long-Memory and Level Shifts in the Volatility of Stock Market Return Indices," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 275-290.
    19. Cătălin Stărică & Clive Granger, 2005. "Nonstationarities in Stock Returns," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 503-522, August.
    20. Crato, Nuno & de Lima, Pedro J. F., 1994. "Long-range dependence in the conditional variance of stock returns," Economics Letters, Elsevier, vol. 45(3), pages 281-285.
    21. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
    22. Lillo Fabrizio & Farmer J. Doyne, 2004. "The Long Memory of the Efficient Market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(3), pages 1-35, September.
    23. Liu, Ming, 2000. "Modeling long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 99(1), pages 139-171, November.
    24. Bollerslev, Tim & Wright, Jonathan H., 2000. "Semiparametric estimation of long-memory volatility dependencies: The role of high-frequency data," Journal of Econometrics, Elsevier, vol. 98(1), pages 81-106, September.
    25. Kristoufek, Ladislav, 2012. "How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4252-4260.
    26. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101.
    27. Epaminondas Panas, 2001. "Estimating fractal dimension using stable distributions and exploring long memory through ARFIMA models in Athens Stock Exchange," Applied Financial Economics, Taylor & Francis Journals, vol. 11(4), pages 395-402.
    28. Barkoulas, John T. & Baum, Christopher F., 1996. "Long-term dependence in stock returns," Economics Letters, Elsevier, vol. 53(3), pages 253-259, December.
    29. Sadique, Shibley & Silvapulle, Param, 2001. "Long-Term Memory in Stock Market Returns: International Evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 6(1), pages 59-67, January.
    30. Batten, Jonathan A. & Ellis, Craig A. & Hogan, Warren P., 2005. "Decomposing intraday dependence in currency markets: evidence from the AUD/USD spot market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 352(2), pages 558-572.
    31. Pilar Grau-Carles, 2005. "Tests of Long Memory: A Bootstrap Approach," Computational Economics, Springer;Society for Computational Economics, vol. 25(1), pages 103-113, February.
    32. Costa, Rogério L. & Vasconcelos, G.L., 2003. "Long-range correlations and nonstationarity in the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 329(1), pages 231-248.
    33. R. L. Costa & G. L. Vasconcelos, 2003. "Long-range correlations and nonstationarity in the Brazilian stock market," Papers cond-mat/0302342, arXiv.org.
    34. Rajan, Raghuram G. & Zingales, Luigi, 2003. "The great reversals: the politics of financial development in the twentieth century," Journal of Financial Economics, Elsevier, vol. 69(1), pages 5-50, July.
    35. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    36. Victor Chow, K. & Denning, Karen C. & Ferris, Stephen & Noronha, Gregory, 1995. "Long-term and short-term price memory in the stock market," Economics Letters, Elsevier, vol. 49(3), pages 287-293, September.
    37. 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.
    38. 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.
    39. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.
    40. Olan Henry, 2002. "Long memory in stock returns: some international evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 12(10), pages 725-729.
    41. 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.
    42. Chan, Kalok & Hameed, Allaudeen, 2006. "Stock price synchronicity and analyst coverage in emerging markets," Journal of Financial Economics, Elsevier, vol. 80(1), pages 115-147, April.
    43. Jacobsen, Ben & Dannenburg, Dennis, 2003. "Volatility clustering in monthly stock returns," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 479-503, September.
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