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Is the efficiency of stock market correlated with multifractality? An evidence from the Shanghai stock market

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  • Gu, Rongbao
  • Shao, Yanmin
  • Wang, Qingnan
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    Abstract

    In this paper, we propose an efficiency index and multifractality degree for financial markets, and investigate the dynamics of the relationship between the two indices for the Shanghai stock market employing the technique of rolling window. By using the DCCA cross-correlation coefficient, we find that, for the Shanghai stock market, the increase in the degree of market multifractality can lead to a lower degree of market efficiency before the equity division reforms, whereas it can result in a lower degree of market efficiency in the short-term and a higher degree of market efficiency in the long-term after the equity division reforms. This finding reflects the process of development of the Shanghai stock market and also provides strong evidence which supports Liu’s argument that the increase in the degree of market complexity can improve the market efficiency Liu (2009) [1].

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    Bibliographic Info

    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 392 (2013)
    Issue (Month): 2 ()
    Pages: 361-370

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    Handle: RePEc:eee:phsmap:v:392:y:2013:i:2:p:361-370

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    Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

    Related research

    Keywords: Stock market; Efficiency index; Multifractality degree; DCCA cross-correlation coefficient;

    References

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    1. Cajueiro, Daniel O. & Tabak, Benjamin M., 2004. "Evidence of long range dependence in Asian equity markets: the role of liquidity and market restrictions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 342(3), pages 656-664.
    2. Wang, Yudong & Wei, Yu & Wu, Chongfeng, 2010. "Auto-correlated behavior of WTI crude oil volatilities: A multiscale perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5759-5768.
    3. Cajueiro, Daniel O. & Tabak, Benjamin M., 2006. "Testing for predictability in equity returns for European transition markets," Economic Systems, Elsevier, vol. 30(1), pages 56-78, March.
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    5. Zebende, G.F., 2011. "DCCA cross-correlation coefficient: Quantifying level of cross-correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 614-618.
    6. Alvarez-Ramirez, Jose & Alvarez, Jesus & Rodriguez, Eduardo, 2008. "Short-term predictability of crude oil markets: A detrended fluctuation analysis approach," Energy Economics, Elsevier, vol. 30(5), pages 2645-2656, September.
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    9. Tabak, Benjamin M. & Cajueiro, Daniel O., 2007. "Are the crude oil markets becoming weakly efficient over time? A test for time-varying long-range dependence in prices and volatility," Energy Economics, Elsevier, vol. 29(1), pages 28-36, January.
    10. 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.
    11. 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 225-36, August.
    12. 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.
    13. Eom, Cheoljun & Choi, Sunghoon & Oh, Gabjin & Jung, Woo-Sung, 2008. "Hurst exponent and prediction based on weak-form efficient market hypothesis of stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(18), pages 4630-4636.
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    Cited by:
    1. Ma, Feng & Wei, Yu & Huang, Dengshi & Zhao, Lin, 2013. "Cross-correlations between West Texas Intermediate crude oil and the stock markets of the BRIC," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5356-5368.
    2. Machado Filho, A. & da Silva, M.F. & Zebende, G.F., 2014. "Autocorrelation and cross-correlation in time series of homicide and attempted homicide," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 12-19.

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