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Analysis of efficiency for Shenzhen stock market: Evidence from the source of multifractality

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  • Liu, Li
  • Wang, Yudong
  • Wan, Jieqiu

Abstract

This paper extends the work in Wang, Liu and Gu (2009) [Analysis of efficiency for Shenzhen stock market based on multifractal detrended fluctuation analysis. International Review of Financial Analysis, 18, 271-276] by investigating the dynamics of two main sources of multifractality over time. Using multiscale detrended fluctuation analysis, we find that the medium-term and long-term auto-correlations of Shenzhen stock market became weaker and weaker over time but the degrees of short-term efficiency seemed to do not change. Evidence shows that the degree of the fat-tail distribution of the market returns abruptly decreased after the price-limited reform. After the reform, the degree of fat-tail distribution seemed to run an upward trend but it went down finally. From the contributions of two sources, we conclude that the multifractality generally displayed a downward trend indicating an upward trend of efficiency only in the medium- and long-term which further confirms the results in Wang, Liu and Gu (2009). We find that some abnormal "jumps" in the evolutions of short-term and medium-term correlation behaviors can be related to the abruptly exogenous events. Some problems about efficiency and operations of Shenzhen market are also discussed at last.

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  • Liu, Li & Wang, Yudong & Wan, Jieqiu, 2010. "Analysis of efficiency for Shenzhen stock market: Evidence from the source of multifractality," International Review of Financial Analysis, Elsevier, vol. 19(4), pages 237-241, September.
    • Handle: RePEc:eee:finana:v:19:y:2010:i:4:p:237-241
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    1. Norouzzadeh, P. & Rahmani, B., 2006. "A multifractal detrended fluctuation description of Iranian rial–US dollar exchange rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 328-336.
    2. 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.
    3. Onali, Enrico & Goddard, John, 2009. "Unifractality and multifractality in the Italian stock market," International Review of Financial Analysis, Elsevier, vol. 18(4), pages 154-163, September.
    4. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    5. Kim, Kyungsik & Yoon, Seong-Min, 2004. "Multifractal features of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 272-278.
    6. repec:clg:wpaper:2008-21 is not listed on IDEAS
    7. Wang, Yudong & Liu, Li, 2010. "Is WTI crude oil market becoming weakly efficient over time?: New evidence from multiscale analysis based on detrended fluctuation analysis," Energy Economics, Elsevier, vol. 32(5), pages 987-992, September.
    8. Cajueiro, Daniel O. & Tabak, Benjamin M., 2007. "Long-range dependence and multifractality in the term structure of LIBOR interest rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 603-614.
    9. 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.
    10. Karuppiah, Jeyanthi & Los, Cornelis A., 2005. "Wavelet multiresolution analysis of high-frequency Asian FX rates, Summer 1997," International Review of Financial Analysis, Elsevier, vol. 14(2), pages 211-246.
    11. 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.
    12. Uritskaya, Olga Y. & Serletis, Apostolos, 2008. "Quantifying multiscale inefficiency in electricity markets," Energy Economics, Elsevier, vol. 30(6), pages 3109-3117, November.
    13. Kwapień, J. & Oświe¸cimka, P. & Drożdż, S., 2005. "Components of multifractality in high-frequency stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 466-474.
    14. Lim, Kian-Ping & Brooks, Robert D. & Kim, Jae H., 2008. "Financial crisis and stock market efficiency: Empirical evidence from Asian countries," International Review of Financial Analysis, Elsevier, vol. 17(3), pages 571-591, June.
    15. Lim, Gyuchang & Kim, SooYong & Lee, Hyoung & Kim, Kyungsik & Lee, Dong-In, 2007. "Multifractal detrended fluctuation analysis of derivative and spot markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 259-266.
    16. Tan, Lin & Chiang, Thomas C. & Mason, Joseph R. & Nelling, Edward, 2008. "Herding behavior in Chinese stock markets: An examination of A and B shares," Pacific-Basin Finance Journal, Elsevier, vol. 16(1-2), pages 61-77, January.
    17. Kumar, Sunil & Deo, Nivedita, 2009. "Multifractal properties of the Indian financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1593-1602.
    18. Du, Guoxiong & Ning, Xuanxi, 2008. "Multifractal properties of Chinese stock market in Shanghai," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(1), pages 261-269.
    19. Stavroyiannis, S. & Makris, I. & Nikolaidis, V., 2010. "Non-extensive properties, multifractality, and inefficiency degree of the Athens Stock Exchange General Index," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 19-24, January.
    20. Zunino, Luciano & Figliola, Alejandra & Tabak, Benjamin M. & Pérez, Darío G. & Garavaglia, Mario & Rosso, Osvaldo A., 2009. "Multifractal structure in Latin-American market indices," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2331-2340.
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