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Long memory volatility in Chinese stock markets

Author

Listed:
  • Kang, Sang Hoon
  • Cheong, Chongcheul
  • Yoon, Seong-Min
Abstract
In this study, the long memory property in the volatility of Chinese stock markets is examined. For this purpose, we applied two semi-parametric tests (GPH and LW) and the FIGARCH model, to four Chinese market indices: Shanghai A, Shanghai B, Shenzhen A and Shenzhen B. From the results of our analysis, we can conclude that the volatility of Chinese stock markets exhibits long memory features, and that the assumption of non-normality provides better specifications regarding long memory volatility processes.

Suggested Citation

  • Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2010. "Long memory volatility in Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(7), pages 1425-1433.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:7:p:1425-1433
    DOI: 10.1016/j.physa.2009.12.004
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    References listed on IDEAS

    as
    1. Philipp Sibbertsen, 2004. "Long memory in volatilities of German stock returns," Empirical Economics, Springer, vol. 29(3), pages 477-488, September.
    2. Andersen, Torben G & Bollerslev, Tim, 1997. "Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," Journal of Finance, American Finance Association, vol. 52(3), pages 975-1005, July.
    3. 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.
    4. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871, September.
    5. Tim Bollerslev & Jonathan H. Wright, 2001. "High-Frequency Data, Frequency Domain Inference, And Volatility Forecasting," The Review of Economics and Statistics, MIT Press, vol. 83(4), pages 596-602, November.
    6. Yanhui Liu & Pierre Cizeau & Martin Meyer & Chung-Kang Peng & H. Eugene Stanley, 1997. "Correlations in Economic Time Series," Papers cond-mat/9706021, arXiv.org.
    7. Lobato, Ignacio N & Savin, N E, 1998. "Real and Spurious Long-Memory Properties of Stock-Market Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 261-268, July.
    8. Mu, Guo-Hua & Zhou, Wei-Xing, 2008. "Relaxation dynamics of aftershocks after large volatility shocks in the SSEC index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5211-5218.
    9. Tian Qiu & Liang Guo & Guang Chen, 2008. "Scaling and Memory Effect in Volatility Return Interval of the Chinese Stock Market," Papers 0805.2194, arXiv.org.
    10. Sibbertsen, Philipp, 2003. "Log-periodogram estimation of the memory parameter of a long-memory process under trend," Statistics & Probability Letters, Elsevier, vol. 61(3), pages 261-268, February.
    11. Jonathan Wright, 2002. "Log-Periodogram Estimation Of Long Memory Volatility Dependencies With Conditionally Heavy Tailed Returns," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 397-417.
    12. Podobnik, Boris & Fu, Dongfeng & Jagric, Timotej & Grosse, Ivo & Eugene Stanley, H., 2006. "Fractionally integrated process for transition economics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 362(2), pages 465-470.
    13. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    14. Parameswaran Gopikrishnan & Vasiliki Plerou & Luis A. Nunes Amaral & Martin Meyer & H. Eugene Stanley, 1999. "Scaling of the distribution of fluctuations of financial market indices," Papers cond-mat/9905305, arXiv.org.
    15. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    16. Dionisio, Andreia & Menezes, Rui & Mendes, Diana A., 2007. "On the integrated behaviour of non-stationary volatility in stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 58-65.
    17. Wen Cheong, Chin & Hassan Shaari Mohd Nor, Abu & Isa, Zaidi, 2007. "Asymmetry and long-memory volatility: Some empirical evidence using GARCH," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 651-664.
    18. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    19. Cajueiro, Daniel O. & Tabak, Benjamin M., 2005. "Testing for time-varying long-range dependence in volatility for emerging markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(3), pages 577-588.
    20. Tang, Ta-Lun & Shieh, Shwu-Jane, 2006. "Long memory in stock index futures markets: A value-at-risk approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 437-448.
    21. Huimin Chung & William T. Lin & Soushan Wu, 2000. "An Analysis of Long Memory in Volatility for Asian Stock Markets," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 3(03), pages 309-330.
    22. 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.
    23. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    24. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    25. Tabak, Benjamin M. & Cajueiro, Daniel O., 2005. "The long-range dependence behavior of the term structure of interest rates in Japan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 418-426.
    26. Cajueiro, Daniel O. & Tabak, Benjamin M., 2007. "Long-range dependence and market structure," Chaos, Solitons & Fractals, Elsevier, vol. 31(4), pages 995-1000.
    27. Kang, Sang Hoon & Yoon, Seong-Min, 2007. "Long memory properties in return and volatility: Evidence from the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 591-600.
    28. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    29. Jiang, Zhi-Qiang & Chen, Wei & Zhou, Wei-Xing, 2008. "Scaling in the distribution of intertrade durations of Chinese stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5818-5825.
    30. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    31. 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.
    32. Granger, Clive W. J. & Ding, Zhuanxin, 1996. "Varieties of long memory models," Journal of Econometrics, Elsevier, vol. 73(1), pages 61-77, July.
    33. Qiu, T. & Guo, L. & Chen, G., 2008. "Scaling and memory effect in volatility return interval of the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6812-6818.
    34. Qiu, T. & Zhong, L.X. & Chen, G. & Wu, X.R., 2009. "Statistical properties of trading volume of Chinese stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2427-2434.
    35. 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.
    36. Cheong, Chin Wen, 2008. "Time-varying volatility in Malaysian stock exchange: An empirical study using multiple-volatility-shift fractionally integrated model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 889-898.
    37. Cheng F. Lee & Gong-meng Chen & Oliver M. Rui, 2001. "Stock Returns And Volatility On China'S Stock Markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 24(4), pages 523-543, December.
    38. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    39. Kang, Sang Hoon & Yoon, Seong-Min, 2008. "Long memory features in the high frequency data of the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5189-5196.
    40. oh, Gabjin & Kim, Seunghwan & Eom, Cheoljun, 2008. "Long-term memory and volatility clustering in high-frequency price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(5), pages 1247-1254.
    41. Jiang, J. & Li, W. & Cai, X. & Wang, Qiuping A., 2009. "Empirical study of recent Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(9), pages 1893-1907.
    42. Chin, Wen Cheong, 2008. "Heavy-tailed value-at-risk analysis for Malaysian stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(16), pages 4285-4298.
    43. Lobato, Ignacio N & Savin, N E, 1998. "Real and Spurious Long-Memory Properties of Stock-Market Data: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 280-283, July.
    44. Carbone, A. & Castelli, G. & Stanley, H.E., 2004. "Time-dependent Hurst exponent in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 267-271.
    45. 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.
    46. Liu, Yanhui & Cizeau, Pierre & Meyer, Martin & Peng, C.-K. & Eugene Stanley, H., 1997. "Correlations in economic time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 245(3), pages 437-440.
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