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Volatility Switching in Shanghai Stock Exchange: Does regulation help reduce volatility?

Author

Listed:
  • Zhang, Dayong
  • Dickinson, David
  • Barassi, Marco

Abstract

This paper investigates volatility switching in the Shanghai Stock Exchange (SSE hereafter,) using several recently developed techniques. They can be categorized into CUSUM type tests and Markov-Switching ARCH models. By detecting and dating switches with these models, we are able to show the volatility dynamics in SSE. Investigating the events in SSE around the switching date suggests that regulation improvements significantly reduce the volatility of the underlying market. Furthermore, the empirical results show that outliers can have significant impact on the conclusion and thus should properly be removed.

Suggested Citation

  • Zhang, Dayong & Dickinson, David & Barassi, Marco, 2008. "Volatility Switching in Shanghai Stock Exchange: Does regulation help reduce volatility?," MPRA Paper 70352, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:70352
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    File URL: https://mpra.ub.uni-muenchen.de/70352/1/MPRA_paper_70352.pdf
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    References listed on IDEAS

    as
    1. Luc Bauwens & Arie Preminger & Jeroen V. K. Rombouts, 2010. "Theory and inference for a Markov switching GARCH model," Econometrics Journal, Royal Economic Society, vol. 13(2), pages 218-244, July.
    2. Elena Andreou & Eric Ghysels, 2002. "Detecting multiple breaks in financial market volatility dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 579-600.
    3. Dueker, Michael J, 1997. "Markov Switching in GARCH Processes and Mean-Reverting Stock-Market Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 26-34, January.
    4. Jurgen A. Doornik & Marius Ooms, 2005. "Outlier Detection in GARCH Models," Tinbergen Institute Discussion Papers 05-092/4, Tinbergen Institute.
    5. Kokoszka, Piotr & Leipus, Remigijus, 1998. "Change-point in the mean of dependent observations," Statistics & Probability Letters, Elsevier, vol. 40(4), pages 385-393, November.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. Lamoureux, Christopher G & Lastrapes, William D, 1990. " Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    8. Cai, Jun, 1994. "A Markov Model of Switching-Regime ARCH," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 309-316, July.
    9. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
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    Cited by:

    1. Lucía Morales & Bernadette Andreosso-O’Callaghan, 2014. "Volatility analysis of precious metals returns and oil returns: An ICSS approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 38(3), pages 492-517, July.

    More about this item

    Keywords

    Volatility switching; CUSUM test; Markov-Switching ARCH; Shanghai Stock Exchange; Outlier.;

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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