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A semi-APARCH approach for comparing long-term and short-term risk in Chinese financial market and in mature financial markets

Author

Listed:
  • Yuanhua Feng

    (University of Paderborn)

  • Lixin Sun

    (Shandong University)

Abstract

The aim of this paper is to analyze the long-term and short-term risk components in Chinese financial market and to compare them with those in mature financial markets. For this purpose a most recently proposed Semi-APARCH is applied to the Shanghai Index and the Shenzhen Index, and four financial indexes in mature markets. A few important empirical findings are achieved. Firstly, the current long-term risk in Chinese financial market is stable and at a low level. Secondly, the dependence level between long-term risk in Chinese financial market and that in mature financial market is not high. Thirdly, the short-term risk in Chinese financial market differs to that in a mature financial market at least in two ways: 1) The leverage effect in Chinese financial market is much lower than that in a mature financial market. 2) The innovations in Chinese financial returns is nearly heavy-tailed distributed. This is however not the case in a mature market.

Suggested Citation

  • Yuanhua Feng & Lixin Sun, 2013. "A semi-APARCH approach for comparing long-term and short-term risk in Chinese financial market and in mature financial markets," Working Papers CIE 69, Paderborn University, CIE Center for International Economics.
    • Handle: RePEc:pdn:ciepap:69
    as

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    File URL: http://groups.uni-paderborn.de/wp-wiwi/RePEc/pdf/ciepap/WP69.pdf
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    References listed on IDEAS

    as
    1. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. Buhlmann, Peter & McNeil, Alexander J., 2002. "An algorithm for nonparametric GARCH modelling," Computational Statistics & Data Analysis, Elsevier, vol. 40(4), pages 665-683, October.
    4. Sylvain Benoît & Gilbert Colletaz & Christophe Hurlin & Christophe Pérignon, 2013. "A Theoretical and Empirical Comparison of Systemic Risk Measures," Working Papers halshs-00746272, HAL.
    5. 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.
    6. Girardi, Giulio & Tolga Ergün, A., 2013. "Systemic risk measurement: Multivariate GARCH estimation of CoVaR," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3169-3180.
    7. Beran, Jan & Feng, Yuanhua & Ocker, Dirk, 1999. "SEMIFAR models," Technical Reports 1999,03, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    8. Van Bellegem, Sebastien & von Sachs, Rainer, 2004. "Forecasting economic time series with unconditional time-varying variance," International Journal of Forecasting, Elsevier, vol. 20(4), pages 611-627.
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    Citations

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    Cited by:

    1. Christian Peitz & Yuanhua Feng & Bernard M. Gilroy & Nico Stoeckmann, 2020. "The Shanghai- Hong Kong Stock Connect: An Application of the Semi-CGARCH and Semi-EGARCH," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 10(4), pages 427-438, April.
    2. repec:pdn:ciepap:104 is not listed on IDEAS
    3. Song, Wenjuan & Sun, Lixin, 2014. "The Measurement of the Long-Term and Short-Term Risks of Chinese Listed Banks," MPRA Paper 70007, University Library of Munich, Germany, revised Jul 2014.

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    More about this item

    Keywords

    Chinese financial market; mature financial markets; long-term risk; short-term risk; semiparametric APARCH;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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