Complex Sciences. First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009. Revised Papers, Part 1

Research Article

The Contrast of Parametric and Nonparametric Volatility Measurement Based on Chinese Stock Market

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  • @INPROCEEDINGS{10.1007/978-3-642-02466-5_60,
        author={Xinwu Zhang and Yan Wang and Handong Li},
        title={The Contrast of Parametric and Nonparametric Volatility Measurement Based on Chinese Stock Market},
        proceedings={Complex Sciences. First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009. Revised Papers, Part 1},
        proceedings_a={COMPLEX PART 1},
        year={2012},
        month={5},
        keywords={realized volatility GARCH volatility measurement conditional distribution},
        doi={10.1007/978-3-642-02466-5_60}
    }
    
  • Xinwu Zhang
    Yan Wang
    Handong Li
    Year: 2012
    The Contrast of Parametric and Nonparametric Volatility Measurement Based on Chinese Stock Market
    COMPLEX PART 1
    Springer
    DOI: 10.1007/978-3-642-02466-5_60
Xinwu Zhang1, Yan Wang1, Handong Li1,*
  • 1: Beijing Normal University
*Contact email: li_handong@sina.com

Abstract

Most procedures for modeling and forecasting financial asset return volatilities rely on restrictive and complicated parametric GARCH or stochastic volatility models. The method of realized volatility constructed from high-frequency intraday returns is an alternative choice for volatility measurement. In this paper we make an empirical analysis on Chinese stock index data by using the method of nonparametric realized volatility. We find that the realized volatility can describe the Chinese stock index volatility very well. The original Chinese stock index return series show obvious leptokurtic, fat-tailed relative to the Gaussian distribution.We show that the return series standardized instead by the realized volatility are very nearly Gaussian distribution, and we find that the four minutes is a better choice as the best time interval to describe the volatility of Chinese stock market. We also make a contrast with the popular method of GARCH model, but the return series standardized instead by GARCH model don’t accord with Gaussian distribution. The result shows that the realized volatility can describe the dynamic behaviors of Chinese stock market well. In a way, it indicates that the Chinese stock market is effective.