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Measuring and Forecasting Volatility in Chinese Stock Market Using HAR‐CJ‐M Model

Author

Listed:
  • Chuangxia Huang
  • Xu Gong
  • Xiaohong Chen
  • Fenghua Wen

Abstract

Basing on the Heterogeneous Autoregressive with Continuous volatility and Jumps model (HAR‐CJ), converting the realized Volatility (RV) into the adjusted realized volatility (ARV), and making use of the influence of momentum effect on the volatility, a new model called HAR‐CJ‐M is developed in this paper. At the same time, we also address, in great detail, another two models (HAR‐ARV, HAR‐CJ). The applications of these models to Chinese stock market show that each of the continuous sample path variation, momentum effect, and ARV has a good forecasting performance on the future ARV, while the discontinuous jump variation has a poor forecasting performance. Moreover, the HAR‐CJ‐M model shows obviously better forecasting performance than the other two models in forecasting the future volatility in Chinese stock market.

Suggested Citation

  • Chuangxia Huang & Xu Gong & Xiaohong Chen & Fenghua Wen, 2013. "Measuring and Forecasting Volatility in Chinese Stock Market Using HAR‐CJ‐M Model," Abstract and Applied Analysis, John Wiley & Sons, vol. 2013(1).
    • Handle: RePEc:wly:jnlaaa:v:2013:y:2013:i:1:n:143194
    DOI: 10.1155/2013/143194
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    References listed on IDEAS

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    Cited by:

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    3. Zhifeng Dai, 2014. "Extension of Modified Polak‐Ribière‐Polyak Conjugate Gradient Method to Linear Equality Constraints Minimization Problems," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).

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