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Forecasting volatility of the Chinese stock markets using TVP HAR-type models

Author

Listed:
  • Liu, Guangqiang
  • Wang, Yan
  • Chen, Xiaodan
  • Zhang, Yifeng
  • Shang, Yue

Abstract

In this paper, we use a novel Heterogeneous Autoregressive Model (HAR) with time-varying parameters (TVP) to forecast China’s stock market volatility. Many traditional constant coefficient (CC) HAR-type models, incorporating signed variance, jump and volatility leverage effect, are extended to be TVP models. The empirical results show that the extended TVP HAR-type models can beat those CC HAR-type ones in both in-sample estimation and out-of-sample prediction perspective. Moreover, the TVP HAR model that can describe continuous volatility component, signed jump and leverage effect is superior to other CC or TVP HAR-type models in forecasting the volatilities of China’s stock market.

Suggested Citation

  • Liu, Guangqiang & Wang, Yan & Chen, Xiaodan & Zhang, Yifeng & Shang, Yue, 2020. "Forecasting volatility of the Chinese stock markets using TVP HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    • Handle: RePEc:eee:phsmap:v:542:y:2020:i:c:s0378437119319247
    DOI: 10.1016/j.physa.2019.123445
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    References listed on IDEAS

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