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Interindustry volatility spillover effects in China’s stock market

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  • Yin, Kedong
  • Liu, Zhe
  • Jin, Xue

Abstract

In this paper, we apply a spillover index method to investigate the interindustry volatility spillovers in Shanghai Stock Exchange during 2009 to 2018. This method is widely used for information spillover behavior between different financial time series. The empirical result indicates that there are some closely related industry pairs in the SSE. The overall spillover index increased significantly during the bull and bear markets and the bull market period became more pronounced. In the time-varying spillover structure, the optional consumer and industrial sectors have been playing a leading role. At the end of the sample period, the spillover level of industrial and raw materials industries fluctuated in a V-shaped manner, while the spillover level of medical & health and public utilities industries increased significantly. The empirical results show that the evolution process of spillover effects between industries corresponds to specific events in political and financial markets. The authorities should adjust industry policies based on these evolutionary rules, and investors can also use this to allocate assets. These findings are also important for analyzing the causes of stock market volatility and for taking measures to reduce market risk.

Suggested Citation

  • Yin, Kedong & Liu, Zhe & Jin, Xue, 2020. "Interindustry volatility spillover effects in China’s stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    • Handle: RePEc:eee:phsmap:v:539:y:2020:i:c:s0378437119316632
    DOI: 10.1016/j.physa.2019.122936
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    8. Zhou, Dong-hai & Liu, Xiao-xing & Tang, Chun & Yang, Guang-yi, 2023. "Time-varying risk spillovers in Chinese stock market – New evidence from high-frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).

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    More about this item

    Keywords

    Interindustry volatility spillover; Industry indices; Transfer structure; Dynamic evolution;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

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