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A dynamic analysis of the relationship between investor sentiment and stock market realized volatility: Evidence from China

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  • Yanhui Chen
  • Hanhui Zhao
  • Ziyu Li
  • Jinrong Lu

Abstract

Investor sentiment is a research focus in behavior finance. This paper chooses five proxy variables according to China’s reality and uses a two-step principal component analysis to construct an investor sentiment index. The five proxy variables are the number of new stock accounts, turnover ratio, margin balance, net active purchasing amount, and investor attention. In the final part of this study, using the price data from the Shanghai and Shenzhen Security Exchange, this paper investigates the dynamic relationship between investor sentiment and stock market realized volatility based on the thermal optimal path. The empirical results show that when the market fluctuates severely, investor sentiment leads stock market realized volatility over one or two steps. The prediction power is also checked. The results indicate that investor sentiment indeed forecasts the realized volatility. This research supports regulators and financial institutions in taking advanced measures.

Suggested Citation

  • Yanhui Chen & Hanhui Zhao & Ziyu Li & Jinrong Lu, 2020. "A dynamic analysis of the relationship between investor sentiment and stock market realized volatility: Evidence from China," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-18, December.
    • Handle: RePEc:plo:pone00:0243080
    DOI: 10.1371/journal.pone.0243080
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    References listed on IDEAS

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    Cited by:

    1. Li, Jiaqi & Ahn, Hee-Joon, 2024. "Sensitivity of Chinese stock markets to individual investor sentiment: An analysis of Sina Weibo mood related to COVID-19," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
    2. Chen, Zhang-HangJian & Ren, Fei & Yang, Ming-Yuan & Lu, Feng-Zhi & Li, Sai-Ping, 2023. "Dynamic lead–lag relationship between Chinese carbon emission trading and stock markets under exogenous shocks," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 295-305.
    3. Zhaofeng Zhang & Banghao Chen & Shengxin Zhu & Nicolas Langren'e, 2024. "Quantformer: from attention to profit with a quantitative transformer trading strategy," Papers 2404.00424, arXiv.org, revised Oct 2024.
    4. Aneeta Elsa Simon & Manu K.S., 2023. "Does Sentiments Impact the Returns of Commodity Derivatives? An Evidence from Multi-commodity Exchange India," Vision, , vol. 27(1), pages 79-92, February.

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