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CCTV News’ Asymmetric Impact on the Chinese Stock Market during COVID-19: A Combination Analysis Based on the SVAR and NARDL Models

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  • Chao Deng
  • Congcong Liang
  • Yun Hong
  • Yanhui Jiang

Abstract

This study uses the structural vector autoregression (SVAR) and nonlinear autoregressive distributed lag (NARDL) models to examine the long- and short-term asymmetric effects of structural state media shocks on the Chinese stock market. The findings, obtained using Xinwen Lianbo as a stand-in for state media, indicate that attention shocks on Xinwen Lianbo have an asymmetrical impact on the aggregate stock market returns in both the short and long run. The sectoral and overall stock market results are similar, with CCTV having a stronger impact in the first half of the pandemic. Employing other COVID-19 news measurements, we validated our primary findings and discovered that the price function differs among various state media’s attention to COVID-19.

Suggested Citation

  • Chao Deng & Congcong Liang & Yun Hong & Yanhui Jiang, 2023. "CCTV News’ Asymmetric Impact on the Chinese Stock Market during COVID-19: A Combination Analysis Based on the SVAR and NARDL Models," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 59(4), pages 1232-1246, March.
    • Handle: RePEc:mes:emfitr:v:59:y:2023:i:4:p:1232-1246
    DOI: 10.1080/1540496X.2022.2123219
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    Cited by:

    1. Li, Yanshuang & Shi, Yujie & Shi, Yongdong & Xiong, Xiong & Yi, Shangkun, 2024. "Time-frequency extreme risk spillovers between COVID-19 news-based panic sentiment and stock market volatility in the multi-layer network: Evidence from the RCEP countries," International Review of Financial Analysis, Elsevier, vol. 94(C).

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