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Measuring news media sentiment using big data for Chinese stock markets

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  • Shen, Shulin
  • Xia, Le
  • Shuai, Yulin
  • Gao, Da

Abstract

We construct and assess new time series measures of news media sentiment based on Global Data on Events, Location, and Tone (GDELT) using Data Science techniques. Five sentiment measures representing the news media Tone, Optimism, Attention, Tone Dispersion, and Emotional Polarity of Chinese stock markets are constructed based on article tone scores and media coverages from GDELT. All these news media sentiment measures are shown to have significant predictive power for Chinese stock market returns and volatilities. We also document substantial asymmetric sentiment effects on the Chinese stock market returns and volatilities. Sentiment extended EGARCH models are shown to improve market return and volatility forecasting accuracy significantly.

Suggested Citation

  • Shen, Shulin & Xia, Le & Shuai, Yulin & Gao, Da, 2022. "Measuring news media sentiment using big data for Chinese stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:pacfin:v:74:y:2022:i:c:s0927538x22001056
    DOI: 10.1016/j.pacfin.2022.101810
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    Cited by:

    1. Dai, Yue & Chen, Minhao & Zuo, Zhengyu, 2023. "Neighbors in space: Satellite imagery and Chinese B-share discount," China Economic Review, Elsevier, vol. 82(C).
    2. Abdollahi, Hooman & Fjesme, Sturla L. & Sirnes, Espen, 2024. "Measuring market volatility connectedness to media sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    3. Cássio Zanatto & Margarida Catalão‐Lopes & Joaquim P. Pina & Inês Carrilho‐Nunes, 2023. "The impact of ESG news on the volatility of the Portuguese stock market—Does it change during recessions?," Business Strategy and the Environment, Wiley Blackwell, vol. 32(8), pages 5821-5832, December.
    4. Banerjee, Ameet Kumar & Pradhan, H.K. & Akhtaruzzaman, Md & Sensoy, Ahmet & Dann, Susan, 2024. "Anatomy of sovereign yield behaviour using textual news," Research in International Business and Finance, Elsevier, vol. 71(C).
    5. Blajer-Gołębiewska, Anna & Honecker, Lukas & Nowak, Sabina, 2024. "Investor sentiment response to COVID-19 outbreak-related news: A sectoral analysis of US firms," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    6. Loan Thi Vu & Dong Ngoc Pham & Hang Thu Kieu & Thuy Thi Thanh Pham, 2023. "Sentiments Extracted from News and Stock Market Reactions in Vietnam," IJFS, MDPI, vol. 11(3), pages 1-16, August.
    7. Zhang, Zuochao & Goodell, John W. & Shen, Dehua & Lahmar, Oumaima, 2024. "Media opinion divergence and stock returns: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 93(C).

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    More about this item

    Keywords

    China; News sentiment; Big data; Stock market; GDELT;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G40 - Financial Economics - - Behavioral Finance - - - General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • 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

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