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News sentiment and stock market volatility

Author

Listed:
  • Yen-Ju Hsu

    (Fu Jen Catholic University
    National Taiwan University)

  • Yang-Cheng Lu

    (Ming Chuan University)

  • J. Jimmy Yang

    (Oregon State University)

Abstract

This study investigates the effect of news sentiment on stock market volatility using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and measures the asymmetric effect with the GJR-GARCH model. We adopt patented linguistic analysis that considers the semantic orientation process to quantify financial news that may attract investor attention. This study distinguishes between unclassified market news sentiment and macroeconomic-related news effects. The evidence suggests that both contemporaneous and lagged news are determinants of market volatility. The effect is especially strong with the market aggregate news sentiment index (ANSI) and the negative ANSI, particularly during the 2008–2009 financial crisis period. This analysis of news sentiment improves the accuracy of in-sample and out-of-sample volatility forecasting.

Suggested Citation

  • Yen-Ju Hsu & Yang-Cheng Lu & J. Jimmy Yang, 2021. "News sentiment and stock market volatility," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 1093-1122, October.
    • Handle: RePEc:kap:rqfnac:v:57:y:2021:i:3:d:10.1007_s11156-021-00971-8
    DOI: 10.1007/s11156-021-00971-8
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    More about this item

    Keywords

    Volatility; GARCH model; Asymmetric effect; News sentiment; Macroeconomic news;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G1 - Financial Economics - - General Financial Markets

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