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Impact of public news sentiment on stock market index return and volatility

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  • Anese, Gianluca
  • Corazza, Marco
  • Costola, Michele
  • Pelizzon, Loriana

Abstract

Recent advances in natural language processing have contributed to the development of market sentiment measures through text content analysis in news providers and social media. The effectiveness of these sentiment variables depends on the implemented techniques and the type of source on which they are based. In this paper, we investigate the impact of the release of public financial news on the S&P 500. Using automatic labeling techniques based on either stock index returns or dictionaries, we apply a classification problem based on long short-term memory neural networks to extract alternative proxies of investor sentiment. Our findings provide evidence that there exists an impact of those sentiments in the market on a 20-minute time frame. We find that dictionary-based sentiment provides meaningful results with respect to those based on stock index returns, which partly fails in the mapping process between news and financial returns.

Suggested Citation

  • Anese, Gianluca & Corazza, Marco & Costola, Michele & Pelizzon, Loriana, 2021. "Impact of public news sentiment on stock market index return and volatility," SAFE Working Paper Series 322, Leibniz Institute for Financial Research SAFE.
    • Handle: RePEc:zbw:safewp:322
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    Cited by:

    1. Sakthivel SANTHOSHKUMAR & Murugesan SELVAM, 2024. "Twitter sentiments and stock indices returns with reference to nifty energy indices of India," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(1(638), S), pages 125-136, Spring.

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    More about this item

    Keywords

    Public financial news; Stock market; NLP; Dictionary; LSTM neural networks; Investor sentiment; S&P 500;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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