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What news can really tell us? Evidence from a news-based sentiment index for financial markets analysis

Author

Listed:
  • Anna Marszal

    (Narodowy Bank Polski)

Abstract

This study presents a state-of-the-art approach in measuring financial market sentiment, namely, extracting it from news headlines. The sentiment index is constructed by analysing over 124,000 news items for the 2020-2021 period using natural language processing methods. Its informational power is validated by the strong correlation with the VIX index as well as by the occurrence of common periods of higher volatility of both measures. These findings reinforce the treatment of the news-based index as a true sentiment indicator and contribute to its usage independently of any financial instruments. Additionally, a direction of significant correlation coefficients between the sentiment indicator and selected financial assets is consistent with the natural logic of capital flows in financial markets. At the same time, the developed tool allows to identify not only market sentiment, but also the main factors contributing to its direction and time periods in which they are of most significance. It is necessary to understand that the analysed period is specific as it coincides with the outbreak and development of the COVID-19 pandemic. This was reflected in the results that highlight coronavirus as the dominant topic throughout the dataset.

Suggested Citation

  • Anna Marszal, 2022. "What news can really tell us? Evidence from a news-based sentiment index for financial markets analysis," NBP Working Papers 349, Narodowy Bank Polski.
    • Handle: RePEc:nbp:nbpmis:349
    as

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    References listed on IDEAS

    as
    1. Diego García, 2013. "Sentiment during Recessions," Journal of Finance, American Finance Association, vol. 68(3), pages 1267-1300, June.
    2. Xi Zhang & Yunjia Zhang & Senzhang Wang & Yuntao Yao & Binxing Fang & Philip S. Yu, 2018. "Improving Stock Market Prediction via Heterogeneous Information Fusion," Papers 1801.00588, arXiv.org.
    3. Mariano González-Sánchez & M. Encina Morales de Vega, 2021. "Influence of Bloomberg’s Investor Sentiment Index: Evidence from European Union Financial Sector," Mathematics, MDPI, vol. 9(4), pages 1-21, February.
    4. L.A. Smales, 2017. "The importance of fear: investor sentiment and stock market returns," Applied Economics, Taylor & Francis Journals, vol. 49(34), pages 3395-3421, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    market sentiment; natural language processing; lexicon-based models; VADER; risk aversion; risk appetite; VIX index; news; volatility;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • G4 - Financial Economics - - Behavioral Finance

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