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News indices on country fundamentals

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  • Fulop, Andras
  • Kocsis, Zalan

Abstract

We propose a novel method to extract textual information about macro fundamentals. The method has two pillars, a set of pre-defined regular expressions and a Bayesian feature selection model. We apply our technique to a 2007–2022 Reuters news corpus from Factiva to create news indices of country fundamentals. Compared to several literature alternatives, we find our method to better identify and discriminate among fundamentals based on both (i) observed economic surprises (macro announcements compared to Bloomberg survey expectations) and (ii) labels on a manually classified test sample. In an application that investigates the determinants of sovereign credit spreads, we show that including our news indices next to traditional macro variables significantly raises the explanatory power attributed to fundamentals. We also show that part of the covariance between sovereign spreads and the VIX and US high yield indices is related to global fundamentals captured by our indices.

Suggested Citation

  • Fulop, Andras & Kocsis, Zalan, 2023. "News indices on country fundamentals," Journal of Banking & Finance, Elsevier, vol. 154(C).
    • Handle: RePEc:eee:jbfina:v:154:y:2023:i:c:s0378426623001565
    DOI: 10.1016/j.jbankfin.2023.106951
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    More about this item

    Keywords

    Financial media; Textual data; Regular expressions; Sequential Monte Carlo; Sovereign credit risk;
    All these keywords.

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F34 - International Economics - - International Finance - - - International Lending and Debt Problems
    • G1 - Financial Economics - - General Financial Markets
    • H63 - Public Economics - - National Budget, Deficit, and Debt - - - Debt; Debt Management; Sovereign Debt

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