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An alternative approach to predicting bank credit risk in Europe with Google data

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  • González-Fernández, Marcos
  • González-Velasco, Carmen

Abstract

The aim of this paper is to construct an alternative approach based on a sentiment index to measure bank credit risk in European countries using an alternative approach instead of traditional measures. Specifically, we use Google data for a set of keywords related to bank credit risk to capture investor sentiment. The resulting index shows a great similarity to traditional indexes based on bank CDS. The out-of-sample analysis demonstrates that our sentiment index is helpful for predicting bank credit risk during periods of financial distress, since it enhances the accuracy of the estimations.

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  • González-Fernández, Marcos & González-Velasco, Carmen, 2020. "An alternative approach to predicting bank credit risk in Europe with Google data," Finance Research Letters, Elsevier, vol. 35(C).
    • Handle: RePEc:eee:finlet:v:35:y:2020:i:c:s1544612319305318
    DOI: 10.1016/j.frl.2019.08.029
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    References listed on IDEAS

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    Cited by:

    1. Fang, Yi & Wang, Qi & Wang, Yanru & Yuan, Yan, 2024. "Media sentiment, deposit stability and bank systemic risk: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 1150-1172.

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    More about this item

    Keywords

    Sentiment index; Google data; Credit risk; Credit default swaps;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G40 - Financial Economics - - Behavioral Finance - - - General

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