An alternative approach to predicting bank credit risk in Europe with Google data
Marcos González-Fernández and
Finance Research Letters, 2020, vol. 35, issue C
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.
Keywords: Sentiment index; Google data; Credit risk; Credit default swaps (search for similar items in EconPapers)
JEL-codes: G10 G17 G40 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:35:y:2020:i:c:s1544612319305318
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