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Título
An alternative approach to predicting bank credit risk in Europe with Google data
Autor
Facultad/Centro
Área de conocimiento
Título de la revista
Finance Research Letters
Editor
Elsevier
Fecha
2020-07-15
ISSN
1544-6123
Résumé
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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