Short-term Prediction of Bank Deposit Flows: Do Textual Features matter?

Apostolos Katsafados and Dimitris Anastasiou

MPRA Paper from University Library of Munich, Germany

Abstract: The purpose of this study is twofold. First, to construct short-term prediction models for bank deposit flows in the Euro area peripheral countries, employing machine learning techniques. Second, to examine whether textual features enhance the predictive ability of our models. We find that Random Forest models including both textual features and macroeconomic variables outperform those that include only macro factors or textual features. Monetary policy authorities or macroprudential regulators could adopt our approach to timely predict potential excessive bank deposit outflows and assess the resilience of the whole banking sector in the Euro area peripheral countries.

Keywords: Bank deposit flows; European banks; textual analysis; short-term prediction; machine learning (search for similar items in EconPapers)
JEL-codes: C0 C22 C5 C51 C54 E44 E47 G10 (search for similar items in EconPapers)
Date: 2022-01
New Economics Papers: this item is included in nep-ban, nep-big, nep-cba, nep-cmp, nep-fdg, nep-mac and nep-mon
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https://mpra.ub.uni-muenchen.de/111418/1/MPRA_paper_111418.pdf original version (application/pdf)

Related works:
Journal Article: Short-term prediction of bank deposit flows: do textual features matter? (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:111418

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