Artikel

Modeling the connection between bank systemic risk and balance-sheet liquidity proxies through random forest regressions

Balance-sheet indicators may reflect, to a great extent, bank fragility. This inherent relationship is the object of theoretical models testing for balance-sheet vulnerabilities. In this sense, we aim to analyze whether systemic risk for a sample of US banks can be explained by a series of balance-sheet variables, considered as proxies for bank liquidity for the 2004:1-2019:1 period. We first compute Marginal Expected Shortfall values for the entities in our sample and then imbed them into a Random Forest regression setup. Although we discover that feature importance is rather bank-specific, we notice that cash and available-for-sale securities are the most relevant factors in explaining the dynamics of systemic risk. Our findings emphasize the need for heightened prudential regulation of bank liquidity, particularly in what concerns cash and immediate liquidity instrument weights. Moreover, systemic risk could be consistently tamed by consolidating bank emergency liquidity provision schemes.

Sprache
Englisch

Erschienen in
Journal: Administrative Sciences ; ISSN: 2076-3387 ; Volume: 10 ; Year: 2020 ; Issue: 3 ; Pages: 1-14 ; Basel: MDPI

Klassifikation
Öffentliche Verwaltung
Thema
balance-sheet data
Marginal Expected Shortfall
Random Forest regression
systemic risk

Ereignis
Geistige Schöpfung
(wer)
Zeldea, Cristina
Ereignis
Veröffentlichung
(wer)
MDPI
(wo)
Basel
(wann)
2020

DOI
doi:10.3390/admsci10030052
Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Zeldea, Cristina
  • MDPI

Entstanden

  • 2020

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