Identifying Systemically Important Banks: A temporal approach for macroprudential policies

A. Spelta, N. Pecora and P. Rovira Kaltwasser

Journal of Policy Modeling, 2019, vol. 41, issue 1, 197-218

Abstract: Contrary to the general belief, systemic risk does not only regard the risk posed by balance sheet relationships and interdependencies among institutions. It also features a temporal dimension related to the inappropriate responses of financial market participants to changes in risk over time. This paper proposes a method to simultaneously address the cross-sectional and the time dimension in which systemic risk materializes. The method is based on the TOPHITS algorithm. It provides three scores, namely borrowing, lending and time scores: the first two represent the systemic importance of the borrowing and the lending activity associated with each financial institution,while the third represents an empirical Early Warning Signal of the financial crisis. Our findings reveal that the identification of the time score as an indicator for an incoming market distress could be relevant to design macro prudential policies.

Keywords: Tensor decomposition; Early warnings; Evolving networks; Interbank market; Systemically important financial institutions (search for similar items in EconPapers)
JEL-codes: C15 C63 G01 G17 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jpolmo:v:41:y:2019:i:1:p:197-218

DOI: 10.1016/j.jpolmod.2018.06.004

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