Identifying Systemically Important Banks: A temporal approach for macroprudential policies

Nicolo' Pecora, Alessandro Spelta, A. Spelta, P. Rovira Kaltwasser

Research output: Contribution to journalArticlepeer-review

4 Citations (SciVal)

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.
Original languageEnglish
Pages (from-to)N/A-N/A
JournalJournal of Policy Modeling
DOIs
Publication statusPublished - 2018

Keywords

  • Early warnings
  • Evolving networks
  • Interbank market
  • Systemically important financial institutions
  • Tensor decomposition

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