Hidden Markov Regimes in Operational Loss Data: Application to the Recent Financial Crisis

30 Pages Posted: 11 Feb 2017

See all articles by Georges Dionne

Georges Dionne

HEC Montreal - Department of Finance

Samir Saissi Hassani

HEC Montreal - Department of Finance

Date Written: February 10, 2017

Abstract

We propose a method to consider business cycles in the computation of capital for operational risk. We examine whether the operational loss data of US banks contains a hidden Markov regime-switching feature from 2001 to 2010. We assume asymmetric distribution of monthly losses. Statistical tests do not reject this assumption. A high-level regime is marked by very high loss values during the recent financial crisis, confirming temporal heterogeneity in the data. If this heterogeneity is not considered in risk management models, capital estimations will be biased. Banks will hold too much capital during periods of low stress and not enough capital in periods of high stress. Additional capital reaches 30% during this period of analysis if regimes are not considered.

Keywords: hidden Markov regime, operational risk, 2007–9 financial crisis, skew-t type-4 distribution, banks’ regulatory capital

Suggested Citation

Dionne, Georges and Saissi Hassani, Samir, Hidden Markov Regimes in Operational Loss Data: Application to the Recent Financial Crisis (February 10, 2017). Journal of Operational Risk, 12(1), 23–51 DOI:10.21314/JOP.2017.188 . Available at SSRN: https://ssrn.com/abstract=2915113

Georges Dionne (Contact Author)

HEC Montreal - Department of Finance ( email )

3000 Chemin de la Cote-Sainte-Catherine
Montreal, Quebec H3T 2A7
Canada
514-340-6596 (Phone)
514-340-5019 (Fax)

HOME PAGE: http://www.hec.ca/gestiondesrisques/

Samir Saissi Hassani

HEC Montreal - Department of Finance ( email )

3000 Chemin de la Cote-Sainte-Catherine
Montreal, Quebec H3T 2A7
Canada

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