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

Georges Dionne () and Samir Saissi-Hassani ()
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Samir Saissi-Hassani: HEC Montreal, Canada Research Chair in Risk Management

No 15-3, Working Papers from HEC Montreal, Canada Research Chair in Risk Management

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 American banks contain 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 when regimes are not considered.

Keywords: Hidden Markov Regime; operational risk; 2007-2009 financial crisis; skew t type 4 distribution; banks’ regulatory capital (search for similar items in EconPapers)
JEL-codes: G21 G24 G28 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2016-08-29
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Persistent link: https://EconPapers.repec.org/RePEc:ris:crcrmw:2015_003

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