Abstract
AbstractIn the last decade of the financial crisis of 2007, the international financial system appeared to be on the brink of a major systemic crisis which leads to a failure of a systemically important European bank. This type of scenario highlights the need for identifying and measuring of the contribution of banks to systemic risk in the financial system. Then, the aim of this paper is to propose, for the first time, a new approach to measure systemic risk in the financial institutions. This approach is based on the epidemic model methodology. Then, we use the SEIR model with four compartments: Susceptible, Exposed, Infected, and Removed. We apply this model for a sample of 18 Greek banks listed in the Athens Exchange over the period from 2 January 2006 to 31 December 2012. Based on the empirical results, we find the existence of 12 times of default transmission during the study period and the transmission of default coincides with the number of Greek banks that have declared failure and then leaving t...
Highlights
The magnitude of the recent financial crisis has led to a redesign of the mechanisms’ supervision of the financial sector
We find that the default probability, the recovery rate, the default correlation, the exposure at default, the frequency of default in the case of loss, the market capitalization, and the regulatory authorities are the main factors of the systemic risk in the financial system of Greece
We present a biofinancial approach adopted for the modeling of systemic risk
Summary
The magnitude of the recent financial crisis has led to a redesign of the mechanisms’ supervision of the financial sector. Segoviano and Goodhart (2009) propose a model for measuring systemic risk, the joint probability of default (JPod) This model was used to analyze conditional probabilities between institutions and the Banking Stability Index (BSI). They found five indicators of systemic risk which are as follows: the values of CDS, the implied probability of default of CDS, the expected default frequency (EDF), the correlation of asset yields, and recovery rates Their results show that all these indicators have a direct effect on systemic risk in Asian banks employed in their study. Derbali, Hallara, and Sy (2015) employed a conditional approach to estimate the systemic risk which allows decomposing the risk of the aggregate financial system of Greece They employed the SRISK index to assess the systemic risk contribution of each Greek bank
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