Next Article in Journal
Regulatory Restrictions on US Bank Funding Sources: A Review of the Treatment of Brokered Deposits
Next Article in Special Issue
Information Frictions and Stock Returns
Previous Article in Journal
Exchange Rate Risk and Uncertainty and Trade Flows: Asymmetric Evidence from Asia
Previous Article in Special Issue
The Influence of Domestic and Foreign Shocks on Portfolio Diversification Gains and the Associated Risks
Open AccessArticle

Modeling Portfolio Credit Risk Taking into Account the Default Correlations Using a Copula Approach: Implementation to an Italian Loan Portfolio

Department of Social and Economic Sciences, “Sapienza” University of Rome, 00185 Roma RM, Italy
J. Risk Financial Manag. 2020, 13(6), 129; https://doi.org/10.3390/jrfm13060129
Received: 1 June 2020 / Revised: 12 June 2020 / Accepted: 13 June 2020 / Published: 17 June 2020
(This article belongs to the Special Issue Quantitative Risk)
This work aims to illustrate an advanced quantitative methodology for measuring the credit risk of a loan portfolio allowing for diversification effects. Also, this methodology can allocate the credit capital coherently to each counterparty in the portfolio. The analytical approach used for estimating the portfolio credit risk is a binomial type based on a Monte Carlo Simulation. This method takes into account the default correlations among the credit counterparties in the portfolio by following a copula approach and utilizing the asset return correlations of the obligors, as estimated by rigorous statistical methods. Moreover, this model considers the recovery rates as stochastic and dependent on each other and on the time until defaults. The methodology utilized for coherently allocating credit capital in the portfolio estimates the marginal contributions of each obligor to the overall risk of the loan portfolio in terms of Expected Shortfall (ES), a risk measure more coherent and conservative than the traditional measure of Value-at-Risk (VaR). Finally, this advanced analytical structure is implemented to a hypothetical, but typical, loan portfolio of an Italian commercial bank operating across the overall national country. The national loan portfolio is composed of 17 sub-portfolios, or geographic clusters of credit exposures to 10,500 non-financial firms (or corporates) belonging to each geo-cluster or sub-portfolio. The outcomes, in terms of correlations, portfolio risk measures and capital allocations obtained from this advanced analytical framework, are compared with the results found by implementing the Internal Rating Based (IRB) approach of Basel II and III. Our chief conclusion is that the IRB model is unable to capture the real credit risk of loan portfolios because it does not take into account the actual dependence structure among the default events, and between the recovery rates and the default events. We underline that the adoption of this regulatory model can produce a dangerous underestimation of the portfolio credit risk, especially when the economic uncertainty and the volatility of the financial markets increase. View Full-Text
Keywords: portfolio credit risk; asset correlation; coherent capital allocation; copula function; Monte Carlo simulation; time until default portfolio credit risk; asset correlation; coherent capital allocation; copula function; Monte Carlo simulation; time until default
MDPI and ACS Style

Di Clemente, A. Modeling Portfolio Credit Risk Taking into Account the Default Correlations Using a Copula Approach: Implementation to an Italian Loan Portfolio. J. Risk Financial Manag. 2020, 13, 129.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop