Generalized Asset Value Credit Risk Models and Risk Minimality of the Classical Approach

Wehrspohn, Uwe

doi:10.2139/ssrn.404920

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…The generalized asset value model (for details see Wehrspohn (2002), pp. 112ff., Wehrspohn (2003)) extends the classical model in the way that the normal distribution as asset return distribution is replaced by a general variance mixture of normals. This is an important topic for testing because it can be shown that tail-risk increases for any deviations from the normal distribution as asset return distribution in the generalized asset value model (Wehrspohn (2003)).…”

Section: An Examplementioning

confidence: 99%

“…Figures 5 and 6 present the results for deviations from the normal distribution as asset return distribution. The choice of the asset return distribution is critical in the generalized asset value model because it can be shown that tail-risk and, thus, values at risk and shortfalls at high confidence levels increase for any deviations from the normal distribution as asset return distribution (Wehrspohn (2003)). Note that small deviations from the normal distribution, i.e.…”

Section: An Examplementioning

confidence: 99%

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Optimal Simultaneous Validation Tests of Default Probabilities, Dependencies, and Credit Risk Models

Wehrspohn

2004

SSRN Journal

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Section: An Examplementioning

confidence: 99%

Section: An Examplementioning

confidence: 99%

Optimal Simultaneous Validation Tests of Default Probabilities, Dependencies, and Credit Risk Models

Wehrspohn

2004

SSRN Journal

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“…To generate a scenario from the Student's t copula with ν degrees of freedom by a one-factor model (see Frey and McNeil 2003;Wehrspohn 2003), it is sufficient to transform Equation (14) as follows:…”

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

Clemente

2020

JRFM

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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.

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The Study on the Loan Risk Pricing of the Bank in Internal Rating-Based Approach

Wang

Liu

2008

2008 International Conference on Risk Management &Amp; Engineering Management

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Generalized Asset Value Credit Risk Models and Risk Minimality of the Classical Approach

Cited by 4 publications

References 8 publications

Optimal Simultaneous Validation Tests of Default Probabilities, Dependencies, and Credit Risk Models

Optimal Simultaneous Validation Tests of Default Probabilities, Dependencies, and Credit Risk Models

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

The Study on the Loan Risk Pricing of the Bank in Internal Rating-Based Approach

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