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Homeen-gbA latent variable credit risk model comprising nonlinear dependencies in a sector framework with a stochastically dependent loss given defaultThis paper proposes a latent variable credit risk model for large loan portfolios. It employs the concept of nested Archimedean copulas to account for both a sector-type dependence structure and a copula-dependent stochastic loss given default (LGD).
https://www.risk.net/journal-of-credit-risk/5376681/a-latent-variable-credit-risk-model-comprising-nonlinear-dependencies-in-a-sector-framework-with-a-stochastically-dependent-loss-given-default
https://www.risk.net/journal-of-credit-risk/5376681/a-latent-variable-credit-risk-model-comprising-nonlinear-dependencies-in-a-sector-framework-with-a-stochastically-dependent-loss-given-default
Wed, 03 Jan 2018 14:22:55 +0000 Stochastic loss given default and exposure at default in a structural model of portfolio credit riskThe authors develop a factor-type latent variable model for portfolio credit risk that accounts for stochastically dependent probability of default (PD), loss given default (LGD) and exposure at default (EAD) at both the systematic and borrower specific levels.
https://www.risk.net/journal-of-credit-risk/3937681/stochastic-loss-given-default-and-exposure-at-default-in-a-structural-model-of-portfolio-credit-risk
https://www.risk.net/journal-of-credit-risk/3937681/stochastic-loss-given-default-and-exposure-at-default-in-a-structural-model-of-portfolio-credit-risk
Mon, 27 Feb 2017 10:05:47 +0000 Comparing risk measures when aggregating market risk and credit risk using different copulasThe authors of this paper simulate realistic total bank return distributions by means of a top-down copula approach for different parameter settings.
https://www.risk.net/journal-of-risk/2460129/comparing-risk-measures-when-aggregating-market-risk-and-credit-risk-using-different-copulas
https://www.risk.net/journal-of-risk/2460129/comparing-risk-measures-when-aggregating-market-risk-and-credit-risk-using-different-copulas
Wed, 08 Jun 2016 13:25:00 +0100