Credit portfolio modelling

A false sense of security

Credit portfolio models often assume that recovery rates are independent of default probabilities. Here, Jon Frye presents empirical evidence showing that such assumptions are wrong. Using US historical default data, he shows that not only are recovery…

A false sense of security

Credit portfolio models often assume that recovery rates are independent of defaultprobabilities. Here, Jon Frye presents empirical evidence showing that such assumptions arewrong. Using US historical default data, he shows that not only are recovery…

Enhancing CreditRisk+

Of the various analytical approaches to credit portfolio modelling, CreditRisk+ has become the most popular due to its tractability. However, the model suffers from the restrictive assumption of sector independence. Moreover, the recursion relation for…

Calculating portfolio loss

For credit portfolios, analytical methods work best for tail risk, while Monte Carlo is used to model expected loss. However, products such as CDOs require a model for the entire distribution. Sandro Merino and Mark Nyfeler meet the challenge by…

Analytical approach to credit risk modelling

The increasing popularity of VAR-based credit portfolio risk models has led to a growing recognition that Monte Carlo techniques are inadequate for economic capital calculations. Here, Michael Pykhtin and Ashish Dev present a new analytical alternative…

Probing granularity

The granularity adjustment, which adjusts risk weightings for credit portfolio diversification, is one of Basel II’s key modelling assumptions. Here, Tom Wilde uncovers a weakness in this assumption arising from the differences in the underlying credit…

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