Which model computes the probability of default through peer set analysis?

The CreditMetrics Model computes the probability of default through peer set analysis by utilizing a systematic approach to measuring credit risk in a portfolio. This model is particularly focused on assessing the credit quality of a group of borrowers within a similar context or industry, meaning it examines how the creditworthiness of individual entities is affected by the performance of their peers. This method allows for a more refined estimate of default probabilities as it takes into account relative evaluations among similar entities, reflecting the interconnected risks that firms face within the same sector or geographical region.

By utilizing peer set analysis, the CreditMetrics Model enhances the understanding of default risk by identifying trends and correlations in credit risk among a specified group of firms, leading to a more comprehensive risk assessment. The model also facilitates the estimation of transition probabilities between different credit ratings, accounting for changes in the economic environment and how they can collectively influence default probabilities.

This model also incorporates historical data and statistical methodologies to refine its calculations, ultimately yielding a probability of default that is not solely based on an individual borrower's characteristics but also on the performance and health of its peer group, making it a robust tool for risk management.