Recovery rates are besides default probabilities the second important component in credit-risk modelling. Whereas the determinants of default probabilities have been studied extensively in the last forty years, recovery risks have been neglected for a long time. Only in recent years, due to new regulatory requirements (e.g. Basel II) and an increasing number of defaults during the financial crisis starting in 2007, recovery rates have gained more interest from academics as well as from practitioners. In this article, the determinants of loan workout recovery rates are described and empirically tested; to the authors' best knowledge this is done for the first time based on such a broad Pan-European database (PECDC's LGD database) using a consistent definition of default and recovery rates over different jurisdictions. Hence, this study allows for an empirical comparison over different countries, industry sectors, and asset classes. We differentiate between facility-level and entity-level factors, factors that describe the collateralisation as well as the default process, and macroeconomic factors. Their impact on loan workout recovery rates is measured on a facility level. Our results support the importance of a sound modelling of recovery rates to avoid an underestimation of default loss risk in risk management as well as in pricing.
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Recovery rates are besides default probabilities the second important component in credit-risk modelling. Whereas the determinants of default probabilities have been studied extensively in the last forty years, recovery risks have been neglected for a long time. Only in recent years, due to new regulatory requirements (e.g. Basel II) and an increasing number of defaults during the financial crisis starting in 2007, recovery rates have gained more interest from academics as well as from practitio...
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