In this article, the dependence of aggregated recovery rates on various explanatory variables is examined. This study is based on a unique dataset covering almost 40000 individual resolved defaulted loans and using a consistent definition of default and recovery over different jurisdictions. Markov switching techniques are applied to show that the distribution of recovery rates and their dependence on explanatory variables may vary between different states. Furthermore, recovery rates are differentiated according to their securisation and it is shown that more than 60 percent of the variation of recovery rates from unsecured facilities can be explained by three factors: the first describes the shortterm interest rates, the second the macroeconomic environment, and finally the third the uncertainty in credit markets.
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In this article, the dependence of aggregated recovery rates on various explanatory variables is examined. This study is based on a unique dataset covering almost 40000 individual resolved defaulted loans and using a consistent definition of default and recovery over different jurisdictions. Markov switching techniques are applied to show that the distribution of recovery rates and their dependence on explanatory variables may vary between different states. Furthermore, recovery rates are differ...
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