Bank loan recovery rates: Measuring and nonparametric density estimation

In this paper we analyse a comprehensive database of 149,378 recovery rates on Italian bank loans. We investigate a new methodology to compute the recovery percentage that we suggest to consider as a mixed random variable. To estimate the probability density function of such a mixture, we propose the mixture of beta kernels estimator and we analyse its performance by Monte Carlo simulations. The application of these proposals to the Bank of Italy's data shows that, even if we remove the endpoints from the support of the recovery rate, the density function estimate is far from being a beta function.