We propose a dynamic model of mortgage credit losses, which is a generalization of the wellknown Vasicek's model of loss distribution. We assume borrowers hold assets covering the instalments and own real estate which serves as collateral. Both the value of the assets and the price of the estate follow general stochastic processes driven by common and individual factors. We describe the correspondence between the common factors and the percentage of defaults, and the loss given default, respectively, and we suggest a procedure of econometric estimation in the model. On an empirical dataset we show that a more accurate estimation of common factors can lead to savings in capital needed to hold against a quantile loss
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We propose a dynamic model of mortgage credit losses, which is a generalization of the wellknown Vasicek's model of loss distribution. We assume borrowers hold assets covering the instalments and own real estate which serves as collateral. Both the value of the assets and the price of the estate follow general stochastic processes driven by common and individual factors. We describe the correspondence between the common factors and the percentage of defaults, and the loss given default, respectively, and we suggest a procedure of econometric estimation in the model. On an empirical dataset we show that a more accurate estimation of common factors can lead to savings in capital needed to hold against a quantile loss
