institutions to develop accurate loss models. This work investigates the loss given default (LGD) of mortgage loans using a large … Repossession Model should consist of more than just the commonly used loan-to-value ratio, and that the estimation of LGD benefits …-stage LGD model is shown to perform better than a single-stage LGD model (which models LGD directly from loan and collateral …

include another parameter loss given default (LGD), the share of the loan which cannot be recovered in case of loan default in … large, highdimensional, real world dataset is used to benchmark several combinations of classification, regression and …

much less on LGD modeling. In this first large-scale LGD benchmarking study, various regression techniques for modeling and … predicting LGD are investigated. These include one-stage models, such as those built by ordinary least squares regression, beta … risk models for three key risk parameters: PD (probability of default), LGD (loss given default) and EAD (exposure at …

, we derive a closed-form expression for European call option prices. We also suggest a regression tree-based method for …

A new quantile regression model for survival data is proposed that permits a positive proportion of subjects to become … proposals for quantile regression estimation of censored survival models, we propose a new "data augmentation" approach to …