Technical paper/Loss given default (LGD)
Modeling the current loan-to-value structure of mortgage pools without loan-specific data
This paper presents a method for approximating the current loan-to-value (CLTV) and remaining principal structures of heterogeneous mortgage loan pools.
Estimating credit risk parameters using ensemble learning methods: an empirical study on loss given default
This study investigates two well-established ensemble learning methods: Stochastic Gradient Boosting and Random Forest, and proposed two new ensembles.
Loss given default modeling: an application to data from a Polish bank
This paper compares two methods of estimating LGD: a beta regression model and a multinomial logit (MNL) model.
The simple link from default to LGD
The simple link from default to LGD
Systematic risk factors redefined
Systematic risk factors redefined
Breaking break clauses
Breaking break clauses
Counterparty risk capital and CVA
Counterparty risk capital and CVA
Empirical performance of loss given default prediction models
Research Papers
Risky funding with counterparty and liquidity charges
Risky funding with counterparty and liquidity charges
Name concentration correction
Credit Risk
Name concentration correction
Name concentration correction