… how penalized regression models such as Firth’s estimator, … scoring models, are widely
used in finance and banking. … use of generalized extreme value (GEV) regression for modelling …

… for estimating credit losses. As a result, even minor improvements in the predictive strength
of credit scoring models could have a substantial financial … of default, we will fit our models to …

… We estimate the probability of default on credit risk data for corporate and retail clients.2.
We compare support vector machines (SVM) and logistic regression (LR).3. The SVM model …

… absolute value of the standardised estimates can serve to provide an approximate ranking of
the relative importance of the input variables on the fitted logistic model (… regression models …

… We propose estimating a model for Loss Given Default (LGD) … link function given by the
Generalised Extreme Value (GEV) … To estimate the GAMLSS beta regression model on all the …

… identified to anticipate and prevent bank defaults. The data, which … similarly to conventional
regression models. Although XGBoost … The authors’ estimates from a multi-period logit model …

… are shown to be much more successful than traditional regression analysis [47]. Indeed, …
We dropped all of the banks for which it was not possible to calculate the proxies for all the …

… bank defaults. Identifying leading indicators of … banking failure model's generalization
capabilities and avoid problems of overfitting. For each parameter combination, we will calculate …

… extreme value theory, the Financial System Dependence Index (FSDI) which uses the spread
of Credit Default Swaps (CDS) of financial … to estimate their impacts on the financial system. …

… literature of extremes concerns the tail index estimation, which governs the probability of …
S&P500 absolute log-returns. Indeed, it is well known that the absolute value of financial returns …