In this paper we propose the use of an asymmetric binary link function to extend the proportional hazard model for predicting loan default. The rationale behind this approach is that the symmetry assumption, that has been widely used in the literature, could be considered as quite restrictive,...

This papers provides clear cut evidence that recessionary and financial distressed conditions, as well as banning foreclosure laws, often introduced by governments to mitigate the effects of the economic and/or financial distressed conditions on mortgage loans, have adverse effects on the loan...

This paper suggests using a multilayer artificial neural network (ANN) method, known as deep learning ANN, to predict the probability of default (PD) within the survival analysis framework. Deep learning ANN structures consider hidden interconnections among the covariates determining the PD...

In this paper we develop a discrete-time pricing model for European options where the log-return of the underlying asset is subject to discontinuous regime shifts in its mean and/or volatility which follow a Markov chain. The model allows for multiple regime shifts whose risk cannot be hedge out...

This paper suggests a multilayer artificial neural network (ANN) method to predict the probability of default (PD) within the survival analysis framework. ANN structures consider hidden interconnections among covariates determining the PD which can lead to prediction improvements, compared to...

We investigate the relationship between non-performing loans (NPLs) and their fundamentals, mainly bank and macroeconomic variables. This is done based on aggregate portfolio loans in the Greek economy. Greece constitutes an interesting case to study the factors determining NPLs, given the...

This paper evaluates the VaR forecasting performance of the Markov regime switching (MRS) based volatility models, allowing for EGARCH effects. As is argued in the literature, this extension of the MRS model model may improve its forecasting performance due to its ability to capture leverage...