We consider time series forecasting in the presence of ongoing structural change where both the time series dependence and the nature of the structural change are unknown. Methods that downweight older data, such as rolling regressions, forecast averaging over different windows and exponentially...

This paper explores a semiparametric version of a time-varying regression, where a subset of the regressors have a fixed coefficient and the rest a time-varying one. We provide an estimation method and establish associated theoretical properties of the estimates and standard errors in extended...

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...

In the years after the financial crisis low bank profitability has been a major issue. The increased regulation imposed in the wake of the crisis has often been accused of overburdening banks and contributing to low profitability. The euro area, consisting of 19 different economies, made a big...

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...

The scope of this paper is to examine if and how the establishment of the Single Supervisory Mechanism (SSM) influenced the profitability of European banks. To do so, we employ the returns on assets and equity as alternative indicators for profitability. Using data for 344 European banks in...

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 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...

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...