Prediction methods have garnered significant attention in intelligent decision-making. Most existing approaches to predicting crude oil prices prioritize accuracy and stability while providing precise prediction intervals that can offer valuable insights. Thus far, we introduced a novel hybrid...

This study develops a framework for forecasting selected balance sheet items of the four largest Maltese core banks, with a particular emphasis on bank profitability. Methodologically, it employs two multivariate time series models, namely a Factor-Augmented VAR (FAVAR) and a Bayesian VAR...

This study develops a framework for forecasting selected balance sheet items of the four largest Maltese core banks, with a particular emphasis on bank profitability. Methodologically, it employs two multivariate time series models, namely a Factor-Augmented VAR (FAVAR) and a Bayesian VAR...

There is an increasing risk of outbreaks escalating into epidemics, despite huge advances in medical science. Epidemics like COVID-19, Monkeypox, Influenza and HIV have been affecting people and public health infrastructure at an alarming rate around the world. COVID-19 alone has infected more...

This study firstly applied a Bayesian symbolic regression (BSR) to the forecasting of numerous commodities' prices (spot-based ones). Moreover, some features and an initial specification of the parameters of the BSR were analysed. The conventional approach to symbolic regression, based on...

In recent years, there is an increasing trend in non-performing loan levels in Turkey which causes stress both on the real and financial sectors. Increasing non-performing loan volumes are an indication of problems in sectors or the general economy. It is also closely related with the stability...