Recent studies document the deteriorating performance of forecasting models during the Great Moderation, which conversely implies that forecastability was higher in the preceding era when the economy was unexpectedly volatile. We explain this phenomenon in the context of equilibrium...

Artificial neural networks have become increasingly popular for statistical model fitting over the last years, mainly due to increasing computational power. In this paper, an introduction to the use of artificial neural network (ANN) regression models is given. The problem of predicting the GDP...

This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning...