Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case

In this work, we investigate a probabilistic method for electricity price forecasting, which overcomes traditional ones. We start considering statistical methods point forecast, comparing their performance in terms of efficiency, accuracy, and reliability, then exploit Neural Networks approaches to derive hybrid model type forecasting. show that our solution reaches the highest standard both efficiency precision by testing its output on German prices data.