learning in the context of energy economics and presenting an exemplary application to electricity load data. For this, we …

Electricity price forecasting has become an area of increasing relevance in recent years. Despite the growing interest … proposes a new univariate hybrid model, trained, and tested on German electricity market data, based on the Seasonal Auto … and actual prices. The ability to predict the dynamics of the price of electricity on the spot market is an important …

, estimation of time-varying forecast biases and facets of miscalibration of individual forecast densities and time-varying inter …

(UVAR) andBayesian (BVAR) perspective. The package includes functionalities forthe speci cation, estimation and diagnosis of …

the major risk exposure for many investors in energy is the volatility of the electricity price, our motivation stems from …, one model may outperform its peers for one country's wholesale electricity price but not necessarily for other markets … volatility in electricity markets …

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors …

UK, the Euro area and Japan, over an estimation period spanning from 1960 to 2012. We find that the relationship between … money growth and inflation appears to be nonlinear, as our estimation results identify multiple inflation regimes displaying …