Electricity price forecasting has become an area of increasing relevance in recent years. Despite the growing interest in predictive algorithms, the challenges are difficult to overcome given the restricted access to relevant data series and the lack of accurate metrics. Multiple models have...

Forecasting hourly electricity prices and their characteristic properties is a core challenge for energy generation companies and trading houses. The short-term marketing and purchase of electricity is usually managed with standardized products traded on different markets and with specific...

The prompt availability of information on the current state of the economy in real-time is required for prediction purposes and crucial for timely policy adjustment and economic decision-making. While important macroeconomic indicators are reported only quarterly and also published with...

We develop a novel large-scale Network Autoregressive model with balance Constraint (NAC) to predict hour-ahead gas flows in the gas transmission network, where the total in- and out-flows of the network are balanced over time. By integrating recent advances in optimization and statistical...

Several approaches for subset recovery and improved forecasting accuracy have been proposed and studied. One way is to apply a regularization strategy and solve the model selection task as a continuous optimization problem. One of the most popular approaches in this research field is given by...

Obgleich es zahlreiche Institutionen gibt, die das deutsche Bruttoinlandsprodukt vorhersagen, mangelt es aktuell an sogenannten "Nowcasting"-Modellen, deren Prognosegüte mit jedem neu verfügbaren, das deutsche Bruttoinlandsprodukt beeinflussenden Datenpunkt verbessert wird. In der folgenden...

Several approaches for subset recovery and improved forecasting accuracy have been proposed and studied. One way is to apply a regularization strategy and solve the model selection task as a continuous optimization problem. One of the most popular approaches in this research field is given by...

This paper introduces a new approach to modelling the conditional variance in a multivariate setting. It is essentially a combination of the popular GARCH model class with a spatial component, inspired by generalized space-time models. The resulting spatial GARCH model takes into account both...

Obgleich es zahlreiche Institutionen gibt, die das deutsche Bruttoinlandsprodukt vorhersagen, mangelt es aktuell an sogenannten "Nowcasting"-Modellen, deren Prognosegüte mit jedem neu verfügbaren, das deutsche Bruttoinlandsprodukt beeinflussenden Datenpunkt verbessert wird. In der folgenden...

Commuting shapes countless everyday-lives around the world, with dynamics varying from city to regional and cross regional level. Taking as reference the free-movement EU-28 area (plus Switzerland and Norway), the analysis considers a total sample of 195 NUTS2 regions over the decade 2007-2017...