In der vorliegenden Arbeit untersuchen wir die Eignung der ifo-Geschäftserwartungen und der ZEW-Konjunkturerwartungen als Frühindikatoren für die deutsche Industrieproduktion. Anhand von Granger-Kausalitätstests wird gezeigt, dass die auf Umfragen unter Finanzanalysten basierenden...

The daily average price of electricity represents the price of electricity to be delivered over the full next day and serves as a key reference price in the electricity market. It is an aggregate that equals the average of hourly prices for delivery during each of the 24 individual hours. This...

One of the most pressing problems in the Latvian economy is related to the energy sector. The most characteristic feature is coupled with the low efficiency of thermal energy consumption of households as a result of poor insulation of existing buildings in Latvia. Solving energy sector problems...

One of the most pressing problems in the Latvian economy is related to the energy sector. The most characteristic feature is coupled with the low efficiency of thermal energy consumption of households as a result of poor insulation of existing buildings in Latvia. Solving energy sector problems...

This paper investigates whether structural breaks and long memory are relevant features in modeling and forecasting the conditional volatility of oil spot and futures prices using three GARCH-type models, i.e., linear GARCH, GARCH with structural breaks and FIGARCH. By relying on a modified...

We examine possible accuracy gains from using factor models, quantile regression and forecast averaging for computing interval forecasts of electricity spot prices. We extend the Quantile Regression Averaging (QRA) approach of Nowotarski and Weron (2014) and use principal component analysis to...

This paper proposes a novel method for assessing the predictability of energy market time series, by predicting the entropy of the series. According to conventional entropy-based analysis where the entropy is always ex-post estimated), high entropy values characterize unpredictable series, while...

Probabilistic load forecasting is becoming crucial in today's power systems planning and operations. We propose a novel methodology to compute interval forecasts of electricity demand, which applies a Quantile Regression Averaging (QRA) technique to a set of independent expert point forecasts....

Improvements in the building stock insulation and the replacement of heating systems will have to take place within the next decades in order to lower heat demand and the associated carbon emissions of the building sector. The current study presents an integrated, iterative modelling approach to...

We evaluate a recently proposed method for constructing prediction intervals, which utilizes the concept of quantile regression (QR) and a pool of point forecasts of different time series models.We find that in terms of interval forecasting of Nord Pool day-ahead prices the new QR-based approach...