We compare alternative univariate versus multivariate models and frequentist versus Bayesian autoregressive and vector autoregressive specifications for hourly day-ahead electricity prices, both with and without renewable energy sources. The accuracy of point and density forecasts is inspected in four main European markets (Germany, Denmark, Italy, and Spain) characterized by different levels of renewable energy power generation. Our results show that the Bayesian vector autoregressive specifications with exogenous variables dominate other multivariate and univariate specifications in terms of both point forecasting and density forecasting
Electricity price forecasting is an interesting problem for all the agents involved in electricity m...
Electricity price forecasting is an interesting problem for all the agents involved in electricity m...
This empirical paper compares the accuracy of 12 time series methods for short-term (day-ahead) spot...
This paper compares alternative univariate versus multivariate models, probabilistic versus Bayesian...
This paper compares alternative univariate versus multivariate models, probabilistic versus Bayesian...
This paper compares alternative univariate versus multivariate models, frequentist versus Bayesian a...
This paper compares alternative univariate versus multivariate models, probabilistic versus Bayesian...
This paper studies the forecasting abilities of a battery of univariate models on hourly electricity...
This paper studies the forecasting abilities of a battery of univariate models on hourly electricity...
In this paper machine learning models are estimated to predict electricity prices. As it is well kno...
Electricity spot market prices are increasingly affected by an expanding amount of renewables and a ...
Using a newly available dataset about the unavailability of power plants and the in-feed of renewab...
Electricity spot prices exhibit strong time series properties, including substantial periodicity, bo...
This paper focuses on the day-ahead forecasting performance of some models for hourly electricity sp...
We analyse the importance of macroeconomic information, such as industrial production index and oil ...
Electricity price forecasting is an interesting problem for all the agents involved in electricity m...
Electricity price forecasting is an interesting problem for all the agents involved in electricity m...
This empirical paper compares the accuracy of 12 time series methods for short-term (day-ahead) spot...
This paper compares alternative univariate versus multivariate models, probabilistic versus Bayesian...
This paper compares alternative univariate versus multivariate models, probabilistic versus Bayesian...
This paper compares alternative univariate versus multivariate models, frequentist versus Bayesian a...
This paper compares alternative univariate versus multivariate models, probabilistic versus Bayesian...
This paper studies the forecasting abilities of a battery of univariate models on hourly electricity...
This paper studies the forecasting abilities of a battery of univariate models on hourly electricity...
In this paper machine learning models are estimated to predict electricity prices. As it is well kno...
Electricity spot market prices are increasingly affected by an expanding amount of renewables and a ...
Using a newly available dataset about the unavailability of power plants and the in-feed of renewab...
Electricity spot prices exhibit strong time series properties, including substantial periodicity, bo...
This paper focuses on the day-ahead forecasting performance of some models for hourly electricity sp...
We analyse the importance of macroeconomic information, such as industrial production index and oil ...
Electricity price forecasting is an interesting problem for all the agents involved in electricity m...
Electricity price forecasting is an interesting problem for all the agents involved in electricity m...
This empirical paper compares the accuracy of 12 time series methods for short-term (day-ahead) spot...