dc.contributor.author | Gianfreda, Angelica | |
dc.contributor.author | Ravazzolo, Francesco | |
dc.contributor.author | Rossini, Luca | |
dc.date.accessioned | 2018-01-15T15:53:45Z | |
dc.date.available | 2018-01-15T15:53:45Z | |
dc.date.issued | 2018-01 | |
dc.identifier.issn | 1892-2198 | |
dc.identifier.uri | http://hdl.handle.net/11250/2477647 | |
dc.description.abstract | This paper compares alternative univariate versus multivariate models, probabilistic versus
Bayesian autoregressive and vector autoregressive specifications for hourly day-ahead electricity
prices, with and without renewable energy sources. The accuracy of point and density forecasts
are 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 VAR
specifications with exogenous variables dominate other multivariate and univariate specifications,
in terms of both point and density forecasting. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | BI Norwegian Business School, Centre for Applied Macro- and Petroleum Economics | nb_NO |
dc.relation.ispartofseries | CAMP Working Paper Series;2 | |
dc.subject | Density Forecasting | nb_NO |
dc.subject | Electricity Market | nb_NO |
dc.subject | Forecasting | nb_NO |
dc.subject | Hourly Prices | nb_NO |
dc.subject | Renewable Energies | nb_NO |
dc.title | Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration | nb_NO |
dc.type | Working paper | nb_NO |
dc.source.pagenumber | 36 | nb_NO |