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dc.contributor.authorGianfreda, Angelica
dc.contributor.authorRavazzolo, Francesco
dc.contributor.authorRossini, Luca
dc.date.accessioned2018-01-15T15:53:45Z
dc.date.available2018-01-15T15:53:45Z
dc.date.issued2018-01
dc.identifier.issn1892-2198
dc.identifier.urihttp://hdl.handle.net/11250/2477647
dc.description.abstractThis 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.isoengnb_NO
dc.publisherBI Norwegian Business School, Centre for Applied Macro- and Petroleum Economicsnb_NO
dc.relation.ispartofseriesCAMP Working Paper Series;2
dc.subjectDensity Forecastingnb_NO
dc.subjectElectricity Marketnb_NO
dc.subjectForecastingnb_NO
dc.subjectHourly Pricesnb_NO
dc.subjectRenewable Energiesnb_NO
dc.titleComparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetrationnb_NO
dc.typeWorking papernb_NO
dc.source.pagenumber36nb_NO


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