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• W2916819811 startingPage "104567" @default.
• W2916819811 abstract "A negative dependence between wind power production and electricity spot price exists. This is an important fact to consider for risk management of long-term power purchase agreements (PPAs). In this study we investigate this dependence by constructing a joint model using constant as well as time-varying copulas. We propose to use score-driven models as marginal model for the spot price of electricity as these are more robust to extreme events compared to ARMA–GARCH models. We apply the new model to pricing and risk management of PPAs and benchmark it against the ARMA–GARCH specification. Our comparison shows that the score-driven model results in a statistically significant improvement of predicting the Value-at-Risk (VaR), which is of high importance for risk management of long-term PPAs. Further, comparing constant and time–varying copulas we find that all time-varying copulas are significantly better than their constant counterparts at predicting the VaR, hence time–varying copulas should be used in risk management of PPAs." @default.
• W2916819811 created "2019-03-02" @default.
• W2916819811 creator A5038499344 @default.
• W2916819811 creator A5057306259 @default.
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• W2916819811 date "2020-01-01" @default.
• W2916819811 modified "2023-09-30" @default.
• W2916819811 title "Managing volumetric risk of long-term power purchase agreements" @default.
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• W2916819811 doi "https://doi.org/10.1016/j.eneco.2019.104567" @default.
• W2916819811 hasPublicationYear "2020" @default.
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