Hedging Wind Power Risk Exposure through Weather Derivatives

Giovanni Masala, Marco Micocci and Andrea Rizk
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Giovanni Masala: Department of Economics and Business Sciences, University of Cagliari, Via S. Ignazio 74, 09123 Cagliari, Italy
Marco Micocci: Department of Economics and Business Sciences, University of Cagliari, Via S. Ignazio 74, 09123 Cagliari, Italy
Andrea Rizk: Department of Statistics Sciences, University of Rome La Sapienza, 00185 Rome, Italy

Energies, 2022, vol. 15, issue 4, 1-30

Abstract: We introduce the industrial portfolio of a wind farm of a hypothetical company and its valuation consistent with the financial market. Next, we propose a static risk management policy originating from hedging against volumetric risk due to drops in wind intensity and we discuss the consequences. The hedging effectiveness firstly requires adequate modeling calibration and an extensive knowledge of these atypical financial (commodity) markets. In this hedging experiment, we find significant benefits for weather-sensitive companies, which can lead to new business opportunities. We provide a new financial econometrics approach to derive weather risk exposure in a typical wind farm. Our results show how accurate risk management can have a real benefit on corporate revenues. Specifically, we apply the spot market price simulation (SMaPS) model for the spot price of electricity. The parameters are calibrated using the prices of the French day-ahead market, and the historical series of the total hourly load is used as the final consumption. Next, we analyze wind speed and its relationship with electricity spot prices. As our main contribution, we demonstrate the effects of a hypothetical hedging strategy with collar options implemented against volumetric risk to satisfy demand at a specific time. Regarding the hedged portfolio, we observe that the “worst value” increases considerably while the earnings-at-risk (EaR) decreases. We consider only volumetric risk management, thus neglecting the market risk associated with electricity price volatility, allowing us to conclude that the hedging operation of our industrial portfolio provides substantial benefits in terms of the worst-case scenario.

Keywords: risk management; wind farms; weather risk; weather derivatives; value-at-risk; day-ahead electricity prices (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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