Energy producers are challenged to contribute to a lower carbon economy and to enhance the decarbonization of this sector two sources highlight: electricity (mainly from renewables) and natural gas. To overcome the gap in the literature to model the dependence between electricity and natural gas prices in a context of energy transition, we propose a stochastic-copula approach where the stochastic component includes the observed stylized facts: seasonality, mean reversion and jumps. Using European electricity and natural gas day-ahead prices between 2015 and 2020, we estimate our suggested stochastic model and examine several copula functions. We find that energy firms are more exposed to price risk with the acceleration of the electrification of the economy and, therefore, producers tend to avoid a high exposure to the electricity volatility. Our findings are also relevant for policymakers since green investments should be promoted with economic mechanisms to fix the electricity price generated by renewables.

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Energy transition,Electricity,Natural gas,Copula functions,Jump-diffusion,Mean reversion

• Economics and Business - Social Sciences