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Modeling Electricity Price and Quantity Uncertainty: An Application for Hedging with Forward Contracts

Alfredo Trespalacios (), Lina Cortés () and Javier Perote ()
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Alfredo Trespalacios: Department of Finance, Faculty of Economic and Administrative Sciences, Instituto Tecnológico Metropolitano, ITM, Medellin 050022, Colombia

Energies, 2021, vol. 14, issue 11, 1-26

Abstract: Energy transactions in liberalized markets are subject to price and quantity uncertainty. This paper considers the spot price and energy generation to follow a bivariate semi-nonparametric distribution defined in terms of the Gram–Charlier expansion. This distribution allows us to jointly model not only mean, variance, and correlation but also skewness, kurtosis, and higher-order moments. Based on this model, we propose a static hedging strategy for electricity generators that participate in a competitive market where hedging is carried out through forward contracts that include a risk premium in their valuation. For this purpose, we use Monte Carlo simulation and consider information from the Colombian electricity market as the case study. The results show that the volume of energy to be sold under long-term contracts depends on each electricity generator and the risk assessment made by the market in the forward risk premium. The conditions of skewness, kurtosis, and correlation, as well as the type of the employed risk indicator, affect the hedging strategy that each electricity generator should implement. A positive correlation between the spot price and energy production tends to increase the hedge ratio; meanwhile, negative correlation tends to reduce it. The increase of forward risk premium, on the other hand, reduces the hedge ratio.

Keywords: semi-nonparametric approach; multivariate distribution; electricity markets; forward contracts (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: 2021
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Working Paper: Modeling electricity price and quantity uncertainty: An application for hedging with forward contracts (2020) Downloads
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