A decision support system for hedge transactions in electrical energy commercialization
DOI:
https://doi.org/10.1590/1808-057x20252172.enKeywords:
energy commercialization, hedge, preference function, risk aversionAbstract
This article proposes an optimization model that maximizes the agent’s returns subject to a risk preference function to support the hedging decision. The originality lies in the development of a commercialization decision support model that maximizes the agent’s profits, customized to a desired level of risk protection, which is a gap in the literature. As this model is tailored to the agent’s individual risk aversion rather than the market as a whole, this model assists in defining, in a personalized manner, the optimal hedging strategy given the agent’s specific risk preferences. It assists the hedging decision maker in selecting the optimal purchasing strategy based on the level of risk the firm is willing to accept. We assume that the agent has an aversion to risk and adopt a preference function, considering their willingness to pay the risk premium and the transaction cost. The case of an agent in the Brazilian electricity sector interested in defining a hedging strategy for the 2nd semester is analyzed. In their day-to-day business, agents in the electricity sector may find themselves in a short position in the market. To mitigate their exposure to this risk, they have the option of entering into fixed-price forward contracts, either partially or in full. This study contributes to the development of an original decision support tool for these agents, considering their willingness to pay the risk premium and transaction costs. In our numerical application, results suggest covering 45.3% of uncontracted amounts in the 2nd semester. However, if the decision is made quarterly, a 100% hedge is recommended for the 3rd quarter and no hedge for the 4th. Sensitivity analyses are performed to show how the level of risk aversion impacts this decision.
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