A Decision Support System for Hedge Transactions in Electrical Energy Commercialization
Agents in the electricity sector may find themselves in a short position in the market at times. In this case, they have the option of hedging their risk by contracting part or all of their position through fixed-price forward contracts. If the hedge is only partial, the non-contracted portion must be settled at an uncertain future spot price, which exposes the agent to price risk. On the other hand, while a full hedge eliminates the risk, it eliminates potential gains. This Python code proposes an optimization model that maximizes the agent´s returns subject to a CVaR risk preference function to support the hedging decision.
Authors and contact: Naielly Lopes Marques (firstname.lastname@example.org), Jonas Caldara Pelajo (email@example.com), Leonardo Lima Gomes (firstname.lastname@example.org), and Luiz Eduardo Teixeira Brandao (email@example.com). Institution: Pontifical Catholic University of Rio de Janeiro (PUC-RJ). Department: IAG Business School
Purpose: This Python code helps researchers and practitioners apply a hedging model that maximizes the agent's profits subject to a desired level of risk protection, where we assume that the agent has a risk aversion level that can be measured by percentiles of Conditional Value at Risk – CVaR.
Paper: A Decision Support System for Hedge Transactions in Electrical Energy Commercialization
Last update: December 17th, 2021