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A Decision Support System for Hedge Transactions in Electrical Energy Commercialization
- Citation Author(s):
-
NaiellyMarques
Pontifical Catholic University of Rio de JaneiroJonasPelajoPontifical Catholic University of Rio de JaneiroLeonardoGomesPontifical Catholic University of Rio de JaneiroLuizBrandãoPontifical Catholic University of Rio de Janeiro - Submitted by:
- Naielly Marques
- Last updated:
- Tue, 01/04/2022 - 08:55
- DOI:
- 10.21227/h2j6-bf33
- License:
234 Views- Categories:
- Keywords:
Abstract
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 (naielly.lopes@iag.puc-rio.br), Jonas Caldara Pelajo (jonas.caldara@iag.puc-rio.br), Leonardo Lima Gomes (leonardoli-ma@iag.puc-rio.br), and Luiz Eduardo Teixeira Brandao (brandao@iag.puc-rio.br). 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
