A primer on the pricing of electric energy options in Brazil via mean-reverting stochastic processes

Research output: Contribution to journalArticlepeer-review

Authors

External organisations

  • Universidade Tecnológica Federal do Paraná, Departamento de Administração
  • Université Laval

Abstract

Pricing option contracts on electricity remains methodologically challenging, with a lack of clearly defined and robust methods. In particular, little is known about pricing options in Brazilian energy markets, despite their economic significance. Using weekly price data (R$/MWh) on four electrical subsystems from the Chamber for Commercialization of Electrical Energy, we estimate models to price Brazilian electricity energy options. This paper has three objectives: i) to identify the occurrence of change-points (regime-switching) in time series of Brazilian energy spot prices; ii) to determine the best Stochastic Differential Equation (SDE) with which to model Brazilian energy spot prices and iii) to price five types of options used to manage electricity price risk in Brazil. We show that the change-point occurred between 2002 and 2018. During this period, the long-run marginal cost of production was the most affected. Furthermore, we find that the Ornstein-Uhlenbeck/Vasicek stochastic process and resulting SDE best explains electricity prices in Brazil, even with the occurrence of structural changes. Finally, our results indicate that Asian-style options are the least costly option contracts to manage electricity price risk in Brazil.

Bibliographic note

Energy Reports’ is a considerably high impact journal. The impact factor of this specialized journal is 3.83 and hence it fits into the category of a ‘4 ABS’ journal publication (e.g. JCF (4 ABS) impact factor is 2.349, JFI (4 ABS) is 2.60, JMCB (4 ABS) is 2.18)

Details

Original languageEnglish
Article number206
Pages (from-to)594-601
Number of pages8
JournalEnergy Reports
Volume5
Early online date17 May 2019
Publication statusE-pub ahead of print - 17 May 2019

Keywords

  • Energy options, Stochastic processes, electricity sector