Using Machine Learning to Profit on the Risk Premium of the Nordic Electricity Futures

• Autor(a) principal: Sebastião, Helder
• Data de Publicação: 2020
• Outros Autores: Godinho, Pedro, Westgaard, Sjur
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10316/106722; https://doi.org/10.47743/saeb-2020-0024
• topic: electricity futures;; machine learning;; Nord Pool;; risk premium; trading

This study investigates the use of several trading strategies, based on Machine Learning methods, to profit on the risk premium of the Nordic electricity base-load week futures. The information set is only composed by financial data from January 02, 2006 to November 15, 2017. The results point out that the Support Vector Machine is the best method, but, most importantly, they highlight that all individual models are valuable, in the sense that their combination provides a robust trading procedure, generating an average profit of at least 26% per year, after considering trading costs and liquidity constraints. The results are robust to the different data partitions, and there is no evidence that the profitability of the trading strategies has decreased in recent years. We claim that this market allows for profitable speculation, namely by using combinations of non-linear signal extraction techniques.