文章基本信息

标题：Using Machine Learning to Profit on the Risk Premium of the Nordic Electricity Futures
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作者：Helder Sebastião ; Pedro Godinho ; Sjur Westgaard 等
期刊名称：Scientific Annals of the “Alexandru Ioan Cuza” University of Iasi – Economic Sciences Series
印刷版ISSN：2501-1960
电子版ISSN：2501-3165
出版年度：2020
页码：1-17
DOI：10.47743/saeb-2020-0024
出版社：Sciendo
摘要：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.
关键词：Nord Pool;electricity futures;risk premium;machine learning;trading.