Machine Learning on EPEX Order Books: Insights and Forecasts

Simon Schn\"urch and Andreas Wagner

Papers from arXiv.org

Abstract: This paper employs machine learning algorithms to forecast German electricity spot market prices. The forecasts utilize in particular bid and ask order book data from the spot market but also fundamental market data like renewable infeed and expected demand. Appropriate feature extraction for the order book data is developed. Using cross-validation to optimise hyperparameters, neural networks and random forests are proposed and compared to statistical reference models. The machine learning models outperform traditional approaches.

Date: 2019-06, Revised 2019-09
New Economics Papers: this item is included in nep-big, nep-cmp, nep-ene, nep-for and nep-pay
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Citations: View citations in EconPapers (5)

Published in Applied Mathematical Finance 27 (2020) 189-206

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1906.06248

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