A neural network based multi-class trading strategy for the S\&P 500 index

DOI10.1007/978-3-030-93699-0_6OpenAlexW4214826711MaRDI QIDQ2100518

Christoph Lohrmann, Pasi Luukka, Leo Soukko

Publication date: 22 November 2022

Full work available at URL: https://doi.org/10.1007/978-3-030-93699-0_6

zbMATH Keywords

thresholdsneural networkstrading strategyS\&P 500 indexmulti-class problem

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Financial markets (91G15)

Uses Software

• ElemStatLearn

Cites Work

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• 10.1162/153244303322753616
• Improving Stock Closing Price Prediction Using Recurrent Neural Network and Technical Indicators
• Prediction of Stock Market Index Movement by Ten Data Mining Techniques
• Random forests

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