Feedforward versus recurrent neural networks for forecasting monthly Japanese yen exchange rates

DOI10.1007/BF00868008zbMath1153.91783MaRDI QIDQ1000399

Milton S. Boyd, Nowrouz Kohzadi, Iebeling Kaastra, Bahman Kermanshahi, Giovani Dematos

Publication date: 6 February 2009

Published in: Financial Engineering and the Japanese Markets (Search for Journal in Brave)

zbMATH Keywords

forecastrecurrent neural networksARIMAfeedforward neural networksjapanese yen/US dollar exchange rate

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Economic time series analysis (91B84) Neural networks for/in biological studies, artificial life and related topics (92B20) Statistical methods; economic indices and measures (91B82)

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Cites Work

• Multilayer feedforward networks are universal approximators
• A logical calculus of the ideas immanent in nervous activity
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