Jordan neural network for inflation forecasting

DOI10.17535/crorr.2019.0003zbMath1470.91184OpenAlexW2954290918WikidataQ127558758 ScholiaQ127558758MaRDI QIDQ5147600

Tea Šestanović

Publication date: 27 January 2021

Published in: Croatian Operational Research Review (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.17535/crorr.2019.0003

zbMATH Keywords

recurrent neural networksinflation forecasting

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Macroeconomic theory (monetary models, models of taxation) (91B64) Statistical methods; economic indices and measures (91B82)

Cites Work

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• Multilayer feedforward networks are universal approximators
• Predictable non-linearities in U.S. inflation
• Static, dynamic, and hybrid neural networks in forecasting inflation
• AI 2005: Advances in artificial intelligence. 18th Australian joint conference on artificial intelligence, Sydney, Australia, December 5--9, 2005. Proceedings
• GARCH based artificial neural networks in forecasting conditional variance of stock returns
• TOOLS FOR NON-LINEAR TIME SERIES FORECASTING IN ECONOMICS – AN EMPIRICAL COMPARISON OF REGIME SWITCHING VECTOR AUTOREGRESSIVE MODELS AND RECURRENT NEURAL NETWORKS

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