Platinum and palladium price forecasting through neural networks

To many commodity market participants, forecasts of price series represent a critical task. In this work, nonlinear autoregressive neural network models' potential is explored for forecasting daily prices series of platinum and palladium over about a fifty-year period. For this purpose, one hun...

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Veröffentlicht in:	Communications in statistics. Simulation and computation Jg. 54; H. 8; S. 2959 - 2973
Hauptverfasser:	Xu, Xiaojie, Zhang, Yun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Philadelphia Taylor & Francis 03.08.2025 Taylor & Francis Ltd
Schlagworte:	Commodities Forecasting Machine learning Neural network Neural networks Palladium Platinum Policy analysis Price forecasting Pricing Time series
ISSN:	0361-0918, 1532-4141
Online-Zugang:	Volltext
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