A CNN–LSTM model for gold price time-series forecasting

Gold price volatilities have a significant impact on many financial activities of the world. The development of a reliable prediction model could offer insights in gold price fluctuations, behavior and dynamics and ultimately could provide the opportunity of gaining significant profits. In this work...

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Veröffentlicht in:	Neural computing & applications Jg. 32; H. 23; S. 17351 - 17360
Hauptverfasser:	Livieris, Ioannis E., Pintelas, Emmanuel, Pintelas, Panagiotis
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.12.2020 Springer Nature B.V
Schlagworte:	Artificial Intelligence Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Deep learning Forecasting Gold Image Processing and Computer Vision Machine learning Mathematical models Prediction models Probability and Statistics in Computer Science S.I. : Emerging applications of Deep Learning and Spiking ANN Deep learning Gold price forecasting Convolutional neural networks Time series
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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