Exploration of stock index change prediction model based on the combination of principal component analysis and artificial neural network

In order to establish an accurate effective stock forecasting model, the principal component analysis (PCA) was first used to analyze the main financial index data of some listed companies and the comprehensive score of evaluation index was obtained in this study. Then, the financial indicator data...

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Veröffentlicht in:	Soft computing (Berlin, Germany) Jg. 24; H. 11; S. 7851 - 7860
Hauptverfasser:	Cao, Jiasheng, Wang, Jinghan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2020 Springer Nature B.V
Schlagworte:	Accuracy Algorithms Artificial Intelligence Artificial neural networks Back propagation networks Computational Intelligence Control Economic development Engineering Financial management Focus Fourier transforms Investment policy Investments Investors Market economies Market prices Mathematical Logic and Foundations Mechatronics Methods Neural networks Performance evaluation Prediction models Principal components analysis Regularization Robotics Securities markets Small & medium sized enterprises-SME Stock exchanges Support vector machines Time series Variables China Investment guidance BP neural network Bayesian regularization algorithm Stock price forecasting Principal component analysis
ISSN:	1432-7643, 1433-7479
Online-Zugang:	Volltext
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