A Stock Market Forecasting Model Combining Two-Directional Two-Dimensional Principal Component Analysis and Radial Basis Function Neural Network

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)(2)PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input featur...

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Detalles Bibliográficos
Autores principales: Guo, Zhiqiang, Wang, Huaiqing, Yang, Jie, Miller, David J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4388524/
https://www.ncbi.nlm.nih.gov/pubmed/25849483
http://dx.doi.org/10.1371/journal.pone.0122385

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4388524/
https://www.ncbi.nlm.nih.gov/pubmed/25849483
http://dx.doi.org/10.1371/journal.pone.0122385

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