Modeling NYSE Composite US 100 Index with a Hybrid SOM and MLP-BP Neural Model

Modeling NYSE Composite US 100 Index with a Hybrid SOM and MLP-BP Neural Model

Neural networks are well suited to predict future results of time series for various data types. This paper proposes a hybrid neural network model to describe the results of the database of the New York Stock Exchange (NYSE). This hybrid model brings together a self organizing map (SOM) with a multi...

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Bibliographic Details
Main Authors: Adriano Beluco, Denise L. Bandeira, Alexandre Beluco
Format: Article
Language:English
Published: MDPI AG 2017-02-01
Series:Journal of Risk and Financial Management
Subjects:
modeling financial indicators
NYSE indexes
self organizing maps
multilayer perceptron
back propagation algorithm
software Matlab
Online Access:http://www.mdpi.com/1911-8074/10/1/6

Internet

http://www.mdpi.com/1911-8074/10/1/6

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