Title
An Arctan-Activated WASD Neural Network Approach to the Prediction of Dow Jones Industrial Average.
Abstract
Accurate prediction of the stock market index is a very challenging task due to the highly nonlinear characteristic of financial time series. For this reason, a single hidden-layer feed-forward neural network, activated by the arctan function, is proposed and investigated for predicting the Dow Jones Industrial Average. Then, a weights and structure determination (WASD) method is exploited to train the proposed arctan-activated neural network (termed arctan-activated WASD neural network). The relatively optimal weight and structure could be obtained by the presented WASD method. Numerical experiments are carried out based on huge amounts of historical data. The experimental results demonstrate the effectiveness and superior abilities of the arctan-activated WASD neural network for predicting the Dow Jones Industrial Average.
Year
DOI
Venue
2017
10.1007/978-3-319-59072-1_15
ADVANCES IN NEURAL NETWORKS, PT I
Keywords
Field
DocType
Arctan,WASD neural network,Prediction,Dow Jones Industrial Average
Nonlinear system,Stock market index,Computer science,Artificial intelligence,Artificial neural network,Machine learning,Inverse trigonometric functions
Conference
Volume
ISSN
Citations 
10261
0302-9743
0
PageRank 
References 
Authors
0.34
4
5
Name
Order
Citations
PageRank
Bolin Liao128118.70
Chuan Ma281.67
Lin Xiao356242.84
Rongbo Lu41015.12
Lei Ding514226.77