Title :
Stock market prediction by using artificial neural network
Author :
Yetis, Yunus ; Kaplan, Halid ; Jamshidi, Mo
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Texas at San Antonio, San Antonio, TX, USA
Abstract :
A neural networks based model have been used in predicting of the stock market. One of the methods, as an intelligent data mining, is artificial neural network (ANN). In this paper represents how to predict a NASDAQ´s stock value using ANNs with a given input parameters of share market. We used real exchange rate value of NASDAQ Stock Market index. This paper makes use generalized feed forward networks. The network was trained using input data of stock market price in between 2012 and 2013. It shows a good performance for NASDAQ stock market prediction.
Keywords :
data mining; feedforward neural nets; financial data processing; stock markets; ANN; NASDAQ Stock Market index; NASDAQ stock value; artificial neural network; data mining; exchange rate value; generalized feedforward networks; share market; stock market prediction; Artificial neural networks; Testing; Training; Artificial Neural Networks; Prediction; Stock Market;
Conference_Titel :
World Automation Congress (WAC), 2014
Conference_Location :
Waikoloa, HI
DOI :
10.1109/WAC.2014.6936118
