Stock price forecasting using ANN method

Title

Stock price forecasting using ANN method

Creator

Ravichandra T.; Thingom C.

Description

Ability to predict stock price direction accurately is essential for investors to maximize their wealth. Neural networks, as a highly effective data mining method, have been used in many different complex pattern recognition problems including stock market prediction. But the ongoing way of using neural networks for a dynamic and volatile behavior of stock markets has not resulted in more efficient and correct values. In this research paper, we propose methods to provide more accurately by hidden layer data processing and decision tree methods for stock market prediction for the case of volatile markets. We also compare and determine our proposed method against three layer feed forward neural network for the accuracy of market direction. From the analysis, we prove that with our way of application of neural networks, the accuracy of prediction is improved. Springer India 2016.

Source

Advances in Intelligent Systems and Computing, Vol-435, pp. 599-605.

Date

2016-01-01

Publisher

Springer Verlag

Subject

Data mining; Decision tree; Index; Investor; Neural networks; Stock market prediction; Stock price; Volatile market

Coverage

Ravichandra T., Department of Professional Studies, Christ University, Bangalore, India; Thingom C., Centre for Digital Innovation, Christ University, Bangalore, India

Rights

Restricted Access

Relation

ISSN: 21945357; ISBN: 978-813222756-4

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-81-322-2757-1_59

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959149198&doi=10.1007%2f978-81-322-2757-1_59&partnerID=40&md5=b38362d24d87d3eb5931a483be888d57