Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/10222
Title: Artificial Neural Network- Validity of Technical Analysis Indicators for Predicting Stock Prices
Authors: Navita Nathani
Jaspreet Kaur
Issue Date: 2017
Publisher: Gitam Journal of Management
Abstract: To predict the stock market, theories like Random Walk, Elliot Wave, and Dow Theory came into existence. These were based on various set of assumptions, which led to fonnation of indicators and Machine Leaming Techniques ( MLT). The present study is an attempt to make use of these enhanced tools for estimating the relationship between the indicators and stock prices, by making use of Artificial Neural Network.This would help in predicting the direction of the stock prices. Two models were defined using input layer and output layer, where, rate of change and moving averages were found to be the significantly associated.
URI: http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/10222
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