Technical Analysis of Pattern Based Stock Prediction Model Using Machine Learning

Abstract

In Stock Prediction, the aim is to predict future stock values with desirable accuracy. Our research aims to offer a method for technical analysis of pattern based stock prediction using Machine Learning on the historical stock data. The newly designed method is based on GA with the appropriate modifications needed for the prediction. We have performed various experiments using the historical data of a few companies and the results confirmed the accuracy and efficiency of the system as it is generating promising predictions. This designed model executes a prediction process that is not influenced by any other external factors.