Stock Data Analysis and Prediction in Machine Learning
DOI:
https://doi.org/10.26438/ijcse/v8i9.7078Keywords:
Stock data, Nifty-50, Stock Indicators, Random Forest, Artificial Neural NetworkAbstract
In the world of stock market Machine Learning has a very unique role to play when it comes on to the stock prediction. Machine learning library which is also known as MLIB helps in determining the future values of the stocks. This Research finds out the future ups and downs of stock market by providing you a signal for the same, whether the stock will be closed up or down. This has done by analysing the historical data. In this study stock data of NSE (National Stock Exchange of India) from 2000 to 2019 have been analysed which includes top forty eight companies of various sectors from all over India. With the help of machine learning libraries six technical indicators known as Bollinger Band, Relative Strength Index(RSI), Stochastic Oscillator, Williams %R, Moving Average Convergence Divergence (MACD), Rate of Change have been applied on to the nineteen years of stock data and finally, Random Forest algorithm and Artificial Neural Network Model have been applied on it to predict the stock movement, at last a comparison between Random forest and ANN model has also been done to check the better prediction.
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