STOCK PRICE PREDICTION USING MACHINE LEARNING

ABSTRACT

Stock Price Prediction using Machine Learning is the process of predicting the future value of a stock traded on a stock exchange. With multiple factors involved in predicting stock prices, it is challenging to predict stock prices with high accuracy, and this is where machine learning plays a vital role. Treating stock data as time-series, one can use past stock prices (and other parameters) to predict the stock prices for the next day or week.  Stock price prediction is a challenging task because of the high volatility and complexity of financial markets. By using Machine Learning, it  analyzes complex sets of historical data, discovers hidden relationships between data sets, makes forecasts, and learns along the way to become even more accurate. Such capabilities make Machine Learning based tools well-suited for financial analysis. Two Machine Learning algorithms namely Decision Tree and Logistics Regression were used in this study for stock prediction. The datasets used for training the Machine Learning algorithms were obtained from kaggle.com. The result of the prediction shows that the two algorithms effectively predicted market stock.