Stock Price Prediction Using Machine Learning

Abstract

Shares in publicly traded companies, or equity shares, can be purchased and sold on the stock market. There are three basic types of stock market investors. All three types of investors: FII (foreign institutional investors), DII (domestic investors), and retail investors. Foreign Institutional Investors, such as mutual funds and banks, who have the experience and knowledge necessary to make their investment. Non-professional investors are known as retail investors. Machine learning is used to make an accurate prediction with less risk management in the stock market because there is a lot of uncertainty there. Through forecasting and LSTM (Long/Short Term Memory), we can theoretically predict stock prices through the use of machine learning. Effective stock market prediction gives us some suggestions on trading strategies, which is why stock market prediction is so important when it comes to investments. There is, however, no way to guarantee that the data will be 100% accurate because of future uncertainty in the field of study. For stock price prediction, this paper reviews studies on machine learning techniques and algorithms.