Abstract: In this project we attempt to implement a machine learning approach to predict stock prices. Forecasting of stock prices can be done effectively using Machine Learning. The main objective is to predict the stock prices such that we can make more informed and accurate investment decisions. Our proposed stock price prediction system integrates mathematical functions, machine learning, and other external factors. This can be used for the purpose of achieving better stock prediction accuracy and issuing profitable trades.
There are two types of stocks. You may know of intraday trading by the commonly used term "day trading." Intraday traders hold securities positions from at least one day to the next and often for several days to weeks or months. In order to store past information in the sequence prediction problems, LSTMs are more powerful. This is most important in our project because the previous price of a stock is crucial in predicting its future price. While predicting the actual price of a stock, we can build a model that will predict whether the price will go up or down.
Keywords: Stock Prediction, Trading, Machine Learning, Stock Price.
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DOI:
10.17148/IJARCCE.2022.114175
