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STOCK PRICE ANALYSIS AND PREDICTION

GAURAV JANGID

DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING

BIRLA INSTITUTE OF TECHNOLOGY,MESRA

Noida  Campus

Abstract

The price at which one share of a corporation would be purchased is known as the share price or stock price. A share's price is not constant; rather, it changes over time in response to market factors. It is likely to rise if the business is thought to be performing well or decline if it isn't living up to expectations. There are two different stock types. You may be familiar with intraday trading through the phrase "day trading." Intraday traders frequently hold securities positions for multiple days up to weeks or months, but at least from one day to the next.

Various application domains, including medical analysis, recommendation systems, stock price forecasts, etc., successfully utilize machine learning. In order to make wiser and more accurate financial decisions, the goal is to forecast stock prices. In order to improve stock forecast accuracy and generate lucrative trades, we suggest a stock price prediction system that combines mathematical functions, machine learning, and other external aspects.

Because they have the capacity to store historical data, LSTMs are particularly effective at solving sequence prediction issues. This is significant in our situation since a stock's historical price plays a key role in determining its future price. While predicting a stock's real price is difficult, we can create a model that will predict whether it will rise or fall.

Keywords: LSTM, CNN, ML, DL, Trade Open, Trade Close, Trade Low, Trade High