Stock Price Prediction and Analysis using Machine Learning Techniques

Abstract

Abstract: Stock market is one of the most sought-after investment options today. Investing in the stock market has the potential to multiply people's money in a short period of time, but it also carries many risks. To be successful in the stock market, it is necessary to conduct extensive research about the market and the forces influencing it. This examination involves a review of historical stock prices as well as real-time market developments. When deciding the position in the market, investors need to make an informed choice. Market-related information may be obtained from a variety of sources, including news articles, stock research websites, apps, and television channels. However, stock movement prediction by taking into consideration the elements influencing it would undoubtedly assist investors in making sound decisions. The research area of stock movement prediction has seen numerous advancements throughout the years. In the domain of machine learning, various methods of stock price prediction have been introduced. In this paper, we have discussed different approaches to stock movement prediction based on diverse factors and technical indicators. We also propose a method for detecting market trends, which is a critical aspect in maintaining long-term market positions. Keywords: Machine Learning, Stock Market, Prediction, Classification, Technical Indicators, Trend prediction