Stock Market Price Prediction Using Machine Learning

• Published in: 2023 5th International Conference on Smart Systems and Inventive Technology (ICSSIT) pp. 823 - 828
• Main Authors: Mohammed, Shariq, Krishna, Somanchi Hari, Mudalkar, Pralhad K., Verma, Narinder, Karthikeyan, P., Yadav, Ajay Singh
• Format: Conference Proceeding
• Language: English
• Published: IEEE 23.01.2023
• Subjects: Analysis; Biological system modeling; Machine learning; Machine learning algorithms; Prediction algorithms; Predictive models; Stock Market Price Prediction; Time series analysis
• ISSN: 2832-3017
• DOI: 10.1109/ICSSIT55814.2023.10061120

The stock market is known for its high volatility, fast changes, and nonlinear behaviour; investors should be prepared for all three. It is highly challenging to precisely forecast the movements of stock prices due to the presence of multiple factors, both macro and micro, such as politics, the state of the global economy, unanticipated occurrences, and the financial success of a firm, among other factors. However, because there is such a wealth of information available, it can be challenging to draw conclusions. Because of this, researchers, analysts, and data scientists working in the financial sector are constantly looking for new analytical techniques that may be used to spot trends in the stock market. This development gave rise to the practice of algorithmic trading, which is characterized by the application of trading strategies that are pre-programmed and automated. Machine Learning models such as LSTM can accurately forecasts the prices of stocks as actual and predicted.