Stock Market Analysis and Prediction

Stock Market Analysis and Prediction

L. Bharath Balaji Naidu1, K. Bindhu Madhavi2, B. Siva Venkata Harshith3, P. Sowmya4, P. Sunny5

S.V. R. Vara Prasad6,

[1],[2],[3],[4],[5] B. Tech Student, Department of Computer Science and Information Technology

[6] Assistant Professor, Department of Computer Science and Information Technology

[1],[2],[3],[4],[5],[6] Lendi Institute of Engineering and Technology, Vizianagaram.

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ABSTRACT

The project focuses on leveraging an LSTM neural network to predict stock market behaviour, addressing the challenges posed by market volatility and complexity. LSTM's capability to handle long-term

dependencies make it suitable for analysing historical stock prices and forecasting future trends. The model’s effectiveness is assessed through its accuracy and ability to generalize across various stocks and market conditions. Initial results indicate that the LSTM model can identify significant trends and patterns, though its accuracy is influenced by the quality of input data. Future enhancements could include incorporating additional market indicators and news sentiment to improve predictive performance and provide deeper insights for investors.

Key Words: Stock Market Analysis, LSTM Model, Time-Series Forecasting, Predictive Analytics, Recurrent Neural Network.