The stock market remains one of the most dynamic and unpredictable domains in the global financial landscape, where rapid price fluctuations and information overload frequently overwhelm individual investors. Reliance on speculative judgment, emotional bias, and unverified market news continues to expose retail investors to significant financial risk and suboptimal decision- making. This paper proposes an AI-Based Stock Market Analysis and Investment Advisory System that integrates advanced Machine Learning and Deep Learning methodologies to deliver accurate price forecasts and actionable investment guidance. At the core of the system, Long Short- Term Memory (LSTM) networks are employed to model complex temporal dependencies and non- linear patterns inherent in historical stock price data, enabling reliable short- and long-term trend forecasting. The system further incorporates a suite of widely adopted technical indicators, including Moving Averages, Relative Strength Index (RSI), and Moving Average Convergence Divergence (MACD), to enrich the feature space and enhance overall prediction accuracy.
India et al. (Wed,) studied this question.
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