NiftyInvest AI: Enhancing Investment Decisions Through Time-Series Forecasting and Deep Learning Models

Abstract: The increasing complexity and volatility of financial markets demand intelligent, technology-driven systems that enable accurate forecasting, risk management, and data-driven decision-making. This paper presents the Nifty50 Decision Tool, a Decision Support System (DSS) designed for stock trend prediction and portfolio analysis. The system integrates two roles—Users and Administrators—to streamline stock selection, forecasting, and decision recommendations. Investors can select stocks from the Nifty50 index (e.g., Reliance, Infosys), visualize technical indicators such as Moving Averages, RSI, MACD, Bollinger Bands, and VWAP, and receive short-term forecasts generated using ARIMA and LSTM models. Administrators leverage the backend to manage data acquisition, validate forecasts, and store user analysis history in SQLite for continuous improvement. The tool combines linear and non-linear forecasting approaches with technical analysis, providing users with actionable insights such as Buy, Hold, or Sell signals. Built with HTML, CSS, and JavaScript for the frontend, Flask APIs for backend, Streamlit for visualization, and SQLite for data storage, the system emphasizes lightweight deployment and scalability. Experimental evaluation demonstrates reliable short-term forecasting, effective visualization, and improved decision accuracy, making the Nifty50 Decision Tool a practical DSS for both academic study and real-world financial decision support. Keywords: Stock Market, Decision Support System, Nifty50, ARIMA, LSTM, Technical Indicators, Forecasting, Portfolio Analysis, Financial Analytics.