An Efficient Facebook Prophet-Based Framework for Accurate Stock Price Prediction

Abstract

Accurate stock market forecasting is essential for investors, financial analysts, and institutions to make informed investment decisions and effectively manage financial risk. However, predicting stock price movements is a challenging task due to the highly dynamic, nonlinear, and volatile nature of financial markets. Conventional statistical forecasting techniques often fail to capture long-term trends, seasonal variations, and sudden market fluctuations, leading to reduced prediction accuracy. This project proposes a Facebook Prophetbased Stock Market Forecasting System that leverages advanced time-series analysis to generate reliable future stock price predictions from historical market data. The proposed framework incorporates comprehensive data preprocessing, including data cleaning, normalization, feature preparation, and date formatting, to improve data quality before model training. The Prophet model is trained to learn longterm trends, seasonal patterns, and changepoints from historical stock prices and generate future forecasts with confidence intervals. The system is evaluated using historical stock datasets and compared with conventional forecasting approaches such as ARIMA, LSTM, and Moving Average models. Experimental results demonstrate that the proposed Prophet model achieves superior forecasting performance with a Mean Absolute Percentage Error (MAPE) of 4.5% and a Root Mean Squared Error (RMSE) of 15.2, outperforming the comparative models in terms of prediction accuracy and robustness. The model effectively captures market trends, adapts to changing market conditions, and provides interpretable forecasting results that support investment planning and financial decision-making. Owing to its simplicity, scalability, and high predictive capability, the proposed forecasting system serves as a reliable decision-support tool for investors, traders, financial analysts, and researchers. The study demonstrates that the Facebook Prophet model provides an efficient and practical solution for stock market forecasting and highlights its potential for enhancing data-driven financial analysis and investment strategies. Keywords— Stock Market Prediction, Facebook Prophet, Time-Series Forecasting, Financial Analytics, Machine Learning, ARIMA, LSTM, Forecasting, RMSE, MAPE.