yasmeensayeed/Stock-market-prediction-EGX30

A stock market prediction project focused on EGX30. We use ARIMA, LSTM, CNN, and NLP models to predict market trends (up/down) based on historical data and sentiment analysis. The goal is to provide accurate and data-driven insights into Egypt's stock market. # 📈 EGX30 Stock Market Prediction This project aims to predict the movement (up or down) of Egypt's EGX30 stock market index using a combination of traditional statistical models and modern deep learning techniques. --- ## 🔍 Overview We analyze historical stock data and financial sentiment to build predictive models. The project integrates: - **ARIMA** for time-series forecasting. - **LSTM** to capture sequential patterns in stock prices. - **CNN** to extract meaningful features from time-based data. - **NLP** for sentiment analysis on financial news and social media. --- ## 🧠 Models Used - `ARIMA`: Statistical model for univariate time series. - `LSTM`: Recurrent neural network effective in time-series prediction. - `CNN`: Used to process time-series data like images for pattern recognition. - `NLP`: Sentiment analysis to assess public mood and its impact on the market. --- ## 📊 Data Sources - **Historical EGX30 index data** (CSV/JSON) - **Financial news headlines and articles** - **Social media sentiment data (optional)** --- ## ⚙️ How to Run 1. Clone the repository: ```bash git clone github.com cd egx30-prediction