This is an interactive Stock Price Prediction Web App built using Streamlit. It allows users to visualize historical stock data and forecast future stock prices using ARIMA/ARIMAX models.
- 📅 Select date range for stock data
- 🏢 Choose any listed company (via ticker symbol)
- 📊 Visualize historical stock trends using Plotly
- 🔮 Predict future prices using ARIMA
- 📈 See forecasts plotted alongside actual prices
- 📥 Built with an intuitive sidebar for parameter selection
- Clone the repository
git clone https://github.com/Shoaib1-coder/StockPricePrediction.git
cd StockPricePrediction- Create a virtual environment (optional but recommended)
# Make sure Anaconda is installed: https://www.anaconda.com/products/distribution
# Create a new environment named 'stockprice' with Python 3.10
conda create --name stockprice python=3.10
# Activate the environment
conda activate stockprice
- Install dependencies
pip install -r requirements.txtstreamlit run app.py├── app.py # Main Streamlit app
├── requirements.txt # Dependencies
├── README.md # This file
└── ...- Choose a company ticker symbol from the sidebar.
- Select a date range to analyze historical stock data.
- Choose the data column (e.g.,
Close,Open) for forecasting. - View:
- Interactive line charts for selected data
- Forecast plots based on ARIMA model
The app uses pmdarima.auto_arima() to automatically find the best (p, d, q) parameters and generate forecasts.
p: Number of lag observations (AR)d: Degree of differencingq: Size of moving average window (MA)
Feel free to fork the repo, open issues, or submit pull requests.
For suggestions or feedback, contact: [mshoaib3393@gmail.com]
This project is open-source and available under the MIT License.