📈 Stock-AI

Stock-AI is an interactive Streamlit web application that simulates future stock price movements using Monte Carlo methods. It allows users to visualize potential future price trajectories based on historical volatility, providing insights into the effects of market fluctuations on financial instruments.

🚀 Features

• Historical Data Simulation: Generate synthetic historical price data based on user-defined volatility parameters.
• Monte Carlo Forecasting: Predict future stock prices through Monte Carlo simulations.
• Interactive Visualizations: Visualize both historical and predicted price movements.
• Accuracy Metrics: Evaluate prediction accuracy using metrics like MAE (Mean Absolute Error), RMSE (Root Mean Square Error), and Percentage Error.

🛠️ Installation

Prerequisites

• Python 3.7 or higher
• pip package manager

Setup Instructions

1. Clone the Repository

   git clone https://github.com/git-devisha/Stock-AI.git
   cd Stock-AI

2. Install Dependencies

   Install the required Python packages:

   pip install -r requirements.txt

   Alternatively, install packages individually:

   pip install streamlit numpy pandas

💻 Usage

1. Run the Application

   streamlit run test3.py

2. Access the Web Interface

   After running the above command, Streamlit will provide a local URL (typically http://localhost:8501). Open this URL in your web browser to interact with the application.

📂 Project Structure

Stock-AI/
├── test3.py             # Main Streamlit application script
├── requirements.txt     # List of required Python packages
└── README.md            # Project documentation

📊 Example Output

Note: Include screenshots or GIFs here to showcase the application's interface and features.

🤝 Contributing

Contributions are welcome! If you'd like to enhance the application, fix bugs, or add new features:

1. Fork the repository.
2. Create a new branch: git checkout -b feature-name.
3. Commit your changes: git commit -m 'Add new feature'.
4. Push to the branch: git push origin feature-name.
5. Open a pull request detailing your changes.