This repository contains a simple web application for stock market prediction. The application is built using Flask, HTML, and Bootstrap. It provides an interface for viewing different stock indices and is designed to be a starting point for building more advanced stock prediction tools. It is purely made for a college project.

• Overview
• Getting Started
• Usage
• Dependencies
• Contributing
• License

The Stock Market Prediction web app is a basic web application that allows users to view various stock market indices. It currently supports the following indices:

• Nifty 50
• Nifty Bank
• Nifty Financial Services
• Reliance

In addition to the current features, the project has future plans for expansion, including the following:

• Integration of Machine Learning Models for Prediction 🤖
• Displaying Charts and Visualizations 📊
• Incorporating Tradingview Technical Analysis 📉

The application's user interface is minimal and user-friendly, thanks to the Bootstrap framework. Users can access different indices through the navigation menu on the left-hand side of the web page.

To run this application locally, follow these steps:

1. Clone this repository to your local machine:

   git clone https://github.com/AdityaDKale/GarnetMarketEngine.git
   

2. Navigate to the project directory:

   cd GarnetMarketEngine/
   

3. Install the required dependencies (Flask):

   pip install -r requirements.txt
   

4. Navigate to src folder:

   cd src
   

5. Run the following commands in succession:

   python model_creation.py
   

   python prediction.py
   

6. Return to base directory:

   cd ..
   

7. Run the Flask application:

   python main.py
   

8. Open a web browser and visit http://localhost:81 to view the web application. (Kept on host=0.0.0.0 and port=81 for easy replit setup)

9. For accurate predictions run predictions.py daily.

• Upon running the application, you will be directed to the home page displaying the available stock market indices.
• Click on an index name in the navigation menu to view the corresponding stock index page.
• Explore the application to get a basic idea of its functionality.

The following dependencies are used in this project:

• Flask: A micro web framework for Python.
• Bootstrap: A popular HTML, CSS, and JavaScript framework for building responsive and mobile-first web applications.
• Lightweight Charts: Framework to plot charts.
• Keras: For machine learning framework.

Contributions to this project are welcome. If you have any ideas or improvements you'd like to see implemented, please open an issue or submit a pull request.

This project is licensed under the MIT License - see the LICENSE file for details. 📄