Django Trading Bot

This project is a web application for a trading bot that displays financial data and indicators. It includes functionality for researching financial data, displaying market indicators, and more.

Table of Contents

• Project Overview
• Features
• Installation
• Usage
• Configuration
• Running Tests
• Contributing
• License

Project Overview

The Django Trading Bot is designed to help users analyze financial data and market indicators. It provides a user-friendly interface to view financial metrics, perform technical analysis, and offers additional functionalities like the efficient portfolio with the most recent stock market data and AI news sentiment analysis.

Features

• Display financial data for selected stocks
• Show technical indicators like SMA, EMA, Bollinger Bands, RSI, MACD, and Stochastic
• Interactive research page to view stock data and charts
• Generate an efficient portfolio with the latest stock market data
• AI-powered news sentiment analysis for informed decision-making
• Admin panel for managing data and settings

Installation

Follow these steps to set up the project on your local machine.

Prerequisites

• Python 3.7+
• Django 3.0+
• Virtualenv (optional but recommended)

Steps

1. Clone the repository

   git clone https://github.com/yourusername/django-trading-bot.git
   cd django-trading-bot

2. Create and activate a virtual environment

   python -m venv env
   source env/bin/activate  # On Windows use `env\Scripts\activate`

3. Install the required packages

   pip install -r requirements.txt

4. Apply migrations

   python manage.py migrate

5. Run the development server

   python manage.py runserver

6. Access the application

   Open your browser and go to http://127.0.0.1:8000/.

Usage

Admin Panel

• Access the admin panel at http://127.0.0.1:8000/admin/.

• Create a superuser to access the admin panel:

  python manage.py createsuperuser

Research Page

• Visit http://127.0.0.1:8000/research/ to use the research functionalities.
• Click on the stock tickers to view detailed financial data and indicators.

Efficient Portfolio

• Visit http://127.0.0.1:8000/portfolio/ to view the efficient portfolio generated using the most recent stock market data.

AI News Sentiment Analysis

• Visit http://127.0.0.1:8000/news-sentiment/ to see AI-powered news sentiment analysis, helping you make informed trading decisions.

Configuration

• Update settings in settings.py as per your environment and requirements.
• Configure database settings, email settings, and other environment-specific variables.

Running Tests

• Run tests using the following command:

  python manage.py test

Contributing

We welcome contributions! Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.

License

This project is licensed under the MIT License. See the LICENSE file for more details.