Real-Time Stock Trading Simulator

A modern, professional web-based real-time stock trading simulator with interactive charts, live data visualization, and advanced trading strategies. Built with Flask, Plotly, and Yahoo Finance API.

What the project includes

Core Trading Features

Real-time Stock Data: Live stock price monitoring with Yahoo Finance integration
Advanced Trading Strategy: Enhanced moving average crossover strategy with RSI, momentum, and risk management
Portfolio Tracking: Real-time portfolio value updates and performance metrics
Historical Mode: Run simulations on historical data for backtesting
Multiple Stocks: Support for 40+ popular stocks and ETFs
Risk Management: Built-in stop-loss and profit-taking mechanisms

User Interface

Interactive Charts: Beautiful Plotly charts showing price movements and trading signals
Responsive Design: Modern UI that works direct on desktop and mobile
Real-time Updates: Live data updates with smooth animations
Dark Mode Support: Automatic dark mode detection and styling
Professional Dashboard: Clean, intuitive interface with comprehensive trading information

Technical Features

Modular Architecture: Well-organized codebase with separation of concerns
API-First Design: RESTful API endpoints for all trading operations
Error Handling: reliable error handling and retry mechanisms
Configuration Management: Environment-based configuration system
Testing Suite: Comprehensive unit tests for core functionality
Performance Optimization: Efficient data processing and caching

How files are organized

Real-Time-Stock-Trading-Simulator/
├── src/                          # Main source code
│   ├── core/                     # Core trading functionality
│   │   ├── __init__.py
│   │   ├── data_fetcher.py      # Stock data fetching
│   │   └── strategy.py          # Enhanced trading strategy implementation
│   ├── api/                      # API endpoints
│   │   ├── __init__.py
│   │   └── routes.py            # Flask routes and API handlers
│   ├── utils/                    # Utility functions
│   │   ├── __init__.py
│   │   └── config.py            # Configuration management
│   └── models/                   # Data models
│       ├── __init__.py
│       └── trade.py             # Trade and portfolio models
├── static/                       # Static assets
│   ├── css/                     # Stylesheets
│   │   └── main.css             # Main application styles
│   ├── js/                      # JavaScript files
│   │   └── app.js               # Main application logic
│   ├── images/                  # Image assets
│   └── templates/               # HTML templates
│       └── index.html           # Main dashboard template
├── docs/                         # Documentation
│   └── API.md                   # API documentation
├── app.py                       # Main application entry point
├── requirements.txt             # Python dependencies
├── setup.py                     # Package setup
├── Makefile                     # Development tasks
├── env.example                  # Environment variables example
└── README.md                    # This file

Installation

Prerequisites

Python 3.8 or higher
pip (Python package installer)

Quick Start

Windows (Recommended)

Clone the repository

git clone https://github.com/yourusername/real-time-stock-trading-simulator.git
cd real-time-stock-trading-simulator

Run installation script
```
install.bat
```
Run the application
```
run.bat
```
Open in browser Navigate to http://localhost:5000

Manual Installation (All Platforms)

Clone the repository

git clone https://github.com/yourusername/real-time-stock-trading-simulator.git
cd real-time-stock-trading-simulator

Create virtual environment

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Install dependencies
```
pip install -r requirements.txt
```
Run the application
```
python app.py
```
Open in browser Navigate to http://localhost:5000

Development Setup

For development with additional tools:

# Install development dependencies
make install-dev

# Run tests
make test

# Format code
make format

# Lint code
make lint

Usage

Basic Trading

Select Stock: Choose from 40+ available stocks and ETFs
Configure Parameters: Set interval, period, and initial cash amount
Start Simulation: Click "Start Simulator" to begin real-time trading
Monitor Results: Watch live charts and trade updates
Stop Simulation: Click "Stop Simulator" when finished

Historical Mode

Enable Historical Mode: Check the "Historical Mode" checkbox
Select Date: Choose a specific date for backtesting
Run Simulation: Start the simulator to see how your strategy would have performed

Enhanced Trading Strategy

The simulator uses an Advanced Moving Average Crossover strategy with multiple confirmations:

Core Strategy Components:

Moving Average Crossover: Golden cross (buy) and death cross (sell) signals
RSI Filter: Relative Strength Index to avoid overbought/oversold conditions
Momentum Analysis: Price and moving average momentum confirmation
Risk Management: Automatic stop-loss and profit-taking mechanisms

Strategy Parameters:

Short Window: Fast moving average period (default: 5)
Long Window: Slow moving average period (default: 20)
Profit Threshold: Target profit percentage (default: 2%)
Stop Loss: Maximum loss percentage (default: 1%)
RSI Window: RSI calculation period (default: 14)

Signal Generation:

Buy Signal: When short MA crosses above long MA + RSI 25 + stop-loss/profit-taking
Position Sizing: Risk-based position sizing (2% risk per trade)

Configuration

Environment Variables

Copy env.example to .env and modify as needed:

# Flask Configuration
FLASK_DEBUG=True
SECRET_KEY=your-secret-key-here
HOST=0.0.0.0
PORT=5000

# Trading Configuration
DEFAULT_SYMBOL=AAPL
DEFAULT_INTERVAL=1m
DEFAULT_PERIOD=1d
DEFAULT_INITIAL_CASH=50000

# Strategy Configuration
DEFAULT_SHORT_WINDOW=5
DEFAULT_LONG_WINDOW=20
DEFAULT_PROFIT_THRESHOLD=0.02
DEFAULT_STOP_LOSS=0.01

Available Stocks

The simulator supports 40+ popular stocks and ETFs including:

Technology: AAPL, MSFT, GOOGL, AMZN, TSLA, META, NVDA
Finance: JPM, BAC, WFC, GS, MS, C
Healthcare: JNJ, PFE, UNH
Consumer: HD, DIS, V, MA, PG, KO, PEP, WMT, COST
And many more...

API Endpoints

Core Endpoints

GET / - Main dashboard
GET /api/simulator-status - Get simulation status

Trading Endpoints

POST /api/start-simulator - Start trading simulation
POST /api/stop-simulator - Stop simulation
POST /api/clear-trades - Clear all trades

Data Endpoints

GET /api/stock-data - Get current stock data and signals
GET /api/trades - Get trade history
GET /api/portfolio-values - Get portfolio value history

Testing

Run the test suite:

# Run all tests
make test

# Run tests with coverage
make test-coverage

# Run specific test file
python -m pytest tests/test_data_fetcher.py -v

Deployment

Local Development

make run-dev

Production

# Set production environment
export FLASK_DEBUG=False
export SECRET_KEY=your-production-secret-key

# Run application
python app.py

Docker Deployment

# Build Docker image
make docker-build

# Run Docker container
make docker-run

Contributing

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

Development Guidelines

Follow PEP 8 style guidelines
Write tests for new features
Update documentation as needed
Use meaningful commit messages

License

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

Acknowledgments

Yahoo Finance: For providing real-time stock data
Plotly: For interactive charting capabilities
Flask: For the web framework
Bootstrap: For responsive UI components

Support

Issues: GitHub Issues
Documentation: Project Wiki
Email: your.email@example.com

Changelog

Version 1.1.0 (Latest)

Enhanced trading strategy with RSI and momentum indicators
Improved risk management with stop-loss and profit-taking
Better signal generation with multiple confirmations
Performance optimizations and bug fixes

Version 1.0.0

Initial release with real-time trading simulation
Interactive charts and portfolio tracking
Historical mode for backtesting
Modular architecture and comprehensive testing

Disclaimer: This is a simulation tool for educational purposes only. It does not provide financial advice or guarantee investment returns. Always do your own research before making investment decisions.