Learn investing and trading by doing. Practice with a virtual account, test real strategies risk-free, and complete a 21-day challenge with daily lessons and exercises. PaperProfit can teach you about investing, trading, risk management, markets, portfolio management, and a wide range of investment strategies using real market data, all without risking real money.

Please note that current version is a MVP and code still has bugs and learning journey content is still incomlete.

• 21-Day Learning Journey: Structured educational path with daily lessons, quizzes, and exercises
• Paper Trading: Simulate buy/sell orders without real money
• Portfolio Management: Track multiple accounts and positions
• Real Market Data: Integration with Yahoo Finance, Alpha Vantage, and Financial Modeling Prep
• Automated Trading Bot: Background jobs for order processing and strategy execution
• Performance Analytics: Track your gains/losses and portfolio performance

A structured educational program designed to take you from beginner to confident trader in 21 days:

• Daily Lessons: Each day covers a specific topic with comprehensive study materials and visual aids
• Interactive Quizzes: Test your knowledge with multiple-choice quizzes after each lesson
• Practical Exercises: Apply what you've learned with hands-on exercises
• Progress Tracking: Visual progress tracking with XP system and completion status
• Sequential Unlocking: Days unlock as you master previous lessons (requires 80% quiz score to advance)
• Flexible Learning: Review completed lessons anytime and retake quizzes

The 21-day journey covers essential topics including:

• Market fundamentals and terminology
• Portfolio management principles
• Risk management strategies
• Technical and fundamental analysis
• Trading strategies and execution
• Psychology of trading
• And more...

PaperProfit includes implementation templates for various trading strategies across multiple categories:

• Buy & Hold
• Index Fund Investing
• Dollar-Cost Averaging (DCA)
• Dividend Growth Investing
• Value Investing
• Growth Investing
• Sector Rotation
• Asset Allocation & Rebalancing

• Trend Following
• Breakout Trading
• Momentum Trading
• Mean Reversion
• RSI Overbought/Oversold

• Scalping
• VWAP Strategy
• Opening Range Breakout
• News-Based Trading

• Covered Calls
• Cash-Secured Puts
• Iron Condor

• Warren Buffett (Value Investing)
• Ben Graham (Deep Value)
• Peter Lynch (GARP)
• Ray Dalio (All Weather Portfolio)
• Jesse Livermore (Trend & Breakout)
• John Bogle (Passive Index)
• Stanley Druckenmiller (Macro Trend)
• Jim Simons (Quantitative Statistical Arbitrage)

• Stock analysis using AI
• Trading strategy generation
• Market insights and sector analysis
• Multi-stock comparison

• Framework: FastAPI
• Database: SQLite with SQLAlchemy ORM
• Task Scheduling: APScheduler
• Market Data: yfinance, alpha_vantage
• Python: 3.x

• Framework: Vue 3
• Build Tool: Vite
• UI: Custom components

• Python 3.8 or higher

git clone <repository-url>
cd paper_profit

./start.sh

This will:

• Create and activate a virtual environment
• Install dependencies
• Run database migrations (if needed)
• Start the FastAPI server on port 5000
• Start background jobs for order processing and market data updates

Go to http://localhost:5000

cd backend/app
python api.py

API will be available at http://localhost:5000
API documentation at http://localhost:5000/docs

cd backend/app
python background.py

cd frontend
npm run dev

Frontend will be available at http://localhost:5173

paper_profit/
├── backend/
│   ├── app/
│   │   ├── api.py                    # FastAPI application
│   │   ├── main.py                   # CLI entry point
│   │   ├── background.py             # Background job scheduler
│   │   ├── analysis/                 # Technical & fundamental analysis
│   │   ├── config/                   # YAML configuration files
│   │   ├── jobs/                     # Scheduled jobs
│   │   │   ├── trading_bot.py        # Main trading bot logic
│   │   │   ├── process_orders.py     # Order execution
│   │   │   ├── update_market_data.py # Market data updates
│   │   │   └── update_positions.py   # Position updates
│   │   ├── neumann/                  # 21-Day Learning Journey content
│   │   │   └── [1-21]/              # Daily lessons, quizzes, and exercises
│   │   ├── octopus/                  # External service integrations
│   │   │   ├── ai_platforms/         # AI service providers
│   │   │   ├── brokers/              # Broker integrations
│   │   │   └── data_providers/       # Market data providers
│   │   ├── services/                 # Business logic
│   │   ├── storage/                  # Database models & repositories
│   │   ├── tests/                    # Unit tests
│   │   └── utils/                    # Utility functions
│   ├── requirements.txt              # Python dependencies
│   └── PaperProfit.db               # SQLite database
├── frontend/
│   ├── src/
│   │   ├── components/              # Vue components
│   │   ├── App.vue                  # Root component
│   │   └── main.js                  # Entry point
│   ├── package.json                 # Node dependencies
│   └── vite.config.js              # Vite configuration
├── start.sh                         # Quick start script
└── README.md                        # This file

• GET /api/accounts - List all accounts
• POST /api/accounts - Create new account
• GET /api/accounts/{id} - Get account details
• PUT /api/accounts/{id} - Update account
• GET /api/accounts/{id}/summary - Account summary with positions
• GET /api/accounts/{id}/portfolio - Portfolio holdings
• GET /api/accounts/{id}/performance - Performance metrics
• POST /api/accounts/{id}/buy - Create buy order
• POST /api/accounts/{id}/sell - Create sell order

• GET /api/strategies - List all strategies
• POST /api/strategies - Create new strategy
• GET /api/strategies/{id} - Get strategy details
• PUT /api/strategies/{id} - Update strategy

• GET /api/instruments/search?query={q} - Search for stocks
• GET /api/instruments/get/{symbol} - Get instrument details
• GET /api/instruments/{symbol}/market-data?period={p} - Historical data

• POST /api/ai/analyze-stock - AI-powered stock analysis
• POST /api/ai/generate-strategy - Generate trading strategy
• GET /api/ai/market-insights - Market insights
• POST /api/ai/compare-stocks - Compare multiple stocks

• GET /api/learning-days - Get all learning days
• GET /api/learning-days/{day}/study - Get study content for a specific day
• GET /api/learning-days/{day}/quiz - Get quiz for a specific day
• GET /api/learning-days/{day}/exercise - Get exercise for a specific day
• GET /api/learning-days/{day}/image - Get image for a specific day
• GET /api/settings/learning_journey - Get learning progress
• PUT /api/settings/learning_journey - Update learning progress

• GET /api/settings - Get settings
• POST /api/settings - Create setting
• GET /api/service-list - Get service list
• GET /api/strategy-list - Get strategy templates
• GET /api/guide - Investment guide

Edit strategy templates in:

• backend/app/config/strategy-list.yaml
• backend/app/config/strategy-parameters.yaml

Configure data providers and services in:

• backend/app/config/service-list-settings.yaml

The application runs several scheduled jobs:

1. Trading Bot - Executes strategies and generates signals
2. Process Orders - Processes pending orders
3. Update Market Data - Fetches latest market prices
4. Update Positions - Updates position valuations

PaperProfit uses SQLite for simplicity. The database is automatically created and migrated on first run.

cd backend/app
python main.py migrate

This project is for educational purposes. Use at your own risk. Past performance does not guarantee future results.

PaperProfit is a simulation platform for educational purposes only. It does not execute real trades. Always do your own research and consult with financial advisors before making real investment decisions.

• Market data is delayed (not real-time)
• Some advanced options strategies are templates only
• AI features require API key

• More broker integrations
• Advanced charting and technical indicators
• Risk management tools

For issues, questions, or contributions, please open an issue on GitHub.

Made with ❤️ for traders and investors learning the markets.