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An intensive, structured 100-day journey to mastering algorithmic trading with Python. This repository contains comprehensive code, projects, and resources from beginner Python fundamentals to advanced trading systems and machine learning models for financial markets.
This isn't just another "learn to code" challenge. This is an intensive deep dive into the complex world of algorithmic trading, where we tackle:
- Python fundamentals through the lens of financial applications
- Real-world trading strategies with live market data
- Complex statistical models and their implementation
- Machine learning applications in trading
- Complete end-to-end trading systems
No shortcuts. No fluff. Just 100 days of intense, practical learning that will transform you from a beginner to a capable algorithmic trader.
This journey is organized into progressive modules, each building on the previous:
- Python basics with financial applications
- OOP fundamentals for trading systems
- Data structures for market data
- Error handling for robust trading systems
- File operations and data serialization
- NumPy for numerical computing
- Pandas for financial data analysis
- Matplotlib for visualizing market data
- Financial statistics and probability
- Technical indicators implementation
- Financial contracts and markets
- Options trading and strategies
- Data scraping for financial information
- Market analysis techniques
- Distribution models for returns
- Regression models for forecasting
- Time series analysis
- Machine learning basics for trading
- Backtesting frameworks
- Signal generation systems
- Portfolio management systems
- Multi-asset trading strategies
- Advanced backtesting with cross-validation
- Optimization techniques
- End-to-end trading platforms
A full-featured web application for backtesting moving average crossover trading strategies. Built with Python and Flask, this project demonstrates how to implement trading strategies using control flow concepts.
Key Features:
- Interactive web interface with Bootstrap 5
- Strategy customization and parameter optimization
- Real-time visualization with Plotly
- Comprehensive performance metrics and trade history
An advanced stock screening tool that filters stocks based on multiple technical indicators and fundamental metrics. Perfect for identifying potential trading opportunities.
Key Features:
- Multi-factor screening criteria
- Technical and fundamental analysis
- Customizable screening parameters
- Export functionality for further analysis
A beginner-friendly Python program that generates trading signals based on key technical indicators. This project demonstrates how to implement basic trading logic.
Key Features:
- Simple trading rules using technical indicators
- Analysis based on moving averages, RSI, and volume
- Clear Buy, Sell, or Hold signals with explanations
- Identification of key chart patterns
A comprehensive portfolio management system that allows tracking and optimizing multi-asset portfolios with advanced risk metrics.
Key Features:
- Portfolio performance tracking
- Risk-adjusted return calculations
- Asset allocation optimization
- Correlation analysis across asset classes
The repository is organized by day, with each folder containing:
- Complete source code with detailed comments
- Data files and resources where applicable
- Implementation notes and explanations
- Challenge problems and solutions
- Python 3.7+
- pip (Python package manager)
-
Clone the repository:
git clone https://github.com/thekuldeepsingh/100-Days-Of-Hell-With-Python-Algotrading.git cd 100-Days-Of-Hell-With-Python-Algotrading -
Install required packages:
pip install -r requirements.txt
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Explore the daily folders to follow the progression, or jump to specific projects that interest you.
| Module | Status | Completion |
|---|---|---|
| Foundation (Days 1-20) | Completed | 100% |
| Data & Analysis (Days 21-40) | Completed | 100% |
| Trading Fundamentals (Days 41-60) | Completed | 100% |
| Strategy Development (Days 61-80) | Completed | 100% |
| Advanced Systems (Days 81-100) | In Progress | 30% |
Join The Quantitative Elite Community to:
- Share your implementation and progress
- Get help with challenges and projects
- Connect with other algorithmic traders
- Learn advanced techniques beyond the 100 days
Supplement your learning with video tutorials on our YouTube Channel:
- Step-by-step explanations of complex concepts
- Live coding sessions for key projects
- Market analysis and strategy discussions
- Additional tips and tricks not covered in the code
- Practical Python for Effective Algorithmic Trading - The companion book to this challenge
- Financial Data APIs Guide - Our guide to accessing market data
- Quantitative Trading Roadmap - A comprehensive learning path
- Python beginners looking for a practical, goal-oriented learning path
- Traders interested in automating their strategies
- Data scientists exploring financial applications
- Software developers entering the fintech space
- Anyone fascinated by the intersection of finance and technology
This project is licensed under the MIT License - see the LICENSE file for details.
- Based on concepts from Practical Python for Effective Algorithmic Trading
- Trading strategies inspired by classic technical analysis techniques
- Community contributions and feedback
Join our community • YouTube Channel • Get the Book
Remember: The markets won't wait for you to get ready. Start your algorithmic trading journey today! 📈