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The “quantitative” repository by Jack-Cherish is a tutorial-style codebase for quantitative trading written in Python — essentially a learning resource that guides users through building algorithmic trading strategies step by step. It’s organized as a sequence of lessons (lesson1, lesson2, etc.), making it approachable for learners who want to understand both theory and practice in quantitative finance. The repo is evidently tied to a popular video series (on Bilibili) that reportedly drew substantial attention, suggesting the material is meant to be both educational and hands-on. The README and associated lessons walk the user through implementing algorithms, likely covering data handling, backtesting, and maybe simple trading logic. As an open-source educational resource, it’s designed for Python users interested in automatic trading, algorithmic strategies, and financial data analysis.
Features
- Lesson-by-lesson structured tutorials for algorithmic trading
- Python-based code (pure Python) for accessibility
- Backtesting-ready scripts for trading strategy evaluation
- Educational material tied to a real video series for guided learning
- Focus on quantitative finance fundamentals (data handling, trade logic, performance)
- Free and open-source, easy to inspect and modify
Project Samples
