This repository contains the open-source book 'XQuant: δΊΊδΊΊι½ζ―ιεδΊ€ζε' (XQuant: Everyone Can Be a Quantitative Trader), which serves as an educational resource for learning quantitative trading methodologies. Rather than being a functional trading application, it provides a structured curriculum teaching readers how to develop, test, execute, and monitor quantitative strategies using AI coding assistants. The book walks through a complete workflow: from selecting investment instruments (ETFs), determining position sizing, creating trading rules, validating strategy performance, avoiding overfitting, modeling execution costs, to monitoring and iterating on live strategies. Its unique value lies in teaching a spec-driven development approach where users write clear strategy specifications that AI coding assistants can translate into executable code, making quantitative research accessible to non-programmers.