Build production-ready quantitative trading systems with multi-agent architecture
用多智能体架构构建可落地的量化交易系统
Author 作者: Wayland Zhang
| Language | Status | Progress | Link |
|---|---|---|---|
| 🇨🇳 中文 | ✅ Complete | 22 lessons + 30 background + 4 appendices | 阅读中文版 → |
| 🇺🇸 English | ✅ Complete | 22 lessons + 30 background + 4 appendices | Read English → |
|
Not a strategy holy grail, but teaching you to build production-ready quant systems. Most quant tutorials stop at:
These let you "play" quant, not "do" quant. Real quant systems need to answer:
This book uses multi-agent architecture to answer these questions: different agents handle different responsibilities (signals, risk, execution), collaborating to make trading decisions. |
不是策略圣杯，而是教你构建可落地的量化交易系统。 市面上的量化教程大多停留在：
这些只能让你"玩"量化，不能让你"做"量化。 真正的量化系统需要回答：
这本书用多智能体架构回答这些问题：不同的 Agent 负责不同的职责（信号、风控、执行），协作完成交易决策。 |
The book has 5 parts, 22 lessons | 全书分为 5 个部分、22 课：
| Part | Topic 主题 | Lessons 课程 | Core Content 核心内容 |
|---|---|---|---|
| 1 | Quick Start 快速体验 | 1 | Quant landscape, multi-agent intuition 量化全景图、多智能体直觉 |
| 2 | Fundamentals 量化基础 | 7 | Markets, statistics, strategies, data, backtesting 市场、统计、策略、数据、回测 |
| 3 | Machine Learning 机器学习 | 2 | Supervised learning, from models to agents 监督学习、从模型到Agent |
| 4 | Multi-Agent 多智能体 | 7 | Architecture, regime detection, LLM, risk control 架构、Regime、LLM、风控 |
| 5 | Production 生产实战 | 5 | Costs, execution, operations, projects 成本、执行、运维、实战 |
Plus 30 background articles and 4 appendices | 另有 30篇背景知识 和 4篇附录
Prerequisites:
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前置要求：
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ai-quant-book/
├── manuscript/
│ ├── cn/ # 中文版 (Complete 已完成)
│ │ ├── Part1-快速体验/
│ │ ├── Part2-量化基础/
│ │ ├── Part3-机器学习/
│ │ ├── Part4-多智能体/
│ │ ├── Part5-生产与实战/
│ │ └── Resources & Links/
│ ├── en/ # English (Complete)
│ │ ├── Part1-Quick-Start/
│ │ ├── Part2-Quant-Fundamentals/
│ │ ├── Part3-Machine-Learning/
│ │ ├── Part4-Multi-Agent/
│ │ ├── Part5-Production/
│ │ └── Resources-Links/
└── README.md
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Recommended Path:
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→ 阅读中文版 推荐路径：
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Quantitative trading involves risk. Invest carefully.
量化交易有风险，投资需谨慎。
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This book is educational and does not constitute investment advice.
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本书是教育性质，不构成投资建议。
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This work is licensed under CC BY-NC-SA 4.0.
本书内容采用 CC BY-NC-SA 4.0 协议。
"Whatever happens in the stock market today has happened before and will happen again." — Jesse Livermore
"We search through historical data looking for anomalous patterns that we believe are predictive of future price action." — Jim Simons