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This book is organized by [TheQuantHackers Community] (https://llmquant.com/) and provides PDF downloads. It is only for learning and communication. The copyright belongs to the original author.
This book is organized by [TheQuantHackers Community] (https://llmquant.com/) and provides PDF downloads. It is only for learning and communication. The copyright belongs to the original author.
<img src="cover.jpg" alt="Algorithmic Trading" width="200"/>Written by quantitative trading expert Ernest P. Chan, this book provides an in-depth discussion of the development, testing and implementation process of algorithmic trading strategies. The book not only introduces in detail a variety of core strategies such as statistical arbitrage, momentum trading, and mean reversion, but also emphasizes the practicality of applying scientific methods to strategy development. Combining his own practical experience, the author explains how to use statistical models, advanced computer algorithms, and mathematical techniques such as Kalman filtering and cointegration testing to discover patterns and trends from massive financial data. This book provides a complete strategy development framework and covers applications in a variety of financial instruments such as stocks, ETFs, currencies, and futures. It also provides an in-depth discussion of risk management and strategy evaluation methods, aiming to help readers build and optimize their own automated trading systems.
本书籍由TheQuantHackers社区整理, 并提供PDF下载, 只供学习交流使用, 版权归原作者所有。本书由量化交易专家Ernest P. Chan撰写，深入探讨了算法交易策略的开发、测试与实现过程。书中不仅详细介绍了统计套利、动量交易和均值回归等多种核心策略，更强调了将科学方法应用于策略开发的实践性。作者结合自身实战经验，阐述了如何利用统计模型、高级计算机算法以及如卡尔曼滤波、协整性检验等数学技术，从海量金融数据中发现模式和趋势。本书提供了完整的策略开发框架，并涵盖了在股票、ETF、货币和期货等多种金融工具中的应用，同时深入讨论了风险管理和策略评估方法，旨在帮助读者构建和优化自己的自动化交易系统。
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