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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="1.png" alt="Hands-On Financial Trading with Python" width="200"/>Hands-On Financial Trading with Python is a professional book on quantitative finance, designed to guide readers in using Python to build and backtest algorithmic trading strategies. This book begins with an introduction to the basics of algorithmic trading, then dives into financial data acquisition, preprocessing, and exploratory data analysis. The book explains in detail how to use Python's core libraries (such as NumPy, pandas, and Matplotlib) for efficient scientific computing, data manipulation, and visualization. In terms of financial applications, this book covers technical analysis, the development and implementation of trading strategies, and introduces machine learning techniques (such as time series forecasting, including ARIMA, pmdarima, and Facebook Prophet) to build predictive trading signals. In addition, this book also focuses on using Zipline and PyFolio for strategy backtesting and optimization, as well as risk management and portfolio optimization. By combining theory and practice, this book aims to help quantitative analysts, algorithmic traders, financial engineers, and data scientists master the key skills of quantitative research, strategy generation, and practical trading system deployment.
Here is a preview of the book’s main chapters:
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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。Hands-On Financial Trading with Python 是一本关于量化金融的专业书籍，旨在指导读者使用Python构建和回测算法交易策略。本书首先介绍算法交易的基础知识，随后深入探讨金融数据获取、预处理和探索性数据分析。书中详细讲解了如何利用Python的核心库（如NumPy、pandas和Matplotlib）进行高效的科学计算、数据操作与可视化。在金融应用方面，本书涵盖了技术分析、交易策略的开发与实现，并引入机器学习技术（如时间序列预测，包括ARIMA、pmdarima和Facebook Prophet）来构建预测性交易信号。此外，本书还重点介绍了使用Zipline和PyFolio进行策略回测与优化，以及进行风险管理和投资组合优化。通过理论与实践相结合的方式，本书旨在帮助量化分析师、算法交易员、金融工程师和数据科学家掌握量化研究、策略生成和实际交易系统部署的关键技能。
以下是本书的主要章节预览：
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。
Hands-On Financial Trading with Python 是一本关于量化金融的专业书籍，旨在指导读者使用Python构建和回测算法交易策略。本书首先介绍算法交易的基础知识，随后深入探讨金融数据获取、预处理和探索性数据分析。书中详细讲解了如何利用Python的核心库（如NumPy、pandas和Matplotlib）进行高效的科学计算、数据操作与可视化。在金融应用方面，本书涵盖了技术分析、交易策略的开发与实现，并引入机器学习技术（如时间序列预测，包括ARIMA、pmdarima和Facebook Prophet）来构建预测性交易信号。此外，本书还重点介绍了使用Zipline和PyFolio进行策略回测与优化，以及进行风险管理和投资组合优化。通过理论与实践相结合的方式，本书旨在帮助量化分析师、算法交易员、金融工程师和数据科学家掌握量化研究、策略生成和实际交易系统部署的关键技能。
以下是本书的主要章节预览：
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