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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="Financial Theory with Python" width="200"/>Financial Theory with Python is a professional book on quantitative finance, covering the intrinsic connections between finance, mathematics and programming (especially Python), aiming to provide readers with the basic tools needed to enter the world of computational finance. This book takes a unique approach by using mathematical concepts as a common background on which to learn financial thinking and programming techniques.
This book provides an in-depth exploration of financial theory, financial data modeling, and the application of Python in computational finance. It addresses fundamental problems in finance such as pricing, decision-making, equilibrium, and asset allocation through static and dynamic financial modeling. The book covers core mathematical techniques such as stochastic calculus, martingale theory, Brownian motion, and Ito's lemma, and applies them to the valuation of options and other derivatives (such as replicating portfolios or risk-neutral pricing) and to financial models such as the capital asset pricing model. In addition, this book also introduces Python libraries commonly used in financial modeling such as NumPy, pandas, Matplotlib, and SymPy.
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。Financial Theory with Python 是一本关于量化金融的专业书籍，涵盖了金融、数学和编程（特别是Python）之间的内在联系，旨在为读者提供进入计算金融世界所需的基础工具。本书采用一种独特的方法，将数学概念作为共同背景，在此基础上学习金融思想和编程技术。
本书深入探讨了金融理论、金融数据建模以及Python在计算金融中的应用。它通过静态和动态金融建模来解决金融中的基本问题，例如定价、决策、均衡和资产配置。书中涵盖了随机微积分、鞅论、布朗运动和伊藤引理等核心数学技术，并将其应用于期权和其他衍生品的估值（如复制投资组合或风险中性定价）以及资本资产定价模型等金融模型。此外，本书还介绍了NumPy、pandas、Matplotlib和SymPy等在金融建模中常用的Python库。
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。
Financial Theory with Python 是一本关于量化金融的专业书籍，涵盖了金融、数学和编程（特别是Python）之间的内在联系，旨在为读者提供进入计算金融世界所需的基础工具。本书采用一种独特的方法，将数学概念作为共同背景，在此基础上学习金融思想和编程技术。
本书深入探讨了金融理论、金融数据建模以及Python在计算金融中的应用。它通过静态和动态金融建模来解决金融中的基本问题，例如定价、决策、均衡和资产配置。书中涵盖了随机微积分、鞅论、布朗运动和伊藤引理等核心数学技术，并将其应用于期权和其他衍生品的估值（如复制投资组合或风险中性定价）以及资本资产定价模型等金融模型。此外，本书还介绍了NumPy、pandas、Matplotlib和SymPy等在金融建模中常用的Python库。
以下是本书的主要章节预览：
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