Python金融应用实战:量化金融与金融工程

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《Python for Finance》是一本专为金融领域的专业人士和对量化金融、金融工程感兴趣的读者编写的实用指南。该书由Yuxing Yan撰写,由Packt Publishing出版,版权属于2014年。书中内容旨在帮助读者构建现实生活中的Python应用,将Python这一强大的编程语言与金融领域的实践相结合。 在创作这本书的过程中,作者Yuxing Yan得到了来自Packt Publishing团队的大力支持,包括Llewellyn F. Rozario、Swati Kumari、Arwa Manasawala、Ruchita Bhansali、Apeksha Chitnis和Pramila Balan等专业人员的辛勤工作。外部审阅人如Martin Olveyra、Mourad MOURAFIQ和Loucas Parayiannis也提供了宝贵的建议、意见和批评,他们的贡献对于确保书籍内容的质量至关重要。 书中强调了版权保护,未经出版商事先书面许可,任何部分不得复制、存储或通过任何形式或手段传播。尽管作者和Packt Publishing已尽最大努力保证信息的准确性,但书中的内容不带任何形式的保证,无论是明示还是暗示的。作者及出版商不对由于本书直接或间接造成的损失承担责任。 《Python for Finance》于2014年4月首次发布,生产参考编号为1180414。这本著作涵盖了广泛的主题,包括Python基础、数据分析处理、金融模型开发、算法交易、风险管理、以及金融科技工具的实战应用。它不仅适合初学者系统学习金融领域中的Python技术,也适合有一定经验的开发者寻求提升其在金融工程和量化分析方面的技能。 通过阅读这本书,读者可以掌握如何利用Python进行金融建模、优化投资组合、执行回测、编写交易策略,以及理解如何利用Python的科学计算库(如NumPy、Pandas和SciPy)处理大量金融数据。此外,书中可能还会涉及金融市场的API集成、机器学习在金融预测中的应用等内容,使读者能够紧跟现代金融市场的发展趋势。 《Python for Finance》是一本兼具理论和实践的教程,它不仅提供深入的理论知识,还提供了丰富的代码示例和案例研究,使读者能够在实际工作中运用Python解决金融问题,提升金融领域的技术竞争力。
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eBook Description: Hands-On Python for Finance: Learn and implement quantitative finance using popular Python libraries like NumPy, pandas, and Keras Python is one of the most popular languages used for quantitative finance. With this book, you’ll explore the key characteristics of Python for finance, solve problems in finance, and understand risk management. The book starts with major concepts and techniques related to quantitative finance, and an introduction to some key Python libraries. Next, you’ll implement time series analysis using pandas and DataFrames. The following chapters will help you gain an understanding of how to measure the diversifiable and non-diversifiable security risk of a portfolio and optimize your portfolio by implementing Markowitz Portfolio Optimization. Sections on regression analysis methodology will help you to value assets and understand the relationship between commodity prices and business stocks. In addition to this, you’ll be able to forecast stock prices using Monte Carlo simulation. The book will also highlight forecast models that will show you how to determine the price of a call option by analyzing price variation. You’ll also use deep learning for financial data analysis and forecasting. In the concluding chapters, you will create neural networks with TensorFlow and Keras for forecasting and prediction. By the end of this Hands-On Python for Finance book, you will be equipped with the skills you need to perform different financial analysis tasks using Python.