Book Details
Before we dive into the review, let's take a look at the book details in the table below.| Title | Python for Finance |
|---|---|
| Author | Yves Hilpisch |
| Pages | 720 |
| Publisher | OTC Exchange Network |
| Publication Date | December 2018 |
Contents
The book "Python for Finance" is divided into three parts, each with several chapters. Part I introduces basic Python programming concepts and libraries such as NumPy, pandas, and matplotlib. Part II delves into financial data analysis, covering topics such as time series analysis and volatility modeling. Part III focuses on advanced topics such as machine learning and deep learning applied to finance. The book is written in a clear and concise manner, with code snippets and examples provided throughout the text. The author also provides exercises at the end of each chapter to reinforce the concepts learned.Strengths
One of the strengths of "Python for Finance" is how it bridges the gap between finance and programming. The author assumes no prior programming knowledge, making it accessible to beginners, but also covers advanced topics such as machine learning and deep learning, making it suitable for experienced programmers as well. Another strength of the book is the author's use of real-world financial data and examples. This not only reinforces the concepts learned but also provides a practical understanding of how Python can be applied in the finance industry.Weaknesses
One weakness of the book is that it assumes a basic understanding of finance. Readers with no finance background may find some of the concepts difficult to grasp. Additionally, while the book covers a wide range of topics, it may not provide enough depth for readers who want to specialize in a particular area.Download
The "Python for Finance" PDF can be downloaded from various websites. It is important to note that downloading copyrighted material without permission is illegal. Therefore, make sure that you download the book from a legitimate source.FAQ
- Is "Python for Finance" suitable for beginners?
- What programming libraries are covered in the book?
- Does the book provide exercises?
- What topics does the book cover?
Yes, the book assumes no prior programming knowledge.
The book covers NumPy, pandas, and matplotlib, among others.
Yes, there are exercises at the end of each chapter.
The book covers basic Python programming, financial data analysis, and advanced topics such as machine learning and deep learning applied to finance.
