Python for Finance

Part II. Financial Analytics and Development

This part of the book represents its core. It introduces the most important Python libraries, techniques, and approaches for financial analytics and application development. The sheer number of topics covered in this part makes it necessary to focus mainly on selected, and partly rather specific, examples and use cases.

The chapters are organized according to certain topics such that this part can be used as a reference to which the reader can come to look up examples and details related to a topic of interest. This core part of the book consists of the following chapters:

• Chapter 4 on Python data types and structures
• Chapter 5 on 2D and 3D visualization with matplotlib
• Chapter 6 on the handling of financial time series data
• Chapter 7 on (performant) input/output operations
• Chapter 8 on performance techniques and libraries
• Chapter 9 on several mathematical tools needed in finance
• Chapter 10 on random number generation and simulation of stochastic processes
• Chapter 11 on statistical applications with Python
• Chapter 12 on the integration of Python and Excel
• Chapter 13 on object-oriented programming with Python and the development of (simple) graphical user interfaces (GUIs)
• Chapter 14 on the integration of Python with web technologies as well as the development of web-based applications and web services