Название: QuantLib Python Cookbook (Updated 10/2022)
Автор: Luigi Ballabio, Goutham Balaraman
Издательство: Leanpub
Год: 2022-10-29
Страниц: 286
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Quantitative finance in Python: a hands-on, interactive look at the QuantLib library through the use of IPython notebooks as working examples.

The book collects updated posts from Goutham's blog and the transcripts of the screencasts that Luigi is publishing on YouTube.

The posts and screencasts use IPython notebooks to demonstrate the QuantLib library. Together, they provide a sort of cookbook that showcases features of the library by means of working examples and provides guidance to its use.

Among other content, the book will also include notebooks that reproduce the results from the often-cited Ametrano and Bianchetti paper, Everything You Always Wanted to Know About Multiple Interest Rate Curve Bootstrapping but Were Afraid to Ask.

If you're interested in the architecture of QuantLib and want to know how to extend it, you might want to look at Implementing QuantLib, too.

The choice of the QuantLib Python bindings and the IPython Notebook was due to their interactivity, which make it easier to demonstrate features, and the fact that the platform provides out of the box excellent modules like Matplotlib for graphing and pandas for data analysis.

This choice might seem to leave C++ users out in the cold. However, it’s easy enough to translate the Python code shown here into the corresponding C++ code. An example of such translation is shown in the appendix.