Название: QuantLib Python Cookbook (Updated 04/2021)
Автор: Luigi Ballabio, Goutham Balaraman
Издательство: Leanpub
Год: 2021-04-20
Страниц: 285
Язык: английский
Формат: pdf (true), mobi, epub + code
Размер: 13.40 MB

Quantitative finance in Python: a hands-on, interactive look at the QuantLib library through the use of Jupyter notebooks as working examples The posts and screencasts use Jupyter 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 also includes 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 recipes in this cookbook are written as Jupyter notebooks, and follow their structure: blocks of explanatory text, like the one you’re reading now, are mixed with cells containing Python code (inputs) and the results of executing it (outputs). It’s easy enough to translate the Python code shown in this book into the corresponding C++ code.