Financial Modelling in Python

P1: JYS

c11 JWBK378-Fletcher April 24, 2009 8:17 Printer: Yet to come

11

Hybrid Python/C++ Pricing Systems

In Chapter 3, we saw how we may extend Python with modules written in C++. Specifically,

we studied case examples of reflecting types from the Boost.Date

Time library into Python.

Further, in section 3.1.1 we developed functionality in Python making use of those reflected

types to compute IMM dates. In this chapter we aim to show how we can exercise that

functionality from C++. What is the relevance of this? Well, it demonstrates the possibility of

‘hybrid pricing systems’. That is, systems formed from a mix of both C++ and Python. Such

potential will likely be of no small interest to those institutions that already have a considerable

investment in C++. By using the techniques about to be presented, organisations with pricing

frameworks in C++ can enjoy the many benefits Python offers while seamlessly integrating

these efforts with their existing C++ frameworks.

11.1 nth imm of year REVISITED

Our goal will be to exercise the Python code for IMM date computation functionality, presented

in section 3.1.1 from C++. As the first step in seeing how to achieve that, it is necessary for us

to review the implementation of the Python class nth

imm of year and examine in closer

detail its relationship with the C++ code on which it rests.

from ppf date time import \

weekdays \

, months

of year \

, nth

kday of