Author: Shayne Fletcher, Christopher Gardner
Pub Date: 2009
Size: 10 Mb
“Fletcher and Gardner have created a comprehensive resource thatwill be of interest not only to those working in the field offinance, but also to those using numerical methods in other fieldssuch as engineering, physics, and actuarial mathematics. By showinghow to combine the high-level elegance, accessibility, andflexibility of Python, with the low-level computational efficiencyof C++, in the context of interesting financial modeling problems,they have provided an implementation template which will be usefulto others seeking to jointly optimize the use of computational andhuman resources. They document all the necessary technical detailsrequired in order to make external numerical libraries availablefrom within Python, and they contribute a useful library of theirown, which will significantly reduce the start-up costs involved inbuilding financial models. This book is a must read for all thosewith a need to apply numerical methods in the valuation offinancial claims.”
–David Louton, Professor of Finance, Bryant University
This book is directed at both industry practitioners andstudents interested in designing a pricing and risk managementframework for financial derivatives using the Python programminglanguage.
It is a practical book complete with working, tested code thatguides the reader through the process of building a flexible,extensible pricing framework in Python. The pricing frameworks’loosely coupled fundamental components have been designed tofacilitate the quick development of new models. Concreteapplications to real-world pricing problems are also provided.
Topics are introduced gradually, each building on the last. Theyinclude basic mathematical algorithms, common algorithms fromnumerical analysis, trade, market and event data modelrepresentations, lattice and simulation based pricing, and modeldevelopment. The mathematics presented is kept simple and to thepoint.
The book also provides a host of information on practicaltechnical topics such as C++/Python hybrid development (embeddingand extending) and techniques for integrating Python based programswith Microsoft Excel.