Financial Modelling in Python

  • 2h 45m
  • C. Gardner, S. Fletcher
  • John Wiley & Sons (UK)
  • 2009

This book is directed at both industry practitioners and students interested in designing a pricing and risk management framework for financial derivatives using the Python programming language.

It is a practical book complete with working, tested code that guides the reader through the process of building a flexible, extensible pricing framework in Python. The pricing frameworks' loosely coupled fundamental components have been designed to facilitate the quick development of new models. Concrete applications to real-world pricing problems are also provided.

Topics are introduced gradually, each building on the last. They include basic mathematical algorithms, common algorithms from numerical analysis, trade, market and event data model representations, lattice and simulation based pricing, and model development. The mathematics presented is kept simple and to the point.

The book also provides a host of information on practical technical topics such as C++/Python hybrid development (embedding and extending) and techniques for integrating Python based programs with Microsoft Excel.

About the Authors

SHAYNE FLETCHER has a BSc. from the University of Sydney, Australia. He has had more than 10 years experience working for major investment banks in London, The Netherlands and Japan. In 2009 he founded QuantSoft (quantsoft.co.jp) providing technical consulting services to meet the financial engineering programming needs of its clients.

CHRISTOPHER GARDNER has a PhD in Applied Mathematics from King's College, London. He began his career working for UKAEA Fusion at Culham Laboratory before moving to the City of London. He has 10 years experience working as a Quantitative analyst. He is currently working on the pricing of Life derivatives for the Asset Management Pricing Desk at Swiss Re.

In this Book

  • Welcome to Python
  • The PPF Package
  • Extending Python from C++
  • Basic Mathematical Tools
  • Market—Curves and Surfaces
  • Data Model
  • Timeline—Events and Controller
  • The Hull-White Model
  • Pricing using Numerical Methods
  • Pricing Financial Structures in Hull-White
  • Hybrid Python/C++ Pricing Systems
  • Python Excel Integration
  • Bibliography
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