Financial Modelling with Pytho
Language: English
Published by John Wiley & Sons Aug 2009, 2009
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 230.52
Quantity: 2 available
Add to basketItem description from seller
Neuware - This book will:Show the reader how to get started quickly: Although the Python programming language is a powerful object-oriented language, it's easy to learn, especially for programmers already familiar with C or C++.Show the reader how to write less code: Comparisons of program metrics (class counts, method counts, and so on) suggest that a program written in the Python programming language can be four times smaller than the same program written in C++.Show the reader how to write better code: The Python programming language encourages good coding practices, and automatic garbage collection helps you avoid memory leaks.Show the reader how to develop programs more quickly: The Python programming language is simpler than C++, and as such, your development time could be up to twice as fast when writing in it. Your programs will also require fewer lines of code.Chapter by chapter this book gradually builds up a practical body of code that will serve as an extensible financial engineering system in python. The book uses the Black-Scholes example to begin the building of the python package that will house the code that will be presented as the book progresses.Contents1 Welcome to Python1.1 Why Python 1.1.1 Python is a high-level programming language1.1.2 Python 'plays well with others'1.1.3 Common misconceptions about Python1.2 Roadmap for this book2 First steps with Python2.1 The Black-Scholes Formula2.2 Modules and Packages2.3 Unit-testing3 Extending Python from C++3.1 Boost.Datetime types3.2 Boost.MultiArray types4 Basic Mathematical Tools4.1 Random number generation4.2 N(.)4.3 Interpolation4.3.1 Interpolation in a single dimension4.3.2 Interpolation in multiple-dimensions4.4 Root-finding4.4.1 Bisection Method4.4.2 Newton-Raphson Method4.5 Quadrature4.5.1 Hermite4.5.2 Piecewise constant polynomial integration4.6 Linear Algebra4.6.1 Matrix Inversion4.6.2 Singular Value Decomposition4.6.3 Solving Tridiagonal Systems4.6.4 Solving linear systems4.6.5 Pseudo square root5 Curve and surface construction5.1 Discount Factor Curves5.2 Caplet Volatility Curves5.3 Intensity Curves5.4 Swaption Volatility Skew Cube6 Pricing using Numerical Methods6.1 Monte-Carlo pricing framework6.2 A lattice pricing framework7 The Hull-White model7.1 A component based design7.1.1 The state7.1.2 The cache7.1.3 The requestor7.1.4 The filler7.1.5 The rollback7.1.6 The evolve7.2 Pricing a Bermudan7.3 Pricing a TARN8 Hybrid Python/C++ Pricing SystemsAppendices1 A Survey of Python Programming Tools.2 Hull-White model.…
Seller Inventory # 9780470987841
- Title
- Financial Modelling with Pytho
- Author
- Fletcher
- Publisher
- John Wiley & Sons Aug 2009
- Publication year
- 2009
- Condition
- Neu
- Binding
- Kombiprodukt
- Language
- English
- ISBN 10
- 0470987847
- ISBN 13
- 9780470987841
- Item weight
- 616 grams
- Dimensions
- 250x175x18 mm
–David Louton, Professor of Finance, Bryant University
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.
"Synopsis" may belong to another edition of this title.
About the Author
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.
"About the title" may belong to another edition of this title.
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