Isbn: 9780470987841 - financial modelling in python (the wiley finance series) (9 Ergebnisse)

hardcover. Zustand: Acceptable. Please see the condition note after this for details, if this is missing please consider Acceptable to mean poor quality that could include major staining, water damage, writing, missing dustjacket, etc etc. Our books are dispatched from a Yorkshire former cotton mill. We list via barcode/ISBN so please note that the images are stock images and may not be the exact copy you receive, furthermore the details about edition and year might not be accurate as many publishers reuse the same ISBN for multiple editions and as we simply scan a barcode or enter an ISBN we do not check the validity of the edition data when listing. If you're looking for an exact edition please don't order (at least not without checking with us first, although we don't always have time to check). We aim to dispatch prompty, the service used will depend on order value and book size. We can ship to most countries, see our shipping policies. Payment is via Abe only.…

Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:9780470987841.…

Hardcover. Zustand: Very Good. Zustand des Schutzumschlags: Very Good. Hardcover with unclipped dust jacket, in very good condition. Includes CD-ROM. Jacket is slightly scuffed, and edges are creased. Board spine ends are slightly bumped. Content is as unread. LW.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. pp. viii + 236 Illus.

Zustand: New. In English.

Zustand: New. 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. Series: Wiley Finance Series. Num Pages: 244 pages, Illustrations. BIC Classification: KFF. Category: (P) Professional & Vocational. Dimension: 256 x 177 x 24. Weight in Grams: 612. . 2009. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.…

Hardcover. Zustand: Brand New. hardback/cd-rom edition. 236 pages. 9.75x6.75x1.00 inches. In Stock.

Kombiprodukt. Zustand: Neu. 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. …