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Document Type: | Book |
---|---|
All Authors / Contributors: |
Shayne Fletcher; Christopher Gardner |
ISBN: | 9780470987841 0470987847 |
OCLC Number: | 804717367 |
Description: | VIII, 236 p. ; 23 cm + 1 Disc òptic (CD-ROM) |
Contents: | 1 Welcome to Python. 1.1 Why Python? 1.2 Common misconceptions about Python. 1.3 Roadmap for this book. 2 The PPF Package. 2.1 PPF topology. 2.2 Unit testing. 2.3 Building and installing PPF. 3 Extending Python from C++. 3.1 Boost.Date Time types. 3.2 Boost.MultiArray and special functions. 3.3 NumPy arrays. 4 Basic Mathematical Tools. 4.1 Random number generation. 4.2 N (.) 4.3 Interpolation. 4.4 Root finding. 4.5 Linear algebra. 4.6 Generalised linear least squares. 4.7 Quadratic and cubic roots. 4.8 Integration. 5 Market: Curves and Surfaces. 5.1 Curves. 5.2 Surfaces. 5.3 Environment. 6 Data Model. 6.1 Observables. 6.2 Flows. 6.3 Adjuvants. 6.4 Legs. 6.5 Exercises. 6.6 Trades. 6.7 Trade utilities. 7 Timeline: Events and Controller. 7.1 Events. 7.2 Timeline. 7.3 Controller. 8 The Hull-White Model. 8.1 A component-based design. 8.2 The model and model factories. 8.3 Concluding remarks. 9 Pricing using Numerical Methods. 9.1 A lattice pricing framework. 9.2 A Monte-Carlo pricing framework. 9.3 Concluding remarks. 10 Pricing Financial Structures in Hull-White. 10.1 Pricing a Bermudan. 10.2 Pricing a TARN. 10.3 Concluding remarks. 11 Hybrid Python/C++ Pricing Systems. 11.1 nth imm of year revisited. 11.2 Exercising nth imm of year from C++. 12 Python Excel Integration. 12.1 Black-scholes COM server. 12.2 Numerical pricing with PPF in Excel. Appendices. A Python. A.1 Python interpreter modes. A.2 Basic Python. A.3 Conclusion. B Boost.Python. B.1 Hello world. B.2 Classes, constructors and methods. B.3 Inheritance. B.4 Python operators. B.5 Functions. B.6 Enums. B.7 Embedding. B.8 Conclusion. C Hull-White Model Mathematics. D Pickup Value Regression. Bibliography. Index. |
Series Title: | Wiley finance series. |
Responsibility: | Shayne Fletcher, Christopher Gardner. |
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