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Financial modelling in Python [[electronic resource] /] / S. Fletcher & C. Gardner
| Financial modelling in Python [[electronic resource] /] / S. Fletcher & C. Gardner |
| Autore | Fletcher S (Shayne) |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Chichester, : Wiley, 2009 |
| Descrizione fisica | 1 online resource (246 p.) |
| Disciplina |
332.0285/5133
332.02855133 |
| Altri autori (Persone) | GardnerChristopher |
| Collana | Wiley finance series |
| Soggetto topico |
Finance - Mathematical models - Computer programs
Python (Computer program language) |
| Soggetto genere / forma | Electronic books. |
| ISBN |
0-470-68500-X
1-282-88892-7 9786612888922 0-470-74789-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Financial Modelling in Python; Contents; 1 Welcome to Python; 1.1 Why Python?; 1.1.1 Python is a general-purpose high-level programming language; 1.1.2 Python integrates well with data analysis, visualisation and GUI toolkits; 1.1.3 Python 'plays well with others'; 1.2 Common misconceptions about Python; 1.3 Roadmap for this book; 2 The PPF Package; 2.1 PPF topology; 2.2 Unit testing; 2.2.1 doctest; 2.2.2 PyUnit; 2.3 Building and installing PPF; 2.3.1 Prerequisites and dependencies; 2.3.2 Building the C++ extension modules; 2.3.3 Installing the PPF package; 2.3.4 Testing a PPF installation
3 Extending Python from C++3.1 Boost.Date Time types; 3.1.1 Examples; 3.2 Boost.MultiArray and special functions; 3.3 NumPy arrays; 3.3.1 Accessing array data in C++; 3.3.2 Examples; 4 Basic Mathematical Tools; 4.1 Random number generation; 4.2 N(.); 4.3 Interpolation; 4.3.1 Linear interpolation; 4.3.2 Loglinear interpolation; 4.3.3 Linear on zero interpolation; 4.3.4 Cubic spline interpolation; 4.4 Root finding; 4.4.1 Bisection method; 4.4.2 Newton-Raphson method; 4.5 Linear algebra; 4.5.1 Matrix multiplication; 4.5.2 Matrix inversion; 4.5.3 Matrix pseudo-inverse 4.5.4 Solving linear systems4.5.5 Solving tridiagonal systems; 4.5.6 Solving upper diagonal systems; 4.5.7 Singular value decomposition; 4.6 Generalised linear least squares; 4.7 Quadratic and cubic roots; 4.8 Integration; 4.8.1 Piecewise constant polynomial fitting; 4.8.2 Piecewise polynomial integration; 4.8.3 Semi-analytic conditional expectations; 5 Market: Curves and Surfaces; 5.1 Curves; 5.2 Surfaces; 5.3 Environment; 6 Data Model; 6.1 Observables; 6.1.1 LIBOR; 6.1.2 Swap rate; 6.2 Flows; 6.3 Adjuvants; 6.4 Legs; 6.5 Exercises; 6.6 Trades; 6.7 Trade utilities 7 Timeline: Events and Controller7.1 Events; 7.2 Timeline; 7.3 Controller; 8 The Hull-White Model; 8.1 A component-based design; 8.1.1 Requestor; 8.1.2 State; 8.1.3 Filler; 8.1.4 Rollback; 8.1.5 Evolve; 8.1.6 Exercise; 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; 9.2.1 Pricing non-callable trades; 9.2.2 Pricing callable trades; 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 Systems11.1 nth imm of year revisited; 11.2 Exercising nth imm of year from C++; 12 Python Excel Integration; 12.1 Black-scholes COM server; 12.1.1 VBS client; 12.1.2 VBA client; 12.2 Numerical pricing with PPF in Excel; 12.2.1 Common utilities; 12.2.2 Market server; 12.2.3 Trade server; 12.2.4 Pricer server; Appendices; A Python; A.1 Python interpreter modes; A.1.1 Interactive mode; A.1.2 Batch mode; A.2 Basic Python; A.2.1 Simple expressions; A.2.2 Built-in data types; A.2.3 Control flow statements; A.2.4 Functions; A.2.5 Classes; A.2.6 Modules and packages A.3 Conclusion |
| Record Nr. | UNINA-9910140162903321 |
Fletcher S (Shayne)
|
||
| Chichester, : Wiley, 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Financial modelling in Python [[electronic resource] /] / S. Fletcher & C. Gardner
| Financial modelling in Python [[electronic resource] /] / S. Fletcher & C. Gardner |
| Autore | Fletcher S (Shayne) |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Chichester, : Wiley, 2009 |
| Descrizione fisica | 1 online resource (246 p.) |
| Disciplina |
332.0285/5133
332.02855133 |
| Altri autori (Persone) | GardnerChristopher |
| Collana | Wiley finance series |
| Soggetto topico |
Finance - Mathematical models - Computer programs
Python (Computer program language) |
| ISBN |
0-470-68500-X
1-282-88892-7 9786612888922 0-470-74789-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Financial Modelling in Python; Contents; 1 Welcome to Python; 1.1 Why Python?; 1.1.1 Python is a general-purpose high-level programming language; 1.1.2 Python integrates well with data analysis, visualisation and GUI toolkits; 1.1.3 Python 'plays well with others'; 1.2 Common misconceptions about Python; 1.3 Roadmap for this book; 2 The PPF Package; 2.1 PPF topology; 2.2 Unit testing; 2.2.1 doctest; 2.2.2 PyUnit; 2.3 Building and installing PPF; 2.3.1 Prerequisites and dependencies; 2.3.2 Building the C++ extension modules; 2.3.3 Installing the PPF package; 2.3.4 Testing a PPF installation
3 Extending Python from C++3.1 Boost.Date Time types; 3.1.1 Examples; 3.2 Boost.MultiArray and special functions; 3.3 NumPy arrays; 3.3.1 Accessing array data in C++; 3.3.2 Examples; 4 Basic Mathematical Tools; 4.1 Random number generation; 4.2 N(.); 4.3 Interpolation; 4.3.1 Linear interpolation; 4.3.2 Loglinear interpolation; 4.3.3 Linear on zero interpolation; 4.3.4 Cubic spline interpolation; 4.4 Root finding; 4.4.1 Bisection method; 4.4.2 Newton-Raphson method; 4.5 Linear algebra; 4.5.1 Matrix multiplication; 4.5.2 Matrix inversion; 4.5.3 Matrix pseudo-inverse 4.5.4 Solving linear systems4.5.5 Solving tridiagonal systems; 4.5.6 Solving upper diagonal systems; 4.5.7 Singular value decomposition; 4.6 Generalised linear least squares; 4.7 Quadratic and cubic roots; 4.8 Integration; 4.8.1 Piecewise constant polynomial fitting; 4.8.2 Piecewise polynomial integration; 4.8.3 Semi-analytic conditional expectations; 5 Market: Curves and Surfaces; 5.1 Curves; 5.2 Surfaces; 5.3 Environment; 6 Data Model; 6.1 Observables; 6.1.1 LIBOR; 6.1.2 Swap rate; 6.2 Flows; 6.3 Adjuvants; 6.4 Legs; 6.5 Exercises; 6.6 Trades; 6.7 Trade utilities 7 Timeline: Events and Controller7.1 Events; 7.2 Timeline; 7.3 Controller; 8 The Hull-White Model; 8.1 A component-based design; 8.1.1 Requestor; 8.1.2 State; 8.1.3 Filler; 8.1.4 Rollback; 8.1.5 Evolve; 8.1.6 Exercise; 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; 9.2.1 Pricing non-callable trades; 9.2.2 Pricing callable trades; 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 Systems11.1 nth imm of year revisited; 11.2 Exercising nth imm of year from C++; 12 Python Excel Integration; 12.1 Black-scholes COM server; 12.1.1 VBS client; 12.1.2 VBA client; 12.2 Numerical pricing with PPF in Excel; 12.2.1 Common utilities; 12.2.2 Market server; 12.2.3 Trade server; 12.2.4 Pricer server; Appendices; A Python; A.1 Python interpreter modes; A.1.1 Interactive mode; A.1.2 Batch mode; A.2 Basic Python; A.2.1 Simple expressions; A.2.2 Built-in data types; A.2.3 Control flow statements; A.2.4 Functions; A.2.5 Classes; A.2.6 Modules and packages A.3 Conclusion |
| Record Nr. | UNINA-9910831174303321 |
|
Fletcher S (Shayne)
|
||
| Chichester, : Wiley, 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Financial modelling in Python / / S. Fletcher & C. Gardner
| Financial modelling in Python / / S. Fletcher & C. Gardner |
| Autore | Fletcher S (Shayne) |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Chichester, : Wiley, 2009 |
| Descrizione fisica | 1 online resource (246 p.) |
| Disciplina | 332.0285/5133 |
| Altri autori (Persone) | GardnerChristopher |
| Collana | Wiley finance series |
| Soggetto topico |
Finance - Mathematical models - Computer programs
Python (Computer program language) |
| ISBN |
0-470-68500-X
1-282-88892-7 9786612888922 0-470-74789-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Financial Modelling in Python; Contents; 1 Welcome to Python; 1.1 Why Python?; 1.1.1 Python is a general-purpose high-level programming language; 1.1.2 Python integrates well with data analysis, visualisation and GUI toolkits; 1.1.3 Python 'plays well with others'; 1.2 Common misconceptions about Python; 1.3 Roadmap for this book; 2 The PPF Package; 2.1 PPF topology; 2.2 Unit testing; 2.2.1 doctest; 2.2.2 PyUnit; 2.3 Building and installing PPF; 2.3.1 Prerequisites and dependencies; 2.3.2 Building the C++ extension modules; 2.3.3 Installing the PPF package; 2.3.4 Testing a PPF installation
3 Extending Python from C++3.1 Boost.Date Time types; 3.1.1 Examples; 3.2 Boost.MultiArray and special functions; 3.3 NumPy arrays; 3.3.1 Accessing array data in C++; 3.3.2 Examples; 4 Basic Mathematical Tools; 4.1 Random number generation; 4.2 N(.); 4.3 Interpolation; 4.3.1 Linear interpolation; 4.3.2 Loglinear interpolation; 4.3.3 Linear on zero interpolation; 4.3.4 Cubic spline interpolation; 4.4 Root finding; 4.4.1 Bisection method; 4.4.2 Newton-Raphson method; 4.5 Linear algebra; 4.5.1 Matrix multiplication; 4.5.2 Matrix inversion; 4.5.3 Matrix pseudo-inverse 4.5.4 Solving linear systems4.5.5 Solving tridiagonal systems; 4.5.6 Solving upper diagonal systems; 4.5.7 Singular value decomposition; 4.6 Generalised linear least squares; 4.7 Quadratic and cubic roots; 4.8 Integration; 4.8.1 Piecewise constant polynomial fitting; 4.8.2 Piecewise polynomial integration; 4.8.3 Semi-analytic conditional expectations; 5 Market: Curves and Surfaces; 5.1 Curves; 5.2 Surfaces; 5.3 Environment; 6 Data Model; 6.1 Observables; 6.1.1 LIBOR; 6.1.2 Swap rate; 6.2 Flows; 6.3 Adjuvants; 6.4 Legs; 6.5 Exercises; 6.6 Trades; 6.7 Trade utilities 7 Timeline: Events and Controller7.1 Events; 7.2 Timeline; 7.3 Controller; 8 The Hull-White Model; 8.1 A component-based design; 8.1.1 Requestor; 8.1.2 State; 8.1.3 Filler; 8.1.4 Rollback; 8.1.5 Evolve; 8.1.6 Exercise; 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; 9.2.1 Pricing non-callable trades; 9.2.2 Pricing callable trades; 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 Systems11.1 nth imm of year revisited; 11.2 Exercising nth imm of year from C++; 12 Python Excel Integration; 12.1 Black-scholes COM server; 12.1.1 VBS client; 12.1.2 VBA client; 12.2 Numerical pricing with PPF in Excel; 12.2.1 Common utilities; 12.2.2 Market server; 12.2.3 Trade server; 12.2.4 Pricer server; Appendices; A Python; A.1 Python interpreter modes; A.1.1 Interactive mode; A.1.2 Batch mode; A.2 Basic Python; A.2.1 Simple expressions; A.2.2 Built-in data types; A.2.3 Control flow statements; A.2.4 Functions; A.2.5 Classes; A.2.6 Modules and packages A.3 Conclusion |
| Record Nr. | UNINA-9910876599003321 |
|
Fletcher S (Shayne)
|
||
| Chichester, : Wiley, 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||