Computational Finance presents a modern computational approach to mathematical finance within the Windows environment, and contains financial algorithms, mathematical proofs and computer code in C/C++. The author illustrates how numeric components can be developed which allow financial routines to be easily called by the complete range of Windows applications, such as Excel, Borland Delphi, Visual Basic and Visual C++.
These components permit software developers to call mathematical finance functions more easily than in corresponding packages. Although these packages may offer the advantage of interactive interfaces, it is not easy or computationally efficient to call them programmatically as a component of a larger system. The components are therefore well suited to software developers who want to include finance routines into a new application.
Typical readers are expected to have a knowledge of calculus, differential equations, statistics, Microsoft Excel, Visual Basic, C++ and HTML.
Additional features such as: working computer code, demonstration applications and also pdf versions of several research articles can be found on the companion site.
- Enables reader to incorporate advanced financial modelling techniques in Windows compatible software
Aids the development of bespoke software solutions covering GARCH volatility modelling, derivative pricing with Partial Differential Equations, VAR, bond and stock options
Includes companion site
Financial Analysts; Financial Engineers; Numerical Analysts; Investment Portfolio Managers; MATLAB Users in Investment Banking, Commercial Banking, Insurance, and Corporate Finance; MSc courses in Computational Finance
Using Numerical Software Components with Microsoft Windows: Introduction; Dynamic Link Libraries (DLLs); ActiveX and COM; A financial derivative pricing example; ActiveX components and numerical optimization; XML and transformation using XSL; Epilogue; Pricing Assets: Introduction; Analytical methods and single asset European options; Numeric methods and single asset American options; Monte Carlo simulation; Multiasset European and American options; Dealing with missing data; Financial Econometrics: Introduction; GARCH models; Nonlinear GARCH; GARCH conditional probability distributions; Maximum likelihood parameter estimation; Analytic derivatives of the log likelihood; GJR-GARCH algorithms; GARCH software; GARCH process identification; Multivariate time series; Appendices.
- No. of pages:
- © Butterworth-Heinemann 2003
- 17th December 2003
- eBook ISBN:
- Hardcover ISBN:
…there are a number of books that describe the numerical methods available for solving the resultant equations in each of these areas. But the final step of coding the numerical models in a suitable environment has not, up to this point, been particularly well covered. Until now. My next choice, Computational Finance: Numerical Methods for Pricing Financial Instruments, written by George Levy and published by Elsevier Butterworth Heinemann as part of the Elsevier finance series, does precisely that. It also includes a [companion site] full of code and examples in environments including Visual Basic in Excel, C, C++, as well as more advanced environments such as HTML, XML, Delphi and C#.net. This is the first in what I expect will become a growing area, which may mean that financial engineering coders will finally be able to throw out their old copies of Numerical Recipes. One of the Top Ten financial engineering titles published in 2003-2004 - Richard Norgate, Ph.D., Financial Engineering News