George Levy currently works as a quantitative analyst at RWE, and has provided technical consultancy to numerous financial institutions, In addition he has also published articles on numerical modelling, mathematical finance and software engineering. He is the author of Computational Finance: Numerical Methods for Pricing Financial Derivatives. His interests include: Monte Carlo simulation, Microsoft technologies and derivative valuation.

"…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

• 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.

George Levy currently works as a quantitative analyst at RWE, and has provided technical consultancy to numerous financial institutions, In addition he has also published articles on numerical modelling, mathematical finance and software engineering. He is the author of Computational Finance: Numerical Methods for Pricing Financial Derivatives. His interests include: Monte Carlo simulation, Microsoft technologies and derivative valuation.

"…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

• 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.