Numerical methods in finance : a matlab-based introduction / Paolo Brandimarte.

By: Brandimarte, PaoloPublisher: [S.l.] : Wiley-Interscience, 2001Edition: 1st edDescription: 416 p. ; 24 cmISBN: 0471396869 (hardcover); 9780471396864 (hardcover)DDC classification: 332.0151 Online resources: Amazon.com Summary: Balanced coverage of the methodology and theory of numerical methods in finance Numerical Methods in Finance bridges the gap between financial theory and computational practice while helping students and practitioners exploit MATLAB for financial applications. Paolo Brandimarte covers the basics of finance and numerical analysis and provides background material that suits the needs of students from both financial engineering and economics perspectives. Classical numerical analysis methods; optimization, including less familiar topics such as stochastic and integer programming; simulation, including low discrepancy sequences; and partial differential equations are covered in detail. Extensive illustrative examples of the application of all of these methodologies are also provided. The text is primarily focused on MATLAB-based application, but also includes descriptions of other readily available toolboxes that are relevant to finance. Helpful appendices on the basics of MATLAB and probability theory round out this balanced coverage. Accessible for students–yet still a useful reference for practitioners–Numerical Methods in Finance offers an expert introduction to powerful tools in finan
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Central Library (CL)
332.0151 BRA (Browse shelf) Available NBS7144
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Balanced coverage of the methodology and theory of numerical methods in finance Numerical Methods in Finance bridges the gap between financial theory and computational practice while helping students and practitioners exploit MATLAB for financial applications. Paolo Brandimarte covers the basics of finance and numerical analysis and provides background material that suits the needs of students from both financial engineering and economics perspectives. Classical numerical analysis methods; optimization, including less familiar topics such as stochastic and integer programming; simulation, including low discrepancy sequences; and partial differential equations are covered in detail. Extensive illustrative examples of the application of all of these methodologies are also provided. The text is primarily focused on MATLAB-based application, but also includes descriptions of other readily available toolboxes that are relevant to finance. Helpful appendices on the basics of MATLAB and probability theory round out this balanced coverage. Accessible for students–yet still a useful reference for practitioners–Numerical Methods in Finance offers an expert introduction to powerful tools in finan

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