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Matemática Financiera con MATLAB© = Mathematical Finance with MATLAB©


  • Merino, María

    () (Departamento de Matemática Aplicada, Estadística e Investigación Operativa. Universidad del País Vasco)

  • Vadillo, Fernando

    () (Departamento de Matemática Aplicada, Estadística e Investigación Operativa. Universidad del País Vasco)


Este artículo quiere mostrar los usos y las utilidades de MATLAB©, tanto en la enseñanza como en las aplicaciones de la Matemática Financiera. El artículo tiene dos partes bien diferenciadas: en la primera se hace un estudio estadístico de los datos del Ibex 35 durante gran parte del año 2006 y en la segunda se comentan y aplican los métodos matemáticos utilizados para estimar la prima de las opciones financieras. = The aim of this paper is to present the MATLAB© tools for the teaching and the applications in the Mathematical Finance. This paper has two parts; the first one is a statistical study of the movement of the prices for the securities in the Ibex 35 during the year 2006. The second one is about the different procedures: the Black-Scholes equation, Monte-Carlo method and Binomial method, to calculate the prices of financial options.

Suggested Citation

  • Merino, María & Vadillo, Fernando, 2007. "Matemática Financiera con MATLAB© = Mathematical Finance with MATLAB©," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 4(1), pages 35-55, December.
  • Handle: RePEc:pab:rmcpee:v:4:y:2007:i:1:p:35-55

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    References listed on IDEAS

    1. David A. Hensher & Stewart Jones, 2007. "Forecasting Corporate Bankruptcy: Optimizing the Performance of the Mixed Logit Model," Abacus, Accounting Foundation, University of Sydney, vol. 43(3), pages 241-264.
    2. Altman, Edward I., 2005. "An emerging market credit scoring system for corporate bonds," Emerging Markets Review, Elsevier, vol. 6(4), pages 311-323, December.
    3. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
    4. Felipe Zurita, 2008. "La Predicción de la Insolvencia de Empresas Chilenas," Documentos de Trabajo 336, Instituto de Economia. Pontificia Universidad Católica de Chile..
    5. Tamura, Karin Ayumi & Giampaoli, Viviana, 2013. "New prediction method for the mixed logistic model applied in a marketing problem," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 202-216.
    6. repec:bla:joares:v:18:y:1980:i:1:p:109-131 is not listed on IDEAS
    7. repec:bla:joares:v:22:y:1984:i::p:59-82 is not listed on IDEAS
    8. Edward I Altman & Tara K N Baidya & Luis Manoel Ribeiro Dias, 1979. "Assessing Potential Financial Problems for Firms in Brazil," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 10(2), pages 9-24, June.
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    More about this item


    MATLAB; Ibex 35; valoración de opciones; componentes principales; ecuaciones de Black-Scholes; método Monte Carlo; método binomial = MATLAB; Ibex 35; options valuation; principal components; Black-Scholes equations; Monte Carlo method; binomial method;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing


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