IDEAS home Printed from https://ideas.repec.org/a/ega/rafega/201403.html
   My bibliography  Save this article

Cálculo de VaR a partir de simulaciones Monte Carlo de rendimientos de activos financieros, con distribuciones no paramétricas y dependientes, utilizando el Método de Iman-Conover

Author

Listed:
  • Juan Sampieri Espinoza

    (Tecnológico de Monterrey)

  • Barbara Ruth Trejo Becerril

    (Grupo Financiero HSBC)

  • Luis Manuel González de Salceda Ruiz

    (Tecnológico de Monterrey)

Abstract

The main purpose of this research work is to present a Monte Carlo model focused in the simulation of vectors with financial assets returns, starting from historical empirical returns series, in which the simulated series have the same probability distributions as the empirical (no distribution is assumed a priori) and save between then the same rank correlation as the observed. The case study shows the application of the model to a portfolio constituted by 30 stocks of the Mexican IPC, for which 100,000 simulations of daily returns for each stock are performed, the frequency distribution of the portfolio is obtained, and VaR is calculated with a 99 % confidence level, for a time horizon of one day

Suggested Citation

  • Juan Sampieri Espinoza & Barbara Ruth Trejo Becerril & Luis Manuel González de Salceda Ruiz, 2014. "Cálculo de VaR a partir de simulaciones Monte Carlo de rendimientos de activos financieros, con distribuciones no paramétricas y dependientes, utilizando el Método de Iman-Conover," Revista de Administración, Finanzas y Economía (Journal of Management, Finance and Economics), Tecnológico de Monterrey, Campus Ciudad de México, vol. 8(1), pages 37-59.
    • Handle: RePEc:ega:rafega:201403
    as

    Download full text from publisher

    File URL: http://alejandria.ccm.itesm.mx/egap/documentos/2014V8A3Sampieri-Trejo-GonzalezdeSalceda.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Simulación Monte Carlo; Método de Iman-Conover; Valor en Riesgo;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ega:rafega:201403. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: José Antonio Núñez (email available below). General contact details of provider: https://edirc.repec.org/data/emitemx.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.