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Medidas alternativas de volatilidad en el mercado de valores peruano

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  • Rafael Nivin Valdiviezo

Abstract

Este documento busca comparar las principales metodologías de cálculo de la volatilidad para el mercado de valores peruano. Se presentan tres métodos de cálculo de volatilidad, el modelo EWMA, el modelo GARCH y el de Volatilidad estocástica(SV). La comparación de estas metodologías se realizó a través del cálculo del Valor en Riesgo y un ejercicio de backtesting. Los resultados muestran que si bien las tres metodologías de estimación generan medidas de volatilidad similares, los modelos GARCH y SV son superiores al modelo EWMA en términos del cálculo del Valor en Riesgo. Asimismo, el ejercicio de backtesting realizado no muestra diferencias significativas entre los modelos GARCH y de volatilidad estocástica.

Suggested Citation

  • Rafael Nivin Valdiviezo, 2019. "Medidas alternativas de volatilidad en el mercado de valores peruano," Revista de Análisis Económico y Financiero, Universidad de San Martín de Porres, vol. 1(03), pages 07-14.
    • Handle: RePEc:alp:revaef:03-02
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    References listed on IDEAS

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    1. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 361-393.
    2. Lengua Lafosse, Patricia & Rodríguez, Gabriel, 2018. "An empirical application of a stochastic volatility model with GH skew Student's t-distribution to the volatility of Latin-American stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 155-173.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
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