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Asymmetric Volatility Relevance in Risk Management: An Empirical Analysis using Stock Index Futures

Author

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  • Guillermo Benavides

    (Banco de México)

Abstract

El objetivo del presente documento es considerar la relevancia de las asimetrías en la estimación de la volatilidad. La metodología consiste en estimar modelos de ARCH-tipo y volatilidades implícitas de opciones (IV) para el Valor-en-Rriesgo (VaR). Lo anterior para una cartera de futuros de índices bursátiles para varios horizontes temporales. El análisis empírico se realiza para los contratos de futuros para los Índices Standard and Poors 500 y el de la Bolsa Mexicana de Valores. De acuerdo con los resultados, el modelo IV es superior en términos de precisión en comparación con los modelos de ARCH-tipo. Se recomienda considerar las ganancias estadísticas relevantes cuando se incluyen asimetrías con respecto a cuando no se usan asimetrías. Las referidas ganancias van de 4 alrededor de 150 puntos base de requerimiento mínimo de capital en riesgo. La presente investigación es original, ya que, documenta la importancia de tener en cuenta los efectos asimétricos con IV y ARCH-tipo en los pronósticos de volatilidad en el análisis de gestión de riesgos. Se concluye que la metodología permite ganancias en términos monetarios.

Suggested Citation

  • Guillermo Benavides, 2021. "Asymmetric Volatility Relevance in Risk Management: An Empirical Analysis using Stock Index Futures," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(TNEA), pages 1-18, Septiembr.
  • Handle: RePEc:imx:journl:v:16:y:2021:i:tnea:a:4
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    References listed on IDEAS

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    More about this item

    Keywords

    Volatilidad asimétrica; GARCH; TARCH; volatilidad implícita; futuros índices accionarios; Valor en Riesgo; México;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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