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Forecasting Short-Run Inflation Volatility using Futures Prices: An Empirical Analysis from a Value at Risk Perspective

Author

Listed:
  • Guillermo Benavides

    () (Banco de México)

Abstract

In this research paper, ARCH models are applied in order to estimate the Value-at-Risk (VaR) of an inflation-index futures portfolio for several time-horizons. The empirical analysis is carried out for Mexican inflation-indexed futures traded at the Mexican Derivatives Exchange (MEXDER). To analyse the VaR with time horizons of more than one trading day bootstrapping simulations were applied. The results show that these models are relatively accurate for time horizons of one trading day. However, the volatility persistence of ARCH models is reflected with relatively high VaR estimates for longer time horizons. This is considered undesirable given that an unnecessary amount of capital must be set aside in order to meet Minimum Capital Risk Requirements for a futures portfolio. By estimating confidence intervals in the VaR, it is possible to have certain confidence about the future range of inflation (or extreme inflation values) for a specified time horizon

Suggested Citation

  • Guillermo Benavides, 2010. "Forecasting Short-Run Inflation Volatility using Futures Prices: An Empirical Analysis from a Value at Risk Perspective," Revista de Administración, Finanzas y Economía (Journal of Management, Finance and Economics), Tecnológico de Monterrey, Campus Ciudad de México, vol. 4(2), pages 1-27.
  • Handle: RePEc:ega:rafega:201007
    as

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    File URL: http://alejandria.ccm.itesm.mx/egap/documentos/2010V4A7Benavides.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Volatilidad asimétrica; remuestreo; modelo GARCH; modelo TARCH; inflación; futuros indizados a la inflación; México; Valor en Riesgo; persistencia en la volatilidad;

    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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