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

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  • Guillermo Benavides
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    Abstract

    In this research paper ARCH-type 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 analyze 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-type models is reflected with relatively high VaR estimates for longer time horizons. These results have implications for short-term inflation forecasts. 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.

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    File URL: http://www.banxico.org.mx/publicaciones-y-discursos/publicaciones/documentos-de-investigacion/banxico/%7B3D80DA42-A6AC-BB0C-9104-B145111BDE86%7D.pdf
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    Bibliographic Info

    Paper provided by Banco de México in its series Working Papers with number 2010-12.

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    Date of creation: Oct 2010
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    Handle: RePEc:bdm:wpaper:2010-12

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    Web page: http://www.banxico.org.mx
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    Related research

    Keywords: Bootstrapping; inflation; inflation-indexed futures; Mexico; value at risk; volatility persistence.;

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    1. Daniel Chiquiar & Antonio Noriega & Manuel Ramos-Francia, 2010. "A time-series approach to test a change in inflation persistence: the Mexican experience," Applied Economics, Taylor & Francis Journals, vol. 42(24), pages 3067-3075.
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    3. Hsieh, David A, 1991. " Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-77, December.
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    7. Giampiero Gallo & Barbara Pacini, 2000. "The effects of trading activity on market volatility," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 163-175.
    8. G. Benavides & P. N. Snowden, 2006. "Futures for farmers: Hedging participation and the Mexican corn scheme," Journal of Development Studies, Taylor & Francis Journals, vol. 42(4), pages 698-712.
    9. Engle III, Robert F., 2003. "Risk and Volatility: Econometric Models and Financial Practice," Nobel Prize in Economics documents 2003-4, Nobel Prize Committee.
    10. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    11. Pong, Shiuyan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2004. "Forecasting currency volatility: A comparison of implied volatilities and AR(FI)MA models," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2541-2563, October.
    12. Anning Wei & Raymond M. Leuthold, 1998. "Long Agricultural Futures Prices: ARCH, Long Memory, or Chaos Processes?," Finance 9805001, EconWPA.
    13. repec:cup:cbooks:9780521694681 is not listed on IDEAS
    14. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
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