IDEAS home Printed from
MyIDEAS: Login to save this paper or follow this series

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

  • Guillermo Benavides
Registered author(s):

    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.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: no

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

    in new window

    Date of creation: Oct 2010
    Date of revision:
    Handle: RePEc:bdm:wpaper:2010-12
    Contact details of provider: Web page:

    More information through EDIRC

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as in new window
    1. 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.).
    2. Engle III, Robert F., 2003. "Risk and Volatility: Econometric Models and Financial Practice," Nobel Prize in Economics documents 2003-4, Nobel Prize Committee.
    3. Hsieh, David A., 1993. "Implications of Nonlinear Dynamics for Financial Risk Management," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(01), pages 41-64, March.
    4. A. F. Herbst & D. D. Kare & S. C. Caples, 1989. "Hedging effectiveness and minimum risk hedge ratios in the presence of autocorrelation: Foreign currency futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 9(3), pages 185-197, 06.
    5. 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.
    6. Carlos Capistrán & Manuel Ramos Francia, 2006. "Inflation Dynamics in Latin America," Working Papers 2006-11, Banco de México.
    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. Manuel Ramos Francia & Daniel Chiquiar & Antonio E. Noriega, 2007. "Time Series Approach to Test a Change in Inflation Persistence: The Mexican Experience," Working Papers 2007-01, Banco de México.
    10. 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.
    11. Brooks, C. & Clare, A. D. & Persand, G., 2000. "A word of caution on calculating market-based minimum capital risk requirements," Journal of Banking & Finance, Elsevier, vol. 24(10), pages 1557-1574, October.
    12. 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.
    13. Anning Wei & Raymond M. Leuthold, 1998. "Long Agricultural Futures Prices: ARCH, Long Memory, or Chaos Processes?," Finance 9805001, EconWPA.
    14. Ng, Victor K & Pirrong, Stephen Craig, 1994. "Fundamentals and Volatility: Storage, Spreads, and the Dynamics of Metals Prices," The Journal of Business, University of Chicago Press, vol. 67(2), pages 203-30, April.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:bdm:wpaper:2010-12. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dirección de Sistemas)

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

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

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.