Forecasting Short-Run Inflation Volatility using Futures Prices: An Empirical Analysis from a Value at Risk Perspective
AbstractIn 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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Bibliographic InfoPaper provided by Banco de México in its series Working Papers with number 2010-12.
Date of creation: Oct 2010
Date of revision:
Bootstrapping; inflation; inflation-indexed futures; Mexico; value at risk; volatility persistence.;
Find related papers by 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 &bull 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-11-27 (All new papers)
- NEP-CBA-2010-11-27 (Central Banking)
- NEP-FOR-2010-11-27 (Forecasting)
- NEP-MON-2010-11-27 (Monetary Economics)
- NEP-RMG-2010-11-27 (Risk Management)
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- Daniel Chiquiar & Antonio Noriega & Manuel Ramos-Francia, 2010.
"A time-series approach to test a change in inflation persistence: the Mexican experience,"
Taylor & Francis Journals, vol. 42(24), pages 3067-3075.
- 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.
- 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.
- 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.
- 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.
- Carlos Capistrán & Manuel Ramos-Francia, 2009.
"Inflation Dynamics In Latin America,"
Contemporary Economic Policy,
Western Economic Association International, vol. 27(3), pages 349-362, 07.
- 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.
- 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.
- 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.
- Engle III, Robert F., 2003.
"Risk and Volatility: Econometric Models and Financial Practice,"
Nobel Prize in Economics documents
2003-4, Nobel Prize Committee.
- Robert Engle, 2004. "Risk and Volatility: Econometric Models and Financial Practice," American Economic Review, American Economic Association, vol. 94(3), pages 405-420, June.
- 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.
- 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.
- Anning Wei & Raymond M. Leuthold, 1998. "Long Agricultural Futures Prices: ARCH, Long Memory, or Chaos Processes?," Finance 9805001, EconWPA.
- repec:cup:cbooks:9780521694681 is not listed on IDEAS
- 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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