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Forecasting Exchange Rate Volatility: The Superior Performance of Conditional Combinations of Time Series and Option Implied Forecasts

  • Guillermo Benavides
  • Carlos Capistrán

This paper provides empirical evidence that combinations of option implied and time series volatility forecasts that are conditional on current information are statistically superior to individual models, unconditional combinations, and hybrid forecasts. Superior forecasting performance is achieved by both, taking into account the conditional expected performance of each model given current information, and combining individual forecasts. The method used in this paper to produce conditional combinations extends the application of conditional predictive ability tests to select forecast combinations. The application is for volatility forecasts of the Mexican Peso-US Dollar exchange rate, where realized volatility calculated using intra-day data is used as a proxy for the (latent) daily volatility.

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File URL: http://www.banxico.org.mx/publicaciones-y-discursos/publicaciones/documentos-de-investigacion/banxico/%7BD569C50A-987B-C362-5963-8ED392255658%7D.pdf
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Paper provided by Banco de México in its series Working Papers with number 2009-01.

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Date of creation: Jan 2009
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Handle: RePEc:bdm:wpaper:2009-01
Contact details of provider: Web page: http://www.banxico.org.mx

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