Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/83752
Authors: 
Benavides, Guillermo
Capistrán, Carlos
Year of Publication: 
2009
Series/Report no.: 
Working Papers, Banco de México 2009-01
Abstract: 
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.
Subjects: 
Composite Forecasts
Forecast Evaluation
GARCH
Implied volatility
Mexican Peso - U.S. Dollar Exchange Rate
Regime-Switching
JEL: 
C22
C52
C53
G10
Document Type: 
Working Paper
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