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Exercise

Use in production

In a corporate environment, there is often a distinction between the stage of model engineering and the stage to using the model in production. When using the model in production, it may be that the model is not re-estimated at each stage. You then use the model with fixed coefficients but integrating on each prediction day the new data. The function ugarchfilter() is designed to complete this task.

In this exercise you use a model fitted on the January 1989 till December 2007 daily S&P 500 returns to make a prediction of the future volatility in a turbulent period (September 2008) and a stable period (September 2017). The model has already been specified as is available as garchspec in the R console.

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  • Specify that you use the returns available at the end of December 2006.
  • Fix the parameters of progarchspec to the estimated parameters in garchfit.
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