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A better model for EUR/USD returns

In the previous exercise you have analyzed the statistical significance of the estimated parameters of the AR(1) GJR GARCH model with skewed student t distribution for the daily EUR/USD returns. The conclusion is that we should simplify the GARCH model used. Let's therefore take a constant mean standard GARCH model with student t distribution. We fix the mean value to zero and use variance targeting.

Este ejercicio forma parte del curso

GARCH Models in R

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Instrucciones del ejercicio

  • Complete the code to estimate a constant mean standard GARCH model with student t distribution and variance targeting.
  • Use setfixed() to impose that the mean parameter equals 0.
  • Estimate the model.
  • Check visually that these changes lead to a volatility series close to the one using flexgarchfit.

Ejercicio interactivo práctico

Prueba este ejercicio completando el código de muestra.

# Specify model with constant mean, standard GARCH and student t
tgarchspec <- ugarchspec(mean.model = list(armaOrder = ___),
                         variance.model = list(model = ___, variance.targeting = ___),
                         distribution.model = ___)

# Fix the mu parameter at zero
 ___(tgarchspec) <- list("mu" = 0)

# Estimate the model
tgarchfit <- ___(data = EURUSDret, spec = tgarchspec)

# Verify that the differences in volatility are small
plot(sigma(___) - ___(flexgarchfit))
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