Get startedGet started for free

Starting values

The estimation of a GARCH model requires to optimize the likelihood. This optimization may fail in case of bad starting values. Fortunately, Alexios Ghalanos, the author of the R package rugarch, did a great job in setting the optimization defaults such that the optimization is accurate in most of the cases. If you have a doubt, you can use the method setstart() to try your own starting values and verify that it leads to a similar result in terms of estimated parameters and likelihood.

Here you can test this in case of the daily EUR/USD returns in EURUSDret and assuming a constant mean standard GARCH model with Student t distribution. The model specification is available in the console as garchspec.

This exercise is part of the course

GARCH Models in R

View Course

Exercise instructions

  • Estimate the model garchspec using default starting values.
  • Print the estimated parameters and the likelihood.
  • Set other starting values and re-estimate.
  • Print the estimated parameters and the likelihood.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Estimate using default starting values
garchfit <- ___

# Print the estimated parameters and the likelihood
___
___

# Set other starting values and re-estimate
___(garchspec) <- ___(alpha1 = 0.05, beta1 = 0.9, shape = 6) 
garchfit <- ___

# Print the estimated parameters and the likelihood
___
___
Edit and Run Code