The AR(1)-GJR GARCH dynamics of MSFT returns

You have seen in the video that the sign of the autoregressive parameter in the AR(1) model depends on the market reaction to news

A positive value of \(\rho \) is consistent with the interpretation that markets under-react to news leading to a momentum in returns. A negative value of \(\rho \) is consistent with the interpretation that markets over-react to news leading to a reversion in returns.

Are the daily Microsoft returns characterized by a momentum or a reversal effect in their AR(1) dynamics? Let's find this out by estimating the parameters of the AR(1)-GJR GARCH model using the daily Microsoft returns in msftret.

armaOrder = c(1,2) corresponds to an ARMA(1,2) model. An AR(1) model is the same as ARMA(1,0).
Complete the mean.model argument in ugarchspec to specify the AR(1) model to be used.
Estimate the model.
Print the first two coefficients of the estimated GARCH model.

Take Hint (-30 XP)

Exercise

The AR(1)-GJR GARCH dynamics of MSFT returns

Instructions