multi_step_ahead_pred {rumidas}

Multi–step–ahead predictions of the GARCH–MIDAS–based models with and without the '–X' part.

Description

Calculates the multi–step–ahead predictions for the GARCH–MIDAS and DAGM models, according to the procedure suggested by Amendola et al. (2021).

Usage

multi_step_ahead_pred(est, h, X = NULL)

Arguments

est

The estimation object as resulting by the ugmfit function

h

The length of the multi-step-ahead predictions

X

optional. The '–X' variable. NULL by default. It hat to be equal to the 'X' used in the ugmfit function

Details

The multi–step–ahead procedure calculates the volatility predictions keeping fixed the information set at the last observation available and projecting forward the forecasts. The procedure calculates the volatility predictions conditionally to the parameters estimated in the in-sample period. Therefore, the estimation object (through the ugmfit function) has to be provided. For additional details, see Eq. (20) in Amendola et al. (2021).

Value

The multi-step-ahead predictions, for the following h days, starting from the last day of the chosen in-sample period adopted in the 'est' object.

References

Amendola A, Candila V, Gallo GM (2021). “Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model.” Economic and Statistics. doi:10.1016/j.ecosta.2020.11.001.

Examples

r_t<-sp500['2008']
X<-(rv5['2008'])^0.5
mv_m<-mv_into_mat(r_t,diff(indpro),K=12,"monthly") 
fit<-ugmfit(model="GMX",skew="YES",distribution="norm",r_t,mv_m,K=12,X=X)
### ten days predictions
multi_step_ahead_pred(fit,h=10,X)