multi_step_ahead_pred {rumidas} | R Documentation |
Calculates the multi–step–ahead predictions for the GARCH–MIDAS and DAGM models, according to the procedure suggested by Amendola et al. (2021).
multi_step_ahead_pred(est, h, X = NULL)
est |
The estimation object as resulting by the |
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 |
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).
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.
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.
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)