This function predicts variance of error terms in time series based on a trained GARCH model, i.e. a fitted "hanaml.GARCH" object.

# S3 method for GARCH
predict(model, n.ahead = NULL)

Arguments

model

R6Class object
A "GARCH" object for prediction.

n.ahead

integer, optional
Specifies the number of steps of future volatility to be forecasted.
Defaults to 1.

Value

Named list of DataFrames

  • variance: Forecast values of future volatility(variance).

  • stats: Related statistics.

Examples

Assuming gh is a fitted "hanaml.GARCH" object:


  > res <- predict(gh, n.ahead = 3)
  > res$variance
    STEP VARIANCE RESIDUAL
  1    1 1.415806       NA
  2    2 1.633979       NA
  3    3 1.865262       NA
  

See also