BEKKs (version 1.4.5)

predict: Forecasting conditional volatilities with BEKK models

Description

Method for predicting a N-dimensional BEKK covariances.

Usage

# S3 method for bekk
predict(object, n.ahead = 1, ci = 0.95, ...)
# S3 method for bekka
predict(object, n.ahead = 1, ci = 0.95, ...)
# S3 method for dbekk
predict(object, n.ahead = 1, ci = 0.95, ...)
# S3 method for dbekka
predict(object, n.ahead = 1, ci = 0.95, ...)
# S3 method for sbekk
predict(object, n.ahead = 1, ci = 0.95, ...)
# S3 method for sbekka
predict(object, n.ahead = 1, ci = 0.95, ...)

Value

Returns a S3 class "bekkForecast" object containing the conditional volatility forecasts and respective confindence bands.

Arguments

object

A fitted bekk model of class "bekkFit" from the bekk_fit function

n.ahead

Number of periods to forecast conditional volatility. Default is a one-period ahead forecast.

ci

Floating point in [0,1] defining the niveau for confidence bands of the conditional volatility forecast. Default is 95 per cent niveau confidence bands.

...

Further parameters to be passed on to the function.

Examples

#'
data(StocksBonds)
obj_spec <- bekk_spec()
x1 <- bekk_fit(obj_spec, StocksBonds, QML_t_ratios = FALSE, max_iter = 50, crit = 1e-9)

x2 <- predict(x1, n.ahead = 1)