predict {BEKKs}

Forecasting conditional volatilities with BEKK models

Description

Method for predicting a N-dimensional BEKK covariances.

Usage

## S3 method for class 'bekk'
predict(object, n.ahead = 1, ci = 0.95, ...)

## S3 method for class 'bekka'
predict(object, n.ahead = 1, ci = 0.95, ...)

## S3 method for class 'dbekk'
predict(object, n.ahead = 1, ci = 0.95, ...)

## S3 method for class 'dbekka'
predict(object, n.ahead = 1, ci = 0.95, ...)

## S3 method for class 'sbekk'
predict(object, n.ahead = 1, ci = 0.95, ...)

## S3 method for class 'sbekka'
predict(object, n.ahead = 1, ci = 0.95, ...)

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.

Value

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

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)