BEKKs (version 1.4.5)

virf: Estimating multivariate volatility impulse response functions (VIRF) for BEKK models

Description

Method for estimating VIRFs of N-dimensional BEKK models. Currently, only VIRFs for symmetric BEKK models are implemented.

Usage

virf(
  x,
  time = 1,
  q = 0.05,
  index_series = 1,
  n.ahead = 10,
  ci = 0.9,
  time_shock = FALSE
)

Value

Returns an object of class "virf".

Arguments

x

An object of class "bekkfit" from function bekk_fit.

time

Time instance to calculate VIRFs for.

q

A number specifying the quantile to be considered for a shock on which basis the VIRFs are generated.

index_series

An integer defining the number of series for which a shock is assumed.

n.ahead

An integer defining the number periods for which the VIRFs are generated.

ci

A number defining the confidence level for the confidence bands.

time_shock

Boolean indicating if the estimated residuals at date specified by "time" shall be used as a shock.

References

Hafner CM, Herwartz H (2006). Volatility impulse responses for multivariate GARCH models: An exchange rate illustration. Journal of International Money and Finance,25,719–740.

Examples

# \donttest{

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

# 250 day ahead VIRFs and 90% CI for a Shock in the 1% quantile  of Bonds (i.e. series=2)
# shock is supposed to occur at day 500
x2 <- virf(x1, time = 500, q = 0.01, index_series=2, n.ahead = 500, ci = 0.90)
plot(x2)
# }