R: (Wald test, volatility spillover) BEKK-GARCH how to extract the asymptotic covariance matrix of the ML estimates? mgarchBEKK or BEKKs

Example code:

library(mgarchBEKK)
library(BEKKs)

#mgarchBEKK version (H IS SINGULAR!... message does not happen with my data, but it does in this simulated example):

 ## Simulate series:
    simulated <- simulateBEKK(2, 1000, c(1,1))

 ## Prepare the matrix:
    simulated <- do.call(cbind, simulated$eps)

 ## Estimate with default arguments:
    estimated1 <- BEKK(simulated)

 ## Standard errors:
    se <- estimated$asy.se.coef


#BEKKs version
    data <- StocksBonds #data comes with package
    spec <- bekk_spec()
    estimated2 <- bekk_fit(spec, data)
    summary(bekk_fit)

I am trying to extract the asymptotic covariance matrix of the ML estimates from either the BEKKs or mgarchBEKK estimation procedures for the BEKK-GARCH model.

The mgarchBEKK package gives us the standard errors, and the BEKKs package gives us the t-values of the parameters.

I would like to do the Wald test to check if any of the off-diagnals of my "A" or "G" matrix are neq 0 for the purposes of volatility spillover.

Can anyone help with how I might extract the asymptotic covariance matrix of the ML estimates of the BEKK-GARCH model?

Thank you for your help.