Usage
dccspec(uspec, VAR = FALSE, robust = FALSE, lag = 1, lag.max = NULL,
lag.criterion = c("AIC", "HQ", "SC", "FPE"), external.regressors = NULL,
robust.control = list("gamma" = 0.25, "delta" = 0.01, "nc" = 10, "ns" = 500),
dccOrder = c(1,1), model = c("DCC", "aDCC", "FDCC"), groups = rep(1, length(uspec@spec)),
distribution = c("mvnorm", "mvt", "mvlaplace"), start.pars = list(), fixed.pars = list())Arguments
uspec
A uGARCHmultispec object created by calling
multispec on a list of univariate GARCH specifications. VAR
Whether to fit a VAR model for the conditional mean.
robust
Whether to use the robust version of VAR.
lag.max
The maximum VAR lag to search for best fit.
lag.criterion
The criterion to use for choosing the best lag when
lag.max is not NULL.
external.regressors
Allows for a matrix of common pre-lagged external
regressors for the VAR option.
robust.control
The tuning parameters to the robust regression
including the proportion to trim (gamma), the critical value for
re-weighted estimator (delta), the number of subsets (ns)
and the number of C-st
dccOrder
The DCC autoregressive order.
model
The DCC model to use, with a choice of the symmetric DCC,
asymmetric (aDCC) and the Flexible DCC (FDCC). See notes for more details.
groups
The groups corresponding to each asset in the FDCC model, where
these are assumed and checked to be contiguous and increasing (unless only 1 group).
distribution
The multivariate distribution. Currently the multivariate
Normal, Student and Laplace are implemented, and only the Normal for the FDCC model.
start.pars
(optional) Starting values for the DCC parameters (starting
values for the univariate garch specification should be passed directly
via the uspec object).