The class is returned by calling the function `dccsim`

.

`msim`

:Object of class

`"vector"`

Multivariate simulation list.`model`

:Object of class

`"vector"`

Model specification list.

Class `"'>mGARCHsim"`

, directly.
Class `"'>GARCHsim"`

, by class "mGARCHsim", distance 2.
Class `"'>rGARCH"`

, by class "mGARCHsim", distance 3.

- fitted
`signature(object = "DCCsim")`

: The conditional mean simulated data matrix given additional argument ‘sim’ denoting the simulation run (`m.sim`

) to return values for.- rcor
`signature(object = "DCCsim")`

: The simulated dynamic conditional correlation array given additional arguments ‘sim’ denoting the simulation run (`m.sim`

) to return values for, and ‘type’ (either “R” for the correlation else will return the Q matrix). A further argument ‘output’ allows to switch between “array” and “matrix” returned object.- rcov
`signature(object = "DCCsim")`

: The simulated dynamic conditional covariance array given additional argument ‘sim’ denoting the simulation run (`m.sim`

) to return values for. A further argument ‘output’ allows to switch between “array” and “matrix” returned object.- sigma
`signature(object = "DCCsim")`

: The univariate simulated conditional sigma matrix given additional argument ‘sim’ (`m.sim`

) denoting the simulation run to return values for.- show
`signature(object = "DCCsim")`

: Summary.

Engle, R.F. and Sheppard, K. 2001, Theoretical and empirical properties of
dynamic conditional correlation multivariate GARCH, *NBER Working Paper*.