Description Usage Arguments Value Note References See Also

This function computes the robust standard errors of the estimates of a DCC-GARCH model.

1 | ```
dcc.results(u, garch.para, dcc.para, h, model)
``` |

`u` |
a matrix of the data used for estimating the (E)DCC-GARCH model |

`garch.para` |
a vector of the estimates of the volatility parameters |

`dcc.para` |
a vector of the estimates of the DCC parameters |

`h` |
a matrix of the estimated conditional variances |

`model` |
a character string describing the model. |

A matrix with the estimates in the first row, and the standard errors in the second row.

`dcc.results`

is called from `dcc.estimation`

.
When `model="diagonal"`

, only the diagonal entries in A and B are used.

Engle, R.F. and K. Sheppard (2001),
“Theoretical and Empirical Properties of Dynamic
Conditional Correlation Multivariate GARCH.”
*Stern Finance Working Paper Series*
FIN-01-027 (Revised in Dec. 2001),
New York University Stern School of Business.

Engle, R.F. (2002),
“Dynamic Conditional Correlation: A Simple Class of
Multivariate Generalized Autoregressive Conditional
Heteroskedasticity Models.”
*Journal of Business and Economic Statistics*
**20**, 339–350.

ccgarch documentation built on May 29, 2017, 12:58 p.m.

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