This function estimates an (E)CCC-GARCH(1,1) model and returns estimates, estimated volatility and various diagnostic statistics.

1 | ```
eccc.estimation(a, A, B, R, dvar, model, method="BFGS")
``` |

`a` |
initial values for constants |

`A` |
initial values for an ARCH parameter matrix |

`B` |
initial values for a GARCH parameter matrix |

`R` |
initial values a constant conditional correlation matrix |

`dvar` |
a matrix of data used for (E)CCC-GARCH estimation |

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

`method` |
a character string specifying the optimisation method in |

A list with components:

`out` |
a |

`h` |
the estimated conditional variances |

`std.resid` |
a matrix of the standardised residuals |

`opt` |
the detailed results of the optimisation |

`para.mat` |
vectorised parameter estimates |

The standardised residuals are calculated through dividing the original series by the estimated conditional standard deviations. See, for instance, p.303 of Bollerslev (1990) for details.

Bollerslev, T. (1990), “Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model”,
*Review of Economics and Statistics*, **20**, 498–505.

Nakatani, T. and T. Ter\"asvirta (2009),
“Testing for Volatility Interactions in the Constant Conditional Correlation GARCH Model”,
*Econometrics Journal*, **12**, 147–163.

Nakatani, T. and T. Ter\"asvirta (2008),
“Appendix to *Testing for Volatility Interactions in the Constant Conditional Correlation GARCH Model*”
Department of Economic Statistics, Stockholm School of Economics,
available at http://swopec.hhs.se/hastef/abs/hastef0649.htm.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.