# Estimating an (E)CCC-GARCH model

### Description

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

### Usage

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

### Arguments

`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 |

### Value

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 |

### Note

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.

### References

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.