Dynamic Conditional Correlation

@article{Engle2002DynamicCC,
  title={Dynamic Conditional Correlation},
  author={Robert F. Engle},
  journal={Journal of Business \& Economic Statistics},
  year={2002},
  volume={20},
  pages={339 - 350}
}
  • R. Engle
  • Published 1 July 2002
  • Mathematics
  • Journal of Business & Economic Statistics
Time varying correlations are often estimated with multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations. They are not linear but can often be estimated very simply with univariate or two-step… 

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Title Stata.com Mgarch — Multivariate Garch Models

  • Economics
Description Syntax Remarks and examples References Also see Description mgarch estimates the parameters of multivariate generalized autoregressive conditional-heteroskedasticity (MGARCH) models.
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