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DCC-GARCH model/Evidence
Method evidence record

DCC-GARCH model

The DCC-GARCH model, introduced by Engle (2002), extends univariate GARCH to capture time-varying correlations between multiple financial time series. It decomposes the multivariate conditional covariance matrix into individual volatility processes and a dynamic correlation matrix, allowing correlations to fluctuate over time while remaining computationally tractable even with many series.

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Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroscedasticity Model
Taxonomic method record · regression-model / econometrics
  • Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. · DOI 10.1198/073500102288618487
  • Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987-1007. · DOI 10.2307/1912773
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Related methods

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Taxonomic bucketARCH modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketEGARCH modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketGranger Causality Testmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketTGARCH modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketVector Autoregressionmachine-suggested · Relational suggestion, not evidence.

Evidence status

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Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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