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Cluster GARCH

Chen Tong, Peter Reinhard Hansen, Ilya Archakov

arXiv 11 Jun 2024 · Econometrics · publishedJournal of Business and Economic Statistics (2025) · 1 citations (OpenAlex)

arXiv:2406.06860 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We introduce a novel multivariate GARCH model with flexible convolution-t distributions that is applicable in high-dimensional systems. The model is called Cluster GARCH because it can accommodate cluster structures in the conditional correlation matrix and in the tail dependencies. The expressions for the log-likelihood function and its derivatives are tractable, and the latter facilitate a score-drive model for the dynamic correlation structure. We apply the Cluster GARCH model to daily returns for 100 assets and find it outperforms existing models, both in-sample and out-of-sample. Moreover, the convolution-t distribution provides a better empirical performance than the conventional multivariate t-distribution.

Citation extraction

36
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77
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36
distinct cited
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Archakov, I. and Hansen, P. R (2024) A canonical representation of block matrices with applications to covariance and correlation matrices self1.00074100%
2Hansen, P. R. and Tong, C (2024) Convolution-t distributions self1.00053100%
3Archakov, I. and Hansen, P. R (2021) A new parametrization of correlation matrices self0.9619589%
4Archakov, I., Hansen, P. R., and Lunde, A (2020) A multivariate Realized GARCH model self0.92843100%
5Creal, D., Koopman, S. J., and Lucas, A (2013) Generalized autoregressive score models with applications0.92843100%
6Engle, R. and Kelly, B (2012) Dynamic equicorrelation0.92843100%
7Hafner, C. M. and Wang, L (2023) A dynamic conditional score model for the log correlation matrix0.92843100%
8Creal, D., Koopman, S. J., and Lucas, A (2012) A dynamic multivariate heavy-tailed model for time-varying volatilities and correlations0.8435460%
9Oh, D. H. and Patton, A. J (2023) Dynamic factor copula models with estimated cluster assignments0.73732100%
10Aielli, G. P (2013) Dynamic conditional correlation: on properties and estimation0.64422100%

Showing the top 10 of 36 scored citations.