An adaptive long memory conditional correlation model

Jonathan Dark

Journal of Empirical Finance, 2024, vol. 75, issue C

Abstract: We propose a conditional correlation model with long memory dependence and smooth structural change. Previous literature has considered correlation and covariance models with structural change or long memory, but this is the first paper to jointly model both features. The correlation matrix is decomposed into long and short run components. Short run correlations converge hypergeometrically towards a slow moving long run correlation matrix that evolves according to one or more flexible Fourier forms. The model is applied to two data sets: a US equity portfolio; and a US equity, bond, gold and oil portfolio. Model fit and out of sample forecasts over 1 to 60 day horizons support the proposed approach.

Keywords: Long memory; Dynamic conditional correlation; Smooth structural change; Flexible Fourier form; Forecasting; Penalised MLE (search for similar items in EconPapers)
JEL-codes: C32 C58 G11 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:75:y:2024:i:c:s0927539823001305

DOI: 10.1016/j.jempfin.2023.101463

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