Large dynamic covariance matrices and portfolio selection with a heterogeneous autoregressive model

URN to cite this document:: urn:nbn:de:bvb:355-epub-771997
DOI to cite this document:: 10.5283/epub.77199

Honig, Igor ; Kircher, Felix

License: Creative Commons Attribution 4.0
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Date of publication of this fulltext: 17 Jul 2025 06:36

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Abstract

We propose a novel framework for modeling large dynamic covariance matrices via heterogeneous autoregressive volatility and correlation components. Our model provides direct forecasts of monthly covariance matrices and is flexible, parsimonious and simple to estimate using standard least squares methods. We address the problem of parameter estimation risks by employing nonlinear shrinkage ...