Hartkopf, Jan Patrick 
ORCID: 0000-0002-3704-1856
.
Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models.
Empir. Econ..
HEIDELBERG:
PHYSICA-VERLAG GMBH & CO.
ISSN 1435-8921
Abstract
We propose a dynamic factor state-space model for the prediction of high-dimensional realized covariance matrices of asset returns. Using a block LDL decomposition of the joint covariance matrix of assets and factors, we express the realized covariance matrix of the individual assets similar to an approximate factor model. We model the individual parts, i.e., the factor and residual covariances as well as the factor loadings, independently via a tractable state-space approach. This results in closed-form Matrix-F predictive densities for the distinct covariance elements and Student's t predictive densities for the factor loadings. In an out-of-sample forecasting and portfolio selection exercise we compare the performance of the proposed factor model under different specifications of the residual dynamics. These includes block diagonal residuals based on the GICS sector classifications and strict diagonality assumptions as well as combinations of both using linear shrinkage. We find that the proposed model performs very well in an empirical application to realized covariance matrices for 225 NYSE-traded stocks using the well-known Fama-French factors and sector-specific factors represented by exchange traded funds.
| Item Type: | Journal Article | ||||||||
| Creators: |
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| URN: | urn:nbn:de:hbz:38-660022 | ||||||||
| DOI: | 10.1007/s00181-022-02245-1 | ||||||||
| Journal or Publication Title: | Empir. Econ. | ||||||||
| Publisher: | PHYSICA-VERLAG GMBH & CO | ||||||||
| Place of Publication: | HEIDELBERG | ||||||||
| ISSN: | 1435-8921 | ||||||||
| Language: | English | ||||||||
| Faculty: | Unspecified | ||||||||
| Divisions: | Unspecified | ||||||||
| Subjects: | no entry | ||||||||
| Uncontrolled Keywords: |
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| URI: | http://kups.ub.uni-koeln.de/id/eprint/66002 |
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