Not logged in.

Quick Search - Contribution

Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs
Organization Unit
Authors
  • Marc Paolella
  • Pawel Polak
  • Patrick Walker
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Journal Title Journal of Banking and Finance
Publisher Elsevier
Geographical Reach international
ISSN 0378-4266
Volume 125
Page Range 106046
Date 2021
Abstract Text Covariance matrix forecasts for portfolio optimization have to balance sensitivity to new data points with stability in order to avoid excessive rebalancing. To achieve this, a new orthogonal GARCH model for a multivariate set of non-Gaussian asset returns is proposed. The conditional return distribution is multivariate generalized hyperbolic and the dispersion matrix dynamics are driven by the leading factors in a principal component decomposition. Each of these leading factors is endowed with a univariate GARCH structure, while the remaining eigenvalues are kept constant over time. Joint maximum likelihood estimation of all model parameters is performed via an expectation maximization algorithm, and is applicable in high dimensions. The new model generates realistic correlation forecasts even for large asset universes and captures rising pairwise correlations in periods of market distress better than numerous competing models. When applied to portfolio optimization, it generates strategies with lower turnover and maximum drawdown, and superior risk-adjusted returns net of transaction costs. Moreover, unlike its competitors, it performs well in the sudden market downturn triggered by the global COVID-19 pandemic.
Official URL https://www.sciencedirect.com/science/article/abs/pii/S0378426621000042
Digital Object Identifier 10.1016/j.jbankfin.2021.106046
Other Identification Number merlin-id:20865
Export BibTeX
EP3 XML (ZORA)