Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices

Maurizio Daniele (), Winfried Pohlmeier () and Aygul Zagidullina
Additional contact information
Maurizio Daniele: Department of Economics, University of Konstanz, Germany
Aygul Zagidullina: Department of Economics, University of Konstanz, Germany

Working Paper series from Rimini Centre for Economic Analysis

Abstract: We propose a novel estimation approach for the covariance matrix based on the l_1-regularized approximate factor model. Our sparse approximate factor (SAF) covariance estimator allows for the existence of weak factors and hence relaxes the pervasiveness assumption generally adopted for the standard approximate factor model. We prove consistency of the covariance matrix estimator under the Frobenius norm as well as the consistency of the factor loadings and the factors. Our Monte Carlo simulations reveal that the SAF covariance estimator has superior properties in finite samples for low and high dimensions and different designs of the covariance matrix. Moreover, in an out-of-sample portfolio forecasting application the estimator uniformly outperforms alternative portfolio strategies based on alternative covariance estimation approaches and modeling strategies including the 1/N-strategy.

Keywords: Approximate Factor model; weak factors; l1-regularization; high dimensional covariance matrix; portfolio allocation (search for similar items in EconPapers)
JEL-codes: C38 C55 G11 G17 (search for similar items in EconPapers)
Date: 2020-02
New Economics Papers: this item is included in nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://rcea.org/RePEc/pdf/wp20-03.pdf

Related works:
Working Paper: Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices (2019)
Working Paper: Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rim:rimwps:20-03

Access Statistics for this paper

More papers in Working Paper series from Rimini Centre for Economic Analysis Contact information at EDIRC.
Bibliographic data for series maintained by Marco Savioli ().