Navigation auf zora.uzh.ch

Search ZORA

ZORA (Zurich Open Repository and Archive)

DDOS: due to massive botnet requests against our ‘Advanced Search’ we have restricted access to UZH (local and VPN). Thank you for your understanding.

Numerical implementation of the QuEST function

Ledoit, Olivier; Wolf, Michael (2017). Numerical implementation of the QuEST function. Computational Statistics & Data Analysis, 115:199-223.

Abstract

Certain estimation problems involving the covariance matrix in large dimensions are considered. Due to the breakdown of finite-dimensional asymptotic theory when the dimension is not negligible with respect to the sample size, it is necessary to resort to an alternative framework known as large-dimensional asymptotics. Recently, an estimator of the eigenvalues of the population covariance matrix has been proposed that is consistent according to a mean-squared criterion under large-dimensional asymptotics. It requires numerical inversion of a multivariate nonrandom function called the QuEST function. The numerical implementation of this QuEST function in practice is explained through a series of six successive steps. An algorithm is provided in order to compute the Jacobian of the QuEST function analytically, which is necessary for numerical inversion via a nonlinear optimizer. Monte Carlo simulations document the effectiveness of the code.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Economics
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Physical Sciences > Computational Mathematics
Physical Sciences > Computational Theory and Mathematics
Physical Sciences > Applied Mathematics
Uncontrolled Keywords:Large-dimensional asymptotics, numerical optimization, Random Matrix Theory, spectrum estimation
Scope:Discipline-based scholarship (basic research)
Language:English
Date:November 2017
Deposited On:18 Jan 2018 13:42
Last Modified:17 Jun 2025 01:35
Publisher:Elsevier
ISSN:0167-9473
Additional Information:Also published as Department of Economics, Working Paper No. 215 (see https://doi.org/10.5167/uzh-120492).
OA Status:Closed
Free access at:Related URL. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.csda.2017.06.004
Related URLs:https://www.zora.uzh.ch/id/eprint/120492/
Other Identification Number:merlin-id:15774

Metadata Export

Statistics

Citations

Dimensions.ai Metrics
41 citations in Web of Science®
38 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

59 downloads since deposited on 18 Jan 2018
0 downloads since 12 months
Detailed statistics

Authors, Affiliations, Collaborations

Similar Publications