Optimal estimation of a large-dimensional covariance matrix under Stein’s loss

Olivier Ledoit and Michael Wolf

No 122, ECON - Working Papers from Department of Economics - University of Zurich

Abstract: This paper introduces a new method for deriving covariance matrix estimators that are decision-theoretically optimal within a class of nonlinear shrinkage estimators. The key is to employ large-dimensional asymptotics: the matrix dimension and the sample size go to infinity together, with their ratio converging to a finite, nonzero limit. As the main focus, we apply this method to Stein’s loss. Compared to the estimator of Stein (1975, 1986), ours has five theoretical advantages: (1) it asymptotically minimizes the loss itself, instead of an estimator of the expected loss; (2) it does not necessitate post-processing via an ad hoc algorithm (called “isotonization”) to restore the positivity or the ordering of the covariance matrix eigenvalues; (3) it does not ignore any terms in the function to be minimized; (4) it does not require normality; and (5) it is not limited to applications where the sample size exceeds the dimension. In addition to these theoretical advantages, our estimator also improves upon Stein’s estimator in terms of finite-sample performance, as evidenced via extensive Monte Carlo simulations. To further demonstrate the effectiveness of our method, we show that some previously suggested estimators of the covariance matrix and its inverse are decision-theoretically optimal in the large-dimensional asymptotic limit with respect to the Frobenius loss function.

Keywords: Large-dimensional asymptotics; nonlinear shrinkage estimation; random matrix theory; rotation equivariance; Stein’s loss (search for similar items in EconPapers)
JEL-codes: C13 (search for similar items in EconPapers)
Date: 2013-05, Revised 2017-03
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.zora.uzh.ch/id/eprint/78074/37/econwp122.pdf (application/pdf)

Related works:
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:zur:econwp:122

Access Statistics for this paper

More papers in ECON - Working Papers from Department of Economics - University of Zurich Contact information at EDIRC.
Bibliographic data for series maintained by Severin Oswald ().