Improving Portfolio Allocation Through Covariance Matrix Filtering

35 Pages Posted: 13 Jan 2017

See all articles by Daron Golden

Daron Golden


Emlyn James Flint

Legae Peresec; Department of Actuarial Science, University of Cape Town

Date Written: October 2014


The sample covariance matrix is known to contain substantial statistical noise, making it inappropriate for use in financial decision making. Leading researchers have proposed various filtering methods that attempt to reduce the level of noise in the covariance matrix estimator. In most cases, these methods can be interpreted by analysing how they adjust the eigen-structure of the sample correlation matrix. This paper compares the filtering methods using a theoretical eigen-framework as well as a practical South African experiment. By focussing on the eigen-structure, the sources of statistical noise are identified. The sample correlation matrix suffers from excess dispersion in its eigenvalues and excess dispersion in its pairwise correlations. Bayesian shrinkage estimators that effectively remove the excess dispersion provide superior performance in terms of out-of-sample portfolio risk and turnover. Specifically, the optimal filtering method is a blend between the sample covariance matrix, its diagonal elements and the covariance matrix based on the constant correlation model.

Keywords: covariance estimation, Bayesian shrinkage, random matrix theory, regularisation, eigenstructure, covariance filtering, South African equity

JEL Classification: C11, C14, C21, C22, C4, C5, C61, G11

Suggested Citation

Golden, Daron and Flint, Emlyn James, Improving Portfolio Allocation Through Covariance Matrix Filtering (October 2014). Available at SSRN: or

Daron Golden

Independent ( email )

No Address Available
United States

Emlyn James Flint (Contact Author)

Legae Peresec ( email )

15 Cavendish Street
Cape Town, Western Cape 7700
South Africa
27117227556 (Phone)


Department of Actuarial Science, University of Cape Town ( email )

Actuarial Science Section, University of Cape Town
Private Bag X3, Rondebosch
Cape Town, Western Cape 7701
South Africa
+27 21 650 2475 (Phone)

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