Muennix, M. C., Schaefer, R. and Grothe, O. (2014). Estimating correlation and covariance matrices by weighting of market similarity. Quant. Financ., 14 (5). S. 931 - 940. ABINGDON: ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD. ISSN 1469-7696

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Abstract

We discuss a weighted estimation of correlation and covariance matrices from historical financial data. To this end, we introduce a weighting scheme that accounts for the similarity of previous market conditions to the present situation. The resulting estimators are less biased and show lower variance than either unweighted or exponentially weighted estimators. The weighting scheme is based on a similarity measure that compares the current correlation structure of the market to the structures at past times. Similarity is then measured by the matrix 2-norm of the difference of probe correlation matrices estimated for two different points in time. The method is validated in a simulation study and tested empirically in the context of mean-variance portfolio optimization. In the latter case we find an enhanced realized portfolio return as well as a reduced portfolio risk compared with alternative approaches based on different strategies and estimators.

Item Type: Journal Article
Creators:
CreatorsEmailORCIDORCID Put Code
Muennix, M. C.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Schaefer, R.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Grothe, O.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
URN: urn:nbn:de:hbz:38-438557
DOI: 10.1080/14697688.2011.605075
Journal or Publication Title: Quant. Financ.
Volume: 14
Number: 5
Page Range: S. 931 - 940
Date: 2014
Publisher: ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
Place of Publication: ABINGDON
ISSN: 1469-7696
Language: English
Faculty: Unspecified
Divisions: Unspecified
Subjects: no entry
Uncontrolled Keywords:
KeywordsLanguage
Business, Finance; Economics; Mathematics, Interdisciplinary Applications; Social Sciences, Mathematical MethodsMultiple languages
URI: http://kups.ub.uni-koeln.de/id/eprint/43855

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