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Oops! I Shrunk the Sample Covariance Matrix Again: Blockbuster Meets Shrinkage

De Nard, Gianluca (2022). Oops! I Shrunk the Sample Covariance Matrix Again: Blockbuster Meets Shrinkage. Journal of Financial Econometrics, 20(4):569-611.

Abstract

Existing shrinkage techniques struggle to model the covariance matrix of asset returns in the presence of multiple-asset classes. Therefore, we introduce a Blockbuster shrinkage estimator that clusters the covariance matrix accordingly. Besides the definition and derivation of a new asymptotically optimal linear shrinkage estimator, we propose an adaptive Blockbuster algorithm that clusters the covariance matrix even if the (number of) asset classes are unknown and change over time. It displays superior all-around performance on historical data against a variety of state-of-the-art linear shrinkage competitors. Additionally, we find that for small- and medium-sized investment universes the proposed estimator outperforms even recent nonlinear shrinkage techniques. Hence, this new estimator can be used to deliver more efficient portfolio selection and detection of anomalies in the cross-section of asset returns. Furthermore, due to the general structure of the proposed Blockbuster shrinkage estimator, the application is not restricted to financial problems.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Finance
Dewey Decimal Classification:330 Economics
Scope:Discipline-based scholarship (basic research)
Language:English
Date:October 2022
Deposited On:28 Oct 2022 06:47
Last Modified:20 Sep 2024 03:38
Publisher:Oxford University Press
ISSN:1479-8409
OA Status:Green
Free access at:Related URL. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/jjfinec/nbaa020
Official URL:https://academic.oup.com/jfec/article-abstract/20/4/569/5960228
Related URLs:https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3400062 (Organisation)
Other Identification Number:merlin-id:19516
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