Arbeitspapier
The power of (non-)linear shrinking: A review and guide to covariance matrix estimation
Many econometric and data-science applications require a reliable estimate of the covariance matrix, such as Markowitz portfolio selection. When the number of variables is of the same magnitude as the number of observations, this constitutes a difficult estimation problem; the sample covariance matrix certainly will not do. In this paper, we review our work in this area, going back 15+ years. We have promoted various shrinkage estimators, which can be classified into linear and nonlinear. Linear shrinkage is simpler to understand, to derive, and to implement. But nonlinear shrinkage can deliver another level of performance improvement, especially if overlaid with stylized facts such as time-varying co-volatility or factor models.
- Sprache
-
Englisch
- Erschienen in
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Series: Working Paper ; No. 323
- Klassifikation
-
Wirtschaft
Estimation: General
Financial Econometrics
Portfolio Choice; Investment Decisions
- Thema
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dynamic conditional correlations
factor models
large-dimensional asymptotics
Markowitz portfolio selection
rotation equivariance
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Ledoit, Olivier
Wolf, Michael
- Ereignis
-
Veröffentlichung
- (wer)
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University of Zurich, Department of Economics
- (wo)
-
Zurich
- (wann)
-
2020
- DOI
-
doi:10.5167/uzh-170642
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Ledoit, Olivier
- Wolf, Michael
- University of Zurich, Department of Economics
Entstanden
- 2020
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