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How large is large? : prelimin...
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Wolf, Michael
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1
The power of (non-)linear shrinking : a review and guide to covariance matrix estimation
Ledoit, Olivier
;
Wolf, Michael
-
2019
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...
Persistent link: https://www.econbiz.de/10012018920
Saved in:
2
Shrinkage estimation of large covariance matrices : keep it simple, statistician?
Ledoit, Olivier
;
Wolf, Michael
-
2019
Under rotation-equivariant decision theory, sample covariance matrix eigenvalues can be optimally shrunk by recombining sample eigenvectors with a (potentially nonlinear) function of the unobservable population covariance matrix. The optimal shape of this function reflects the loss/risk that is...
Persistent link: https://www.econbiz.de/10012030045
Saved in:
3
Large dynamic covariance matrices
Engle, Robert F.
;
Ledoit, Olivier
;
Wolf, Michael
-
2017
-
Revised version
for conditional heteroskedasticity; a favored model is Dynamic Conditional
Correlation
(DCC), derived from the ARCH …
Persistent link: https://www.econbiz.de/10011640555
Saved in:
4
Large dynamic covariance matrices
Engle, Robert F.
;
Ledoit, Olivier
;
Wolf, Michael
- In:
Journal of business & economic statistics : JBES ; a …
37
(
2019
)
2
,
pp. 363-375
Persistent link: https://www.econbiz.de/10012178181
Saved in:
5
Efficient sorting : a more powerful test for cross-sectional anomalies
Ledoit, Olivier
;
Wolf, Michael
;
Zhao, Zhao
- In:
Journal of financial econometrics
17
(
2019
)
4
,
pp. 645-686
Persistent link: https://www.econbiz.de/10012152240
Saved in:
6
Large dynamic covariance matrices
Engle, Robert F.
;
Ledoit, Olivier
;
Wolf, Michael
-
2016
for conditional heteroskedasticity; a favored model is Dynamic Conditional
Correlation
(DCC), derived from the ARCH …
Persistent link: https://www.econbiz.de/10011518597
Saved in:
7
Nonlinear shrinkage of the covariance matrix for portfolio selection : Markowitz meets Goldilocks
Ledoit, Olivier
;
Wolf, Michael
- In:
The review of financial studies
30
(
2017
)
12
,
pp. 4349-4388
Persistent link: https://www.econbiz.de/10011924578
Saved in:
8
Honey, I shrunk the sample covariance matrix
Ledoit, Olivier
(
contributor
);
Wolf, Michael
(
contributor
)
-
2003
-
[Elektronische Ressource]
Persistent link: https://www.econbiz.de/10002055527
Saved in:
9
Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size
Ledoit, Olivier
(
contributor
);
Wolf, Michael
(
contributor
)
-
2001
-
[Elektronische Ressource]
Persistent link: https://www.econbiz.de/10001625987
Saved in:
10
Improved estimation of the covariance matrix of stock returns with an application to portofolio selection
Ledoit, Olivier
(
contributor
);
Wolf, Michael
(
contributor
)
-
2001
-
[Elektronische Ressource]
Persistent link: https://www.econbiz.de/10001627199
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