[Statlist] Statistics Seminar, Friday 13 March, 14h15 at EPFL

[Schaffner Portillo Maroussia]

STATISTICS SEMINAR at EPFL

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Friday 13 March, 2020 - 14h15

CM 1 221<https://plan.epfl.ch/?room==CM%201%20221>



Prof. Michael Wolf<https://www.econ.uzh.ch/en/people/faculty/wolf.html>

University of Zurich



will be speaking on :



Shrinkage Estimation of Large Covariance Matrices: Keep It Simple, Statistician?



Abstract:

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 to be minimized.

We solve the problem of optimal covariance matrix estimation under a variety of loss functions motivated by statistical precedent, probability theory, and differential geometry. A key ingredient of our nonlinear shrinkage methodology s a new estimator of the angle between sample and population eigenvectors, without making strong assumptions on the population eigenvalues.

We also introduce a broad family of covariance matrix estimators that can handle all regular functional transformations of the population covariance matrix under large-dimensional asymptotics.

In addition, we compare via Monte Carlo simulations our methodology to two simpler ones from the literature, linear shrinkage and shrinkage based on the spiked covariance model.

Best wishes,

Maroussia Schaffner
EPFL SB SMAT
Station 8
CH-1015 Lausanne



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