Analytical nonlinear shrinkage of large-dimensional covariance matrices
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References listed on IDEAS
- Ledoit, Olivier & Wolf, Michael, 2004.
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CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Olivier Ledoit & Michael Wolf, 2019. "The power of (non-)linear shrinking: a review and guide to covariance matrix estimation," ECON - Working Papers 323, Department of Economics - University of Zurich.
- Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Data-driven covariance estimators for high-dimensional minimum-variance portfolios," Papers 1910.13960, arXiv.org, revised Dec 2019.
- Olivier Ledoit & Michael Wolf, 2019. "Shrinkage estimation of large covariance matrices: keep it simple, statistician?," ECON - Working Papers 327, Department of Economics - University of Zurich.
More about this item
KeywordsKernel estimation; Hilbert transform; large-dimensional asymptotics; nonlinear shrinkage; rotation equivariance;
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ECM-2017-10-08 (Econometrics)
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