Portfolio optimization typically requires an estimate of a covariance matrix of asset returns. There are many approaches for constructing such a covariance matrix, some using the sample covariance matrix as a starting point. This package provides implementations for two such methods: random matrix theory and shrinkage estimation. Each method attempts to clean or remove noise related to the sampling process from the sample covariance matrix.
|Author||Brian Lee Yung Rowe|
|Maintainer||Brian Lee Yung Rowe <firstname.lastname@example.org>|
|Package repository||View on GitHub|
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