Covariance averaging for improved estimation and portfolio allocation
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We propose a new method for estimating the covariance matrix of a multivariate time series of financial returns. The method is based on estimating sample covariances from overlapping windows of observations which are then appropriately weighted to obtain the final covariance estimate. We extend the idea of (model) covariance averaging offered in the covariance shrinkage approach by means of greater ease of use, flexibility and robustness in averaging information over different data segments. The suggested approach does not suffer from the curse of dimensionality and can be used without problems of either approximation or any demand for numerical optimization.
KeywordsAveraging Covariance estimation Portfolio allocation Rolling window
JEL ClassificationC32 C58 G11
The authors are very grateful for helpful comments from the editor and an anonymous referee. Any remaining errors are our responsibility.
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