Covariance Averaging for Improved Estimation and Portfolio Allocation
Quantf Research Working Paper Series No. WP11/2014
30 Pages Posted: 15 Jul 2013 Last revised: 2 Jun 2014
Date Written: June 1, 2014
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.
Keywords: Averaging, Covariance Estimation, Financial Returns, Multivariate Time Series, Portfolio Allocation, Risk Management, Rolling Window
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