A flexible class of prior distributions is proposed, for the covariance matrix of a multivariate normal distribution, yielding much more general hierarchical and empirical Bayes smoothing and ...

Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation This paper proposes a novel shrinkage estimator for high-dimensional covariance matrices by extending the Oracle ...

This short paper demonstrates how a covariance matrix estimated using log returns of multiple assets in their respective base currencies can be converted directly into a covariance matrix in a single ...

The Annals of Statistics, Vol. 30, No. 4 (Aug., 2002), pp. 1081-1102 (22 pages) This paper analyzes whether standard covariance matrix tests work when dimensionality is large, and in particular larger ...

Graphical models provide a robust framework for representing the conditional independence structure between variables through networks, enabling nuanced insight into complex high-dimensional data.

Covariance is a statistical measure of how two assets move in relation to each other. It provides diversification and reduces the overall volatility of a portfolio. A positive covariance indicates ...