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 ...

This paper proposes a novel shrinkage estimator for high-dimensional covariance matrices by extending the Oracle Approximating Shrinkage (OAS) of Chen et al. (2009) to target the diagonal elements of ...

This article proposes a data-driven method to identify parsimony in the covariance matrix of longitudinal data and to exploit any such parsimony to produce a statistically efficient estimator of the ...

While risk factor disclosures in 10-K filings have been criticized by practitioners as generic and boilerplate, recent studies indicate that these risk reports can be informative. This study ...

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