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 ...

Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Gordon Scott has been an active investor and ...

The COV= option must be specified to compute an approximate covariance matrix for the parameter estimates under asymptotic theory for least-squares, maximum-likelihood, or Bayesian estimation, with or ...

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

In this paper we propose a new regression interpretation of the Cholesky factor of the covariance matrix, as opposed to the well-known regression interpretation of the Cholesky factor of the inverse ...

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 ...

The sandwich estimator, also known as robust covariance matrix estimator, heteroscedasticity-consistent covariance matrix estimate, or empirical covariance matrix estimator, has achieved increasing ...

The estimated covariance matrix of the parameter estimates is computed as the inverse Hessian matrix, and for unconstrained problems it should be positive definite. If the final parameter estimates ...