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 ...

A new formula for converting a covariance matrix estimated in local currencies into a covariance matrix expressed in a common currency is proposed. This process uses simple matrix multiplications. We ...

Here again, RMT provides powerful tools to describe the time evolution of the full covariance matrix. 3 As I discussed in my previous column, stochastic volatility models have made significant ...

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 ...

We model a covariance matrix in terms of its corresponding standard deviations and correlation matrix. We discuss two general modeling situations where this approach is useful: shrinkage estimation of ...

The distribution of the largest latent root of the covariance matrix calculated from a sample from the normal normalitive multivariate population with population covariance matrix σ2 I are presented ...

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 ...