We investigate covariance matrix estimation in vast-dimensional spaces of 1,500 up to 2,000 stocks using fundamental … about estimation risk in FFMs in high dimensions. We investigate whether recent linear and non-linear shrinkage methods help … to reduce the estimation risk in the asset return covariance matrix. Our findings indicate that modest improvements are …

conditions: in particular it allows for parameter estimation uncertainty and for the copulas to be nested or non-nested. Monte …

period than our detailed education data panel, we propose a twostep estimation procedure. First, we consider a score …

exploit a maximum likelihood estimation on the Stiefel manifolds, which ensure that the identification constraint is satisfied … numerically, hence allowing a joint estimation of the static and time-varying parameters. Furthermore, the asymptotic properties …

interdependence structures across multiple sectors. The estimation procedure is based on a multistep least squares method which is …