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 …

estimation of static factor models and factor augmented autoregressions using a set of 190 quarterly observations of 144 US …

-sectional dependence, which may arise from local network structures. Model selection, filtering of the dynamic factors, and estimation are …

-to-implement estimator of the common primitive shocks. We illustrate our testing and estimation procedures with applications to panels of …

simulation, thus enabling straightforward parameter estimation by standard maximum likelihood. We use the new mixed …

orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … proposed estimation approach pairs intuitiveappeal with computational efficiency. We evaluate various alternative estimation …