Bayesian investor. We develop a constrained parameter learning approach for sequential estimation allowing for belief revisions …

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 …We investigate covariance matrix estimation in vast-dimensional spaces of 1,500 up to 2,000 stocks using fundamental …