This paper proposes a regularisation method for the estimation of large covariance matrices that uses insights from the … of estimating the theoretical constant arising in the rate of convergence of existing thresholding estimators, and hence … it is easy to implement and does not require cross-validation. The MT estimator of the sample correlation matrix is shown …

modelling that enables stochastic structural change in model parameters and on model estimation by Bayesian or non …-parametric kernel methods. In the context of the estimation of covariance matrices of large dimensional panels, such data requires … applicable in econometric analysis beyond estimation of large covariance matrices. We discuss the utility of the robust …

Existing shrinkage techniques struggle to model the covariance matrix of asset returns in the presence of multiple …-asset classes. Therefore, we introduce a Blockbuster shrinkage estimator that clusters the covariance matrix accordingly. Besides … the definition and derivation of a new asymptotically optimal linear shrinkage estimator we propose an adaptive …

competing estimators. An out-of-sample GMV portfolio allocation problem is studied. A simple shrinkage technique is introduced …

Chen and Deo (2009a) proposed procedures based on restricted maximum likelihood (REML) for estimation and inference in … the context of predictive regression. Their method achieves bias reduction in both estimation and inference which assists …