Statistical Performance Measures to Evaluate Covariance Matrix Estimates
Asymmetric loss function
Distance measure defined in Eq. (3.1) of Li et al. (2016)
Discrepancy measure defined in Eq. (4.2) of Li et al. (2016)
Frobenius distance
Euclidean distance
Eigenvalue loss function
Loss function defined in Eq. (4.6) of Engle et al. (2016)
Mean Absolute Error
Mean Square Error
Statistical performance measures to evaluate conditional covariance ma...
Stein loss function.
Statistical performance measures used in the econometric literature to evaluate conditional covariance/correlation matrix estimates (MSE, MAE, Euclidean distance, Frobenius distance, Stein distance, asymmetric loss function, eigenvalue loss function and the loss function defined in Eq. (4.6) of Engle et al. (2016) <doi:10.2139/ssrn.2814555>). Additionally, compute Eq. (3.1) and (4.2) of Li et al. (2016) <doi:10.1080/07350015.2015.1092975> to compare the factor loading matrix. The statistical performance measures implemented have been previously used in, for instance, Laurent et al. (2012) <doi:10.1002/jae.1248>, Amendola et al. (2015) <doi:10.1002/for.2322> and Becker et al. (2015) <doi:10.1016/j.ijforecast.2013.11.007>.