Factor_Model

The factor model problem focuses on the decomposition of a covariance matrix $\Sigma$ to low-rank and diagnonal positive semidefinite matrices. In practice, $\Sigma$ is often not available, and only its empirical counterpart, $\hat{\Sigma}$, is available. To robustify to this approximation error, a common practice is to consider a family of covariance matrices in the vicinity of $\Sigma$.

The linked repository contains MATLAB files corresponding to the numerical results of the paper 'A Saddle Point Algorithm for Robust Data-Driven Factor Model Problems'.