Before revision:  Our paper develops a frameworkfor estimating a high-dimensional precision matrix which combines the benefits of exploring the factor structure of the stock returns and the sparsity of the precision matrix of the factor-adjusted returns. The proposed algorithm is called Factor Graphical Lasso (FGL) .
After revision:  We address this limitation and develop a framework, Factor Graphical Lasso (FGL) .