Before revision: We present a set of analyses aiming at quantifying the amount of information filtered by different hierarchical clustering methods on correlations between stock returns . In particular we apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree (DBHT), and we compare it with other methods including the Linkage and k-medoids.
After revision: We present a set of analyses aiming at quantifying the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing it with the underlying industrial activity structure. Specifically, we apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree (DBHT), and we compare it with other methods including the Linkage and k-medoids.