Asset Selection via Correlation Blockmodel Clustering
46 Pages Posted: 29 Mar 2021 Last revised: 13 Aug 2021
Date Written: March 26, 2021
We aim to cluster financial assets in order to identify a small set of stocks to approximate the level of diversification of the whole universe of stocks. We develop a data-driven approach to clustering based on a correlation blockmodel in which assets in the same cluster have the same correlations with all other assets. We devise an algorithm to detect the clusters, with a theoretical analysis and a practical guidance. Finally, we conduct an empirical analysis to attest the performance of the algorithm.
Keywords: Asset selection, cluster analysis
JEL Classification: G11
Suggested Citation: Suggested Citation