Asset Selection via Correlation Blockmodel Clustering

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

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Year of publication:	2022
Authors:	Tang, Wenpin ; Xu, Xiao ; Zhou, Xun Yu
Publisher:	[S.l.] : SSRN
Subject:	Korrelation \| Correlation \| Regionales Cluster \| Regional cluster \| Portfolio-Management \| Portfolio selection \| Clusteranalyse \| Cluster analysis

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