Asset Selection via Correlation Blockmodel Clustering

33 Pages Posted: 29 Mar 2021

See all articles by Wenpin Tang

Wenpin Tang

Columbia University - Department of Industrial Engineering and Operations Research

Xiao Xu

Columbia University - Department of Industrial Engineering and Operations Research (IEOR)

Xun Yu Zhou

Columbia University - Department of Industrial Engineering and Operations Research (IEOR)

Date Written: March 26, 2021

Abstract

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

Tang, Wenpin and Xu, Xiao and Zhou, Xunyu, Asset Selection via Correlation Blockmodel Clustering (March 26, 2021). Available at SSRN: https://ssrn.com/abstract=3813247 or http://dx.doi.org/10.2139/ssrn.3813247

Wenpin Tang (Contact Author)

Columbia University - Department of Industrial Engineering and Operations Research ( email )

500 W. 120th Street #315
New York, NY 10027
United States

Xiao Xu

Columbia University - Department of Industrial Engineering and Operations Research (IEOR) ( email )

331 S.W. Mudd Building
500 West 120th Street
New York, NY 10027
United States

Xunyu Zhou

Columbia University - Department of Industrial Engineering and Operations Research (IEOR) ( email )

331 S.W. Mudd Building
500 West 120th Street
New York, NY 10027
United States

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