Title: Industry classifications and identification of important industry groups

Authors: Serkan Alkan

Addresses: Department of Finance and Banking, Tarsus University, Mersin, Turkey

Abstract: Researchers in finance, managers, and people interested in the stock market observe that stock prices generally move together. Financial analysts and academic researchers use different techniques to construct homogeneous stock groups as in the Global Industry Classification System (GICS). This study analyses how homogeneity at each aggregation level of the GICS scheme changes over time. It identifies industries with more homogeneous structure than others in terms of stock returns by applying internal cluster validation statistics. A technique derived from complex network theory is proposed to illustrate how to construct a network whose nodes are financial industry groups to examine the evolution of the relationships among these groups over time. The findings indicate that stock networks undergo regular structural shifts in their interaction structure, and such structural changes become more intense during financial crises. Certain industry groups dominate the market at certain times and undergo significant changes during different market regimes.

Keywords: industry classification; mutual information; complex networks; comovement; sector strength.

DOI: 10.1504/IJBIDM.2023.133225

International Journal of Business Intelligence and Data Mining, 2023 Vol.23 No.3, pp.303 - 324

Received: 04 Mar 2022
Accepted: 28 Feb 2023
Published online: 01 Sep 2023 *

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