The Linear Relationship Model with LASSO for Studying Stock Networks

Muzi Chen, Hongjiong Tian, Boyao Wu, Tianhai Tian

Research output: Contribution to journalArticleResearchpeer-review


The correlation-based network is a powerful tool to reveal the influential mechanisms and relations in stock markets. However, current methods for developing network models are dominantly based on the pairwise relationship of positive correlations. This work proposes a new approach for developing stock relationship networks by using the linear relationship model with LASSO to explore negative correlations under a systemic framework. The developed model not only preserves positive links with statistical significance but also includes link directions and negative correlations. We also introduce blends cliques with the balance theory to investigate the consistency properties of the developed networks. The ASX 200 stock data with 194 stocks are applied to evaluate the effectiveness of our proposed method. Results suggest that the developed networks not only are highly consistent with the correlation coefficient in terms of positive or negative correlations but also provide influence directions in stock markets.

Original languageEnglish
Article number808
Number of pages13
Issue number6
Publication statusPublished - Jun 2022


  • linear relationship model
  • negative correlation
  • stock relationship network

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