 Firm connection and equity return predictability – Graph-based machine learning methodsMian Wu, Wenli Huang, Xiaoquan Liu and Qingxin Meng The British Accounting Review, 2026, vol. 58, issue 2 Abstract: We develop a unified measure of firm linkage from popular linkage indicators in the literature via graph-based machine learning methods and investigate its asset pricing implication. Using all A-shares listed in the Chinese stock market from 2003 to 2022, we reveal a widespread momentum spillover in the cross section of stock returns based on our linkage measure. In particular, a long-short trading strategy for portfolios sorted by our measure generates significant risk-adjusted returns of 0.83% on a monthly basis. We show that our measure contains incremental information on firm fundamental connections relative to well-documented alternative measures, and its predictive ability can be rationalized by the investor inattention hypothesis. Our study contributes to the literature which explores economic linkages that generate lead-lag predictability and sheds new light on the interconnected nature of companies in an economy via advanced machine learning techniques. Keywords: Cross-firm return predictability; Machine learning; Momentum spillover; Firm network; Economic linkage (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:bracre:v:58:y:2026:i:2:s0890838924002002 DOI: 10.1016/j.bar.2024.101436 Access Statistics for this article The British Accounting Review is currently edited by Nathan Lael Joseph and Alan Lowe More articles in The British Accounting Review from Elsevier |
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