Abstract
We develop a unified measure of firm linkage from popular linkage indicators in the liter- ature 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 par- ticular, 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 incre- mental 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.
| Original language | English |
|---|---|
| Title of host publication | 2023 XJTLU AI and Big Data in Accounting and Finance Research Conference and the BAR special issue |
| Publication status | In preparation - 2023 |
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Dive into the research topics of 'Firm connection and equity return predictability – Evidence from China'. Together they form a unique fingerprint.Student theses
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Equity pricing in China: firm connections, style investment, and disagreement spillover
Wu, M. (Author), Meng, Q. (Supervisor), Liu, X. (Supervisor) & Huang, W. (Supervisor), 19 Jul 2026Student thesis: PhD Thesis
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