Firm connection and equity return predictability – Evidence from China

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review


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 languageEnglish
Title of host publication2023 XJTLU AI and Big Data in Accounting and Finance Research Conference and the BAR special issue
Publication statusIn preparation - 2023


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