Cross-firm momentum effects via shared analyst coverage are well-documented in de-veloped markets, but their robustness remains unclear in emerging markets, where information diffusion is asymmetric and analyst coverage is highly concentrated. Our work revisits this effect in an environment of extreme informational frictions — the Chinese market. We reconstruct the information transmission channel within the an-alyst coverage network by introducing a novel weighting scheme based on strength centrality (SC). This measure identiffes inffuential leader firms that command dis-proportionate attention from both analysts and the market. Our results demonstrate that SC-weighted connected-firm returns robustly predict cross-sectional stock returns, yielding significant and persistent profits even under a rigorous stock filter. This per-formance cannot be subsumed by strategies based on alternative weighting schemes or by explanations such as intra-industry cross-firm momentum and information discreteness. Further analysis reveals that the superiority of the SC-based approach stems from its ability to effectively identify firms with stronger cross-period fundamental linkages. In addition, high-SC stocks are characterized by higher investor attention, more efficient information processing, lower arbitrage costs, and greater internationa exposures. With this evidence, we further confirm a directional spillover: cross-firm momentum effects flow exclusively from these high-SC leaders to low-SC laggards, and there is no reverse spillover. Our findings suggest that cross-firm momentum may be systematically underestimated in many international markets due to methodological limitations rather than economic irrelevance. The SC-based framework therefore of-fers a portable tool for global investors and researchers operating in environments with asymmetric information.

We construct a novel risk-based similarity peer network by applying machine learning techniques to extract a comprehensive set of disclosed risk factors from firms' annual reports. We find that a firm's future returns can be significantly predicted by the past returns of its risk-similar peers, even after excluding firms within the same industry. A long-short portfolio, formed based on the returns of these risk-similar peers, generates an alpha of 84 basis points per month. This return predictability is particularly pronounced for negative-return stocks and those with limited investor attention, suggesting that the effect is driven by slow information diffusion across firms with similar risk exposures. Our findings highlight that the risk factors disclosed in 10-K filings contain valuable information that is often overlooked by investors.

In this paper, we introduce the first dataset that records the news co-mention relationships in the Chinese A-share market. In total, we collected 1,138,247 pieces of news articles that at least mentioned one listed firm in the A market from major Chinese media and financial websites from September 1999 to December 2022. The development of this dataset could enable data scientists and financial economists to investigate the network of stocks through news co-mention in the Chinese stock market. The dataset could also help to construct novel portfolio strategies like the cross-firm momentum strategy with news-implied links as in Ge et al. (2023).

This paper decomposes news-implied linkages into two types: leader-follower links (LF) and peer links (PE), based on people's reading and information-processing habits. We explore how the structure of information impacts processing costs and subsequently leads to market outcomes by examining momentum spillover effects via these distinct linkage types. Our findings indicate that the information structure of leader-follower links is more readily comprehensible to investors than peer linkages. We provide empirical evidence of this by demonstrating faster attention spillover from leader to follower than among peer firms, using Baidu search data. Furthermore, we document that due to the lower information processing cost, information transmits through the leader-follower linkages more quickly, leading to a weaker momentum spillover effect compared to the more complex and less easily perceivable peer links.