Can network structure predict cross-sectional stock returns? Evidence from co-attention networks in China
Xi Chen,
Wuyue Shangguan,
Yanchu Liu and
Shichao Wang
Finance Research Letters, 2021, vol. 38, issue C
Abstract:
This study represents the Chinese stock market as co-attention networks based on investors’ correlated searches of stocks in a web portal. We investigate the predictability of network structures on cross-sectional stock returns. Our results show that network structures play different roles in predicting stock returns when peer stocks behave differently. Specifically, an increase in network centrality and network closure among the “historical winner peers” of a focal stock is associated with higher abnormal returns, while such an increase among the “historical loser peers” predicts lower abnormal returns.
Keywords: Co-attention; Network structure; Network centrality; Network closure; Stock returns (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1544612319309808
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:38:y:2021:i:c:s1544612319309808
DOI: 10.1016/j.frl.2019.101422
Access Statistics for this article
Finance Research Letters is currently edited by R. Gençay
More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().