Does a firm’s geographic feature matter for stock returns? Evidence from the Chinese A-share market

Changyang Liu, Tian Yue and Yugang Yin

Applied Economics, 2023, vol. 55, issue 21, 2455-2476

Abstract: This study reveals a new stock return predictability that relates to firms’ geographic features in the Chinese A-share market. Using a text-based measure of the degree of localness to capture the economic ties between firms and their provinces, we find that low-localized firms are slow to incorporate local information into stock prices. Specifically, there is a significant lead-lag effect in stock returns between high- and low-localized firms in the same region, and a portfolio that exploits this pattern can generate a monthly alpha of about 1%. This effect cannot be explained by geographic or industry return momentum, investors’ inattention, and limits to arbitrage. We find that this return predictability is mainly driven by investors’ limited information-processing capacity, and the evidence of predictability is stronger among low-localized firms with highly complicated business structures.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2022.2103080 (text/html)
Access to full text is restricted to subscribers.

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:taf:applec:v:55:y:2023:i:21:p:2455-2476

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

DOI: 10.1080/00036846.2022.2103080

Access Statistics for this article

Applied Economics is currently edited by Anita Phillips

More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().