Does a firm's geographic feature matter for stock returns? Evidence from the Chinese A-share market
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 incor...
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Veröffentlicht in: | Applied economics 2023-05, Vol.55 (21), p.2455-2476 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 0003-6846 1466-4283 |
DOI: | 10.1080/00036846.2022.2103080 |