Local information demand and the cross-section of stock returns

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Authors: Gang Chu, John W. Goodell, Xiao Li
Cited by: 1
References: 53

Abstract

Using Internet search data, we examine how geographic proximity shapes individual investors’ information acquisition behavior. Focusing on the Chinese stock market, we document a pronounced local bias in information demand: individual investors search more intensively for stocks of firms headquartered in their own province than for non-local firms. Consistent with a local information advantage, we show that local investors receive more private information about nearby firms than non-local investors, giving rise to local bias in investor information demand. We then study the asset-pricing implications of this bias by examining the cross-sectional relation between abnormal local bias in information demand and expected returns. Stocks with high abnormal local bias earn significantly higher future returns than those with low abnormal local bias, even after controlling for well-known risk factors. This return predictability is stronger among stocks subject to greater information frictions. Finally, we show that abnormal local bias in information demand primarily captures the arrival of non-fundamental news, as its return predictability reverses over longer horizons. Overall, our findings highlight the role of geography in shaping investor information demand and its implications for asset prices.

Fields of Study & Subjects

Financial Markets and Investment Strategies Auditing Earnings Management Governance Complex Systems and Time Series Analysis

Publication details

Journal / source
Journal of Management Science and Engineering
Publisher
Elsevier BV
Volume
11
Issue
1
Pages
169–188
Publication date
23 January 2026
Language
EN