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Cited by 1,310

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

Local Does as Local Is: Information Content of the Geography of Individual Investors' Common Stock Investments

IVKOVIĆ, ZORAN, WEISBENNER, SCOTT·2005·The Journal of Finance
DOI 10.1111/j.1540-6261.2005.00730.x
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Abstract

Using data on the investments a large number of individual investors made through a discount broker from 1991 to 1996, we find that households exhibit a strong preference for local investments. We test whether this locality bias stems from information or from simple familiarity. The average household generates an additional annualized return of 3.2% from its local holdings relative to its nonlocal holdings, suggesting that local investors can exploit local knowledge. Excess returns to investing locally are even larger among stocks not in the S&P 500 index (firms for which information asymmetries between local and nonlocal investors may be largest).

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Metadata

Authors
IVKOVIĆ, Z., & WEISBENNER, S.
Venue
The Journal of Finance
Publisher
Wiley
Published
2005-02
Volume
60
Issue
1
Pages
267-306
ISSN
  • 0022-1082 (ISSN-L)
  • 1540-6261
DOI
10.1111/j.1540-6261.2005.00730.x
OpenAlex
W3023582314
Cited by
1,310
References
27
FWCI
54.52
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Local Does as Local Is: Information Content of the Geography of Individual Investors' Common Stock Investments. https://app.cochat.ai/papers/10.1111/j.1540-6261.2005.00730.x
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IVKOVIĆ, Z., & WEISBENNER, S. (2005). Local Does as Local Is: Information Content of the Geography of Individual Investors' Common Stock Investments. The Journal of Finance. https://doi.org/10.1111/j.1540-6261.2005.00730.x

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.