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The Local Bias of Individual Investors

Authors: Ning Zhu;

The Local Bias of Individual Investors

Abstract

This study investigates individual investors’ bias towards nearby companies. Using data from a large U.S. discount brokerage, we find that individual investors tend to invest in companies closer to them relative to the market portfolio. Unlike Coval and Moskowitz’s (1999) findings on institutional investors, however, we find that advantageous information cannot explain individual investors’ local bias. Accounting numbers and information asymmetry matter less to individual investors’ local bias than to that of institutional investors. Instead, we hypothesize that individuals’ non-fundamentally based familiarity with local companies and ready reaction to local information are more plausible explanations. Consistent with this hypothesis, we find that individual investors are more likely to invest in remote companies that spend heavily on advertising. Evidence from investors’ reactions to earnings announcements also confirms the hypothesis: local investors do not change their portfolios so as to take advantage of potentially advantageous information before earnings announcements. After earnings announcements, local investors change their portfolios more than remote investors in the direction opposite to the same earnings surprises.

Keywords

Local Bias, Individual Behavior, Asset Pricing, Asymmetric Information, Overreaction, Familiarity

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
104
Top 1%
Top 1%
Top 10%
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