Measuring the effects of geographical distance on stock market correlation

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Recent studies suggest that the correlation of stock returns increases with decreasing geographical distance. However, there is some debate on the appropriate methodology for measuring the effects of distance on correlation. We modify a regression approach suggested in the literature and complement it with an approach from spatial statistics, the mark correlation function. For the stocks contained in the S&P 500 that we examine, both approaches lead to similar results. Contrary to previous studies we find that beyond 50 miles geographical proximity is irrelevant for stock return correlations. For distances below 50 miles, we can show that the magnitude of local correlations varies with investor sentiment.

Several studies have documented that investment decisions are affected by geographical location within a country. Both institutional investors (e.g. Coval and Moskowitz, 2001) as well as retail investors (e.g. Grinblatt and Keloharju, 2001; Huberman, 2001; Ivkovic and Weisbenner, 2005) allocate a disproportionately large fraction of their portfolios to firms that are close to their offices or homes. Possible reasons for such investment patterns are informational advantages and behavioral preferences for familiarity.1 The latter can lead to locally correlated trading through the following channel: local information or events – be they value-relevant or not – lead to correlated trading activity of local investors; as investors focus on local stocks, trading patterns in nearby-stocks will be correlated, too. Pirinsky and Wang (2006) and Barker and Loughran (2007) test an implication of this conjecture and conclude that the correlation of stock returns increases with decreasing distance. Another possible explanation for locally correlated stock returns is locally correlated fundamentals, but Pirinsky and Wang (2006) fail to find support for this second explanation. Download free Measuring the effects of geographical distance on stock market correlation.pdf here

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