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Count Models of Social Networks in Finance

46 Pages Posted: 8 Jan 2014 Last revised: 22 Jul 2015

Harrison G. Hong

Columbia University, Graduate School of Arts and Sciences, Department of Economics; National Bureau of Economic Research (NBER)

Jiangmin Xu

Peking University - Department of Finance

Multiple version iconThere are 2 versions of this paper

Date Written: December 28, 2014

Abstract

Social networks are thought to be important for the investment and performance of mutual fund managers. We propose a measure of whether a manager is part of a network using only data on the distribution of the number of stocks headquartered in a given city that are held by managers. For some cities, the count distribution is roughly Poisson. However, for a significant fraction of cities, the count distribution is highly overdispersed Poisson --- where most managers have a couple of picks but a few managers have many picks. We show that the degree of overdispersion is a theoretically well-motivated measure of network influence and that managers with concentrated stock picks in a city are likely to be part of a network in that city. These managers indeed significantly outperform other managers by around 1.6% per annum.

Keywords: Social Networks, Poisson Regressions, Investor Behavior

JEL Classification: G1, G2, G3

Suggested Citation

Hong, Harrison G. and Xu, Jiangmin, Count Models of Social Networks in Finance (December 28, 2014). Available at SSRN: https://ssrn.com/abstract=2375461 or http://dx.doi.org/10.2139/ssrn.2375461

Harrison G. Hong (Contact Author)

Columbia University, Graduate School of Arts and Sciences, Department of Economics ( email )

420 W. 118th Street
New York, NY 10027
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Jiangmin Xu

Peking University - Department of Finance ( email )

5 Yiheyuan Road
Beijing 100871
China

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