Abstract

http://ssrn.com/abstract=2375461
 


 



Count Models of Social Networks in Finance


Harrison G. Hong


Princeton University - Department of Economics; National Bureau of Economic Research (NBER)

Jiangmin Xu


Department of Finance, Guanghua School of Management, Peking University

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.

Number of Pages in PDF File: 46

Keywords: Social Networks, Poisson Regressions, Investor Behavior

JEL Classification: G1, G2, G3


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Date posted: January 8, 2014 ; Last revised: December 28, 2014

Suggested Citation

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

Contact Information

Harrison G. Hong (Contact Author)
Princeton University - Department of Economics ( email )
Princeton, NJ 08544-1021
United States
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Jiangmin Xu
Department of Finance, Guanghua School of Management, Peking University ( email )
5 Yiheyuan Road
Beijing 100871
China
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