Abstract

http://ssrn.com/abstract=2375461
 


 



Count Models of Social Networks in Finance


Harrison G. Hong


Columbia University, Graduate School of Arts and Sciences, 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: July 22, 2015

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)
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
Department of Finance, Guanghua School of Management, Peking University ( email )
5 Yiheyuan Road
Beijing 100871
China
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