Asset Pricing in Large Information Networks

43 Pages Posted: 5 Mar 2009 Last revised: 29 Jun 2012

See all articles by Han N. Ozsoylev

Han N. Ozsoylev

Ozyegin University

Johan Walden

University of California, Berkeley - Finance Group

Date Written: March 3, 2009


We study asset pricing in economies with large information networks. We derive closed form expressions for price, volatility, profitability and several other key variables, as a function of the topological structure of the network. We focus on networks that are sparse and have power law degree distributions, in line with empirical studies of large scale human networks. Our analysis allows us to rank information networks along several dimensions and to derive several novel results. For example, price volatility is a non-monotone function of network connectedness, as is average expected profit. Moreover, the profit distribution among investors is intimately linked to the properties of the information network. We also examine which networks are stable, in the sense that no agent has an incentive to change the network structure. We show that if agents are ex ante identical, then strong conditions are needed to allow for non-degenerate network structures, including power-law distributed networks. If, on the other hand, agents face different costs of forming links, which we interpret broadly as differences in social skills, then power-law distributed networks arise quite naturally.

Keywords: Information networks, noisy rational expectations equilibrium, power law

JEL Classification: D8, G12, G14

Suggested Citation

Ozsoylev, Han N. and Walden, Johan, Asset Pricing in Large Information Networks (March 3, 2009). Available at SSRN: or

Han N. Ozsoylev (Contact Author)

Ozyegin University ( email )

Kusbakisi Cd. No: 2
Altunizade, Uskudar
Istanbul, 34662

Johan Walden

University of California, Berkeley - Finance Group ( email )

545 Student Services Building, #1900
2220 Piedmont Avenue
Berkeley, CA 94720
United States
(510) 643-0547 (Phone)


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