Date of Award

6-1-2012

Document Type

Open Access Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Duc A. Tran

Second Advisor

Timothy Killingback

Third Advisor

Bala Sundaram

Abstract

Over the past decade, a great deal of research has been done on the dynamics of complex networks, particularly in the realm of social networks. As online social networks (Facebook, LinkedIn, etc.) have exploded in popularity, a deluge of data has become available to researchers, providing detailed histories of online social interaction. A growing number of small-scale online networks aimed at certain niche groups of users have also sprouted up, providing a richer context for the study of social network dynamics. One such network is Currensee, which provides a social platform for investors in the foreign exchange market. Through the dataset provided by Currensee, we are able to study the investment activity of investors who participate in a social network focused on their investment decisions. Furthermore, we can examine the aggregate investment activity of this network in relation to general financial market volatility. After discovering an interesting relationship between between market volatility and a certain measure of behavioral finance (“herding”), we lastly aim to simulate this type of investment network, allowing us to control for network topology, and thus examine the impact of network topology on the aggregate behavior of the investing agents composing said network.

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