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.
|Advisor:||Tran, Duc A.|
|Commitee:||Killingback, Timothy, Simovici, Dan, Sundaram, Bala|
|School:||University of Massachusetts Boston|
|School Location:||United States -- Massachusetts|
|Source:||MAI 50/06M, Masters Abstracts International|
|Subjects:||Economics, Sociology, Computer science|
|Keywords:||Herding, Market simulation, Social network analysis|
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