TitleUnderstanding financial networks through minority game
NameD'Souza, Savio Jude (author), Marsic, Ivan (chair), RABINER, LAWRENCE (internal member), Wilder, Joseph (internal member), Rutgers University, Graduate School - New Brunswick,
SubjectElectrical and Computer Engineering,
Stock exchanges--Social aspects
DescriptionThe recent financial crisis has highlighted the fact that financial systems are complex in nature and understanding financial systems is not a trivial task. One of the major factors that contribute to the complexity of financial systems is the presence of human traders in these systems. Also, the interaction between these human traders leads to traders getting influenced by other trader’ decisions and thus adding another layer of complexity. It has been observed that, social interactions among traders form a social network that influences economic decisions made by these traders. This has lead to a study of a new branch of economics namely “social economics” which takes into consideration the fact that traders are influenced by their social circle. “Social economics” is gaining popularity because the study of psychological aspects of human behavior is able to enhance the modeling of economic models especially the allocation of resources. W.B. Arthur introduced the El Farol Bar Problem in 1994, which shows how agents with bounded rationality and no interaction can show emergent behavior. The Minority game is a variant of the El Farol Bar Problem and it basically shows how agents collectively behave in an ideal situation while competing, by means of adaptation, for a scarce resource even without interacting with each other. In order to extract more characteristics of financial markets from the Minority Game, we modify it by introducing communication among the agents, thereby letting them get influenced by each other’s decisions. We aim to observer herding phenomena as agents are likely to take actions similar to that of their neighbors. Financial markets are quite dynamic in nature and the interacting traders form a network whose topology dynamically evolves. We study the effect on the network topology due to dynamic updates of the link weights of a financial network. We start with two initial network topologies namely a torus network and a random network. We also observe herding phenomenon among the agents. The degree distribution of the nodes of this financial network is fat-tailed, which is characteristic of a network that is robust against random fluctuations.
NoteIncludes bibliographical references
Noteby Savio Jude D'Souza
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.