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Modeling financial markets with heterogeneous interacting agents

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TitleInfo (displayLabel = Citation Title); (type = uniform)
Title
Modeling financial markets with heterogeneous interacting agents
Name (ID = NAME001); (type = personal)
NamePart (type = family)
Desai
NamePart (type = given)
Viral
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Viral Desai
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author
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Marsic
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Ivan
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Advisory Committee
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Ivan Marsic
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chair
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Silver
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Deborah
Affiliation
Advisory Committee
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Deborah Silver
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internal member
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Gajic
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Zoran
Affiliation
Advisory Committee
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Zoran Gajic
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internal member
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Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
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Graduate School - New Brunswick
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school
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Text
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theses
OriginInfo
DateCreated (qualifier = exact)
2007
DateOther (qualifier = exact); (type = degree)
2007
Language
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English
PhysicalDescription
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electronic
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application/pdf
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text/xml
Extent
ix, 79 pages
Abstract
Financial market has been extensively recognized as a complex system, where large number of heterogeneous agents contribute to price formation of asset. Interactions and adaptations of these agents form the core foundation of market operations and its resultant characteristic properties. These market agents are highly diverse in their perception of the world around them and in the way they respond to it. Various studies of statistical properties of financial markets and price fluctuations have revealed a rich set of typical characteristics knows as stylized facts. Agent-based models that can reproduce these stylized facts and explain the roots of complex dynamics of financial market have been subject of intense research in recent time. The Minority Game Model proposed by Challet and Zhang is one such model that presents a simplified paradigm of financial market. Another model proposed by Lux and Marchesi offers a different perspective to agent-based modeling, where parallels are drawn between the physical system with a large number of interacting units and financial markets. The Minority Game model succeeds to a certain extent in reproducing stylized facts and explaining behavioral foundation of it. However, in attempt to present a simplified picture of market scenario both these models make certain assumptions that dilute the heterogeneity aspect of the real market. In real world markets, agents are truly diverse in their thinking, strategy, action and analyzing ability. Due to these unrealistic assumptions, the model can be validated only with a very limited spectrum of parameters. Also, it's difficult to point out precisely which aspects of the game contribute to some of the stylized facts producible with the model. To improve on these issues, we have developed a model and a simulator based on modified minority game, which we are referring to as "adapted minority game." The main focus of our research is on improving the heterogeneity aspect of agents, their interactions, and bringing fundamental value of asset into the Minority Game model. Our model introduces fundamentalist agents into the minority game model and also allows agents to have different historical memory and time horizons. Furthermore, agents are free to switch from one trading strategy group to another to improve their chances of performing better. Reproducing the stylized facts still remains the benchmark for validating our model. Our adapted minority game succeeds to an extent in expanding the spectrum of parameters that can be used for modeling the market. Agents' interactions and adaptations have been tracked down to the basis of stylized facts. An interesting property of periodic volatility is successfully demonstrated with our model.
Note (type = degree)
M.S.
Note (type = bibliography)
Includes bibliographical references (p. 78-79).
Subject (ID = SUBJ1); (authority = RUETD)
Topic
Electrical and Computer Engineering
Subject (ID = SUBJ2); (authority = ETD-LCSH)
Topic
Finance--Mathematical models
Subject (ID = SUBJ3); (authority = ETD-LCSH)
Topic
Economics
Subject (ID = SUBJ4); (authority = ETD-LCSH)
Topic
Macroeconomics
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Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
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http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.15812
Identifier
ETD_517
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T38C9WQZ
Genre (authority = ExL-Esploro)
ETD graduate
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The author owns the copyright to this work.
Copyright
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Copyright protected
Availability
Status
Open
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Name
Viral Desai
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
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Permission or license
Detail
Non-exclusive ETD license
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Author Agreement License
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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