Internal Evolution for Agent Cognition - Agent-Based Modelling of an Artificial Stock Market

dc.contributor.authorHassanzadeh, Morteza
dc.contributor.departmentChalmers tekniska högskola / Institutionen för energi och miljösv
dc.contributor.departmentChalmers University of Technology / Department of Energy and Environmenten
dc.date.accessioned2019-07-03T12:43:02Z
dc.date.available2019-07-03T12:43:02Z
dc.date.issued2011
dc.description.abstractAgent-Based Modeling (ABM) is a powerful simulation technique with applications in several fields, in particular social sciences. Artificial Stock Market (ASM), introduced by a group of researchers at Santa Fe Institute (SFI) in the mid 90’s, is one of the pioneering works in which the application of agent-based modeling is examined being used to model a stock market and to study economic behavior. A number of heterogeneous agents form a market in which they buy and sell shares of a single introduced asset and they make their decision upon their expectations of the market which is determined from their aggregate expectations, while they improve their predictions based on the response they get from the market. The computer simulation of the model gives a market dynamics which has similarities with real market data. The internal evolution of agents has a direct effect on the market dynamics, and the learning speed of agents controls the overall qualitative characteristics of the market. With emphasis on the role of evolution of agents in this artificial stock market, an implementation of the model has been done and a few issues have been studied.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/148480
dc.language.isoeng
dc.setspec.uppsokLifeEarthScience
dc.subjectAnnan fysik
dc.subjectOther Physics Topics
dc.titleInternal Evolution for Agent Cognition - Agent-Based Modelling of an Artificial Stock Market
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
dc.type.uppsokH
local.programmeComplex adaptive systems (MPCAS), MSc
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