Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.537227
Title: Using agent-based simulation models in the analysis of market crashes
Author: Kabanov, Alexander
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2011
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Abstract:
In this thesis we propose an agent-based model for a financial market with a single asset. The agents are motivated to trade via their personal beliefs about the future direction of the asset price moves. Additionally, the trades are restricted by the resources available to agents. The constructed model is used to attempt to gain some insight into the origin of large price moves in the market (“market crashes”). Monte Carlo simulations are used to study model behaviour under varying initial conditions. The model is found to be generally capable of reproducing the stylised facts of real financial markets. The ubiquity of relatively high incidence of large price moves in the results of model simulation, together with results from similar models by other authors allow us to conjecture that such moves are inherent in a market model based on a heterogenous population of intelligent agents. Finally, several directions for model improvement are identified.
Supervisor: Davis, Mark Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.537227  DOI: Not available
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