DocumentCode
2917605
Title
A mixed-game agent-based model for simulating financial contagion
Author
Caporale, Guglielmo Maria ; Serguieva, Antoaneta ; Wu, Hao
Author_Institution
Dept. of Econ. & Finance, Brunel Univ., London
fYear
2008
fDate
1-6 June 2008
Firstpage
3421
Lastpage
3426
Abstract
Over the past two decades, financial market crises with similar features have occurred in different regions of the world. Unstable cross-market linkages during financial crises are referred to as financial contagion. We simulate the transmission of financial crises in the context of a model of market participants adopting various strategies; this allows testing for financial contagion under alternative scenarios. Using a minority game approach, we develop an agent-based multinational model and investigate the reasons for contagion. Although contagion has been extensively investigated in the financial literature, it has not been studied yet through computational intelligence techniques. Our simulations shed light on parameter values and characteristics which can be exploited to detect contagion at an earlier stage, hence recognising financial crises with the potential to destabilise cross-market linkages. In the real world, such information would be extremely valuable to develop appropriate risk management strategies.
Keywords
financial data processing; financial management; game theory; multi-agent systems; agent-based multinational model; computational intelligence techniques; cross-market linkages; financial contagion; financial market crises; minority game approach; mixed-game agent-based model; risk management strategies; Context modeling; Couplings; Economic forecasting; Electric shock; Fluctuations; Game theory; Parameter estimation; Position measurement; Predictive models; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-1822-0
Electronic_ISBN
978-1-4244-1823-7
Type
conf
DOI
10.1109/CEC.2008.4631260
Filename
4631260
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