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Financial Contagion: Evolutionary Optimisation of a Multinational Agent-Based Model

Author

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  • Guglielmo Maria Caporale
  • Antoaneta Serguieva
  • Hao Wu

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 a crisis are referred to as financial contagion. We simulate crisis transmission 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 the phenomenon has been extensively investigated in the financial literature, it has not been studied 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 in developing appropriate risk management strategies.

Suggested Citation

  • Guglielmo Maria Caporale & Antoaneta Serguieva & Hao Wu, 2008. "Financial Contagion: Evolutionary Optimisation of a Multinational Agent-Based Model," CESifo Working Paper Series 2444, CESifo.
    • Handle: RePEc:ces:ceswps:_2444
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    1. Graciela Kaminsky & Saul Lizondo & Carmen M. Reinhart, 1998. "Leading Indicators of Currency Crises," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 1-48, March.
    2. King, Mervyn A & Wadhwani, Sushil, 1990. "Transmission of Volatility between Stock Markets," The Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 5-33.
    3. LeBaron, Blake, 2000. "Agent-based computational finance: Suggested readings and early research," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 679-702, June.
    4. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, vol. 57(5), pages 2223-2261, October.
    5. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2001. "Evolving traders and the business school with genetic programming: A new architecture of the agent-based artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 363-393, March.
    6. repec:cdl:ucsbec:13-89 is not listed on IDEAS
    7. Lettau, Martin, 1997. "Explaining the facts with adaptive agents: The case of mutual fund flows," Journal of Economic Dynamics and Control, Elsevier, vol. 21(7), pages 1117-1147, June.
    8. Jean-Philippe Bouchaud & Rama Cont, 1998. "A Langevin approach to stock market fluctuations and crashes," Science & Finance (CFM) working paper archive 500027, Science & Finance, Capital Fund Management.
    9. Challet, Damien & Marsili, Matteo & Zhang, Yi-Cheng, 2001. "Stylized facts of financial markets and market crashes in Minority Games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 294(3), pages 514-524.
    10. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2006. "Estimation of a simple agent-based model of financial markets: An application to Australian stock and foreign exchange data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 38-42.
    11. W. Brian Arthur, 1994. "Inductive Reasoning, Bounded Rationality and the Bar Problem," Working Papers 94-03-014, Santa Fe Institute.
    12. Johnson, Neil F. & Lamper, David & Jefferies, Paul & Hart, Michael L. & Howison, Sam, 2001. "Application of multi-agent games to the prediction of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 222-227.
    13. Richard B. Olsen & Ulrich A. Müller & Michel M. Dacorogna & Olivier V. Pictet & Rakhal R. Davé & Dominique M. Guillaume, 1997. "From the bird's eye to the microscope: A survey of new stylized facts of the intra-daily foreign exchange markets (*)," Finance and Stochastics, Springer, vol. 1(2), pages 95-129.
    14. Cont, Rama & Bouchaud, Jean-Philipe, 2000. "Herd Behavior And Aggregate Fluctuations In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 4(2), pages 170-196, June.
    15. Caporale, Guglielmo Maria & Cipollini, Andrea & Spagnolo, Nicola, 2005. "Testing for contagion: a conditional correlation analysis," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 476-489, June.
    16. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    17. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    18. Chengling Gou, 2006. "The Simulation of Financial Markets by an Agent-Based Mix-Game Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(3), pages 1-6.
    19. Jeffrey A. Frankel and Kenneth A. Froot., 1986. "Explaining the Demand for Dollars: International Rates of Return and the Expectations of Chartists and Fundamentalists," Economics Working Papers 8603, University of California at Berkeley.
    20. LeRoy, Stephen F, 1989. "Efficient Capital Markets and Martingales," Journal of Economic Literature, American Economic Association, vol. 27(4), pages 1583-1621, December.
    21. Kalinowski, Thomas & Schulz, Hans-Jörg & Briese, Michael, 2000. "Cooperation in the Minority Game with local information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 277(3), pages 502-508.
    22. Chengling Gou, 2006. "The Simulation of Financial Markets by Agent-Based Mix-Game Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(3), pages 1-6.
    23. Derrick Reagle & Dominick Salvatore, 2000. "Forecasting Financial Crises in Emerging Market Economies," Open Economies Review, Springer, vol. 11(3), pages 247-259, July.
    24. Neil F. Johnson & David Lamper & Paul Jefferies & Michael L. Hart & Sam Howison, 2001. "Application of multi-agent games to the prediction of financial time-series," OFRC Working Papers Series 2001mf04, Oxford Financial Research Centre.
    25. Arthur, W Brian, 1994. "Inductive Reasoning and Bounded Rationality," American Economic Review, American Economic Association, vol. 84(2), pages 406-411, May.
    26. Challet, Damien & Marsili, Matteo & Zhang, Yi-Cheng, 2001. "Minority games and stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 228-233.
    27. N. F. Johnson & D. Lamper & P. Jefferies & M. L. Hart & S. Howison, 2001. "Application of multi-agent games to the prediction of financial time-series," Papers cond-mat/0105303, arXiv.org.
    28. Challet, D. & Zhang, Y.-C., 1997. "Emergence of cooperation and organization in an evolutionary game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 407-418.
    29. Chen, Fang & Gou, Chengling & Guo, Xiaoqian & Gao, Jieping, 2008. "Prediction of stock markets by the evolutionary mix-game model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3594-3604.
    30. Shimokawa, Tetsuya & Suzuki, Kyoko & Misawa, Tadanobu, 2007. "An agent-based approach to financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 207-225.
    31. Kaizoji, Taisei, 2001. "A model of international financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 279-293.
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    Cited by:

    1. Grinis, Inna, 2015. "Credit risk spillovers, systemic importance and vulnerability in financial networks," LSE Research Online Documents on Economics 60954, London School of Economics and Political Science, LSE Library.

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    More about this item

    Keywords

    financial contagion; minority; majority game; agent-based model; evolutionary; parameter optimisation;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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