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Social Simulation of Stock Markets: Taking It to the Next Level

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Abstract

This paper studies the use of social simulation in linking micro level investor behaviour and macro level stock market dynamics. Empirical data from a survey on individual investors' decision-making and social interaction was used to formalize the trading and interaction rules of the agents of the artificial stock market SimStockExchange. Multiple simulation runs were performed with this artificial stock market, which generated macro level results, like stock market prices and returns over time. These outcomes were subsequently compared to empirical macro level data from real stock markets. Partial qualitative as well as quantitative agreement between the simulated asset returns distributions and the asset returns distributions of the real stock markets was found.

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  • Arvid Oskar Ivar Hoffmann & Wander Jager & J. H. Von Eije, 2007. "Social Simulation of Stock Markets: Taking It to the Next Level," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-7.
    • Handle: RePEc:jas:jasssj:2006-33-3
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    Cited by:

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    2. Lovric, M. & Kaymak, U. & Spronk, J., 2008. "A Conceptual Model of Investor Behavior," ERIM Report Series Research in Management ERS-2008-030-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Bertazzi, Ilaria, 2014. "Transitivity matters. Norms Enforcement and diffusion using different neighborhoods in CAs," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201429, University of Turin.
    4. Sylvain Mignot & Gabriele Tedeschi & Annick Vignes, 2012. "An Agent Based Model of Switching: The Case of Boulogne S/mer Fish Market," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(2), pages 1-3.
    5. Scott Moss, 2007. "Alternative Approaches to the Empirical Validation of Agent-Based Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(1), pages 1-5.
    6. Matthew Oldham, 2019. "Understanding How Short-Termism and a Dynamic Investor Network Affects Investor Returns: An Agent-Based Perspective," Complexity, Hindawi, vol. 2019, pages 1-21, July.
    7. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.

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