SOCIAL SIMULATION OF STOCK MARKETS: TAKING IT TO THE NEXT LEVEL

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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