Impacts of social networks in an agent-based artificial stock market

Xiaoting Dai, Jie Zhang, Victor Chang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


We propose an agent-based artificial stock market to investigate the influences of social networks on financial markets. It contains four types of traders whose information sets and trading strategies are different. The application of artificial intelligence is employed in informed and uninformed traders’behaviour and heterogeneity. When information is exogenous, social networks result in higher volatility and trading volume and lower price distortion and bid-ask spread. When information is endogenous, the influences are reversed. The reason is that social networks harm information production after traders tend to rely on information from communication, instead of spending a cost on it.

Original languageEnglish
Article number2008514
JournalEnterprise Information Systems
Issue number5
Publication statusPublished - 2023


  • Social networks
  • artificial intelligence
  • bid-ask spread
  • genetic programming
  • price distortion
  • trading volume
  • volatility


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