Investigating Retail Investors’ Decisions in a Social Network using Agent-Based Models

Research output: Contribution to conferenceAbstractpeer-review

With the escalating influence of social media and innovative social trading platforms on financial markets, understanding the behavioural patterns of retail investors becomes increasingly imperative. This study employs an Agent-Based Simulation approach (ABS) to scrutinise the retail investors’ behaviour in a social network. We built on the simulation model developed by Feng et al. (2012) [Feng, L.; Li, B.; Podobnik, B.; and Stanley, H.E. (2012). Linking agent-based models and stochastic models of financial markets. PNAS, 109 (22) 8388-8393], and proposed an innovative opinion clustering process. In particular, retail investors are divided into influencers and followers, where followers are further segregated into trend-chasers, contrarian traders, and noise traders. Trend-chasers buy after positive signals released by their focal influencers and sell after negative; contrarian traders behave conversely; and noise traders, acting independently of incoming signals, add an unpredictable element to the system. The results suggest that our model provides a closer reproduction of “fat” tails of the empirical financial market data compared to the baseline model developed by Feng et al. (2012). Our study provides a nuanced understanding of retail investors’ behaviour. It contributes to a more comprehensive portrayal of the complex financial decision-making in the digital age.


  • Retail investors, Agent based model, Social network
Original languageEnglish
Publication statusPublished - 12 Sep 2023
EventThe Operational Research Society's Annual Conference OR65 - University of Bath, Bath, United Kingdom
Duration: 12 Sep 202314 Sep 2023


ConferenceThe Operational Research Society's Annual Conference OR65
Abbreviated titleAnnual Conference OR65
Country/TerritoryUnited Kingdom
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