Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
April 10, 2026Northeast Journal of Complex SystemsOpen Access

Behavioral Biases as Drivers of Complexity in Stock Markets: An Agent-Based Modeling Approach

View Full Paper
Ask AI
Bookmark
Share

Authors

DJDavid JosephAJAlwin JosephBJBlesson Varghese James

Discussion

Loading...

Member takes

Overview

Agent-based modeling explores complexity in stock markets due to behavioral biases, suggesting significant implications for stability.

Key Points

  • This research aims to understand how behavioral biases influence complexity in stock markets.
  • Utilized agent-based modeling to simulate financial systems as complex adaptive systems.
  • Incorporated heterogeneous agents, including rational traders and behavioral investors.
  • Calibrated models for U.S. and Indian market conditions using the ABIDES simulation environment.
  • Conducted Monte Carlo simulations to analyze price dynamics, volatility, and liquidity structures.
  • Behavioral biases lead to nonlinear price reactions in stock markets.
  • Emergent complexity produces heavy-tailed return distributions that complicate order-book dynamics.
  • Increased influence of biased actors results in heightened market volatility and instability.
  • The market transitions from stable to complex, fragile liquidity conditions as biased participants rise.

Cite This Study

Joseph et al. (2026) studied this question.

synapsesocial.com/papers/69d894326c1944d70ce05226https://doi.org/10.63562/2577-8439.1143
View Full Paper
Ask AI
Bookmark
Share