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A Real-world What-Where-When Memory Test
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Information Cost, Memory Length and Market Instability.

Cees Diks1, Xindan Li2, Chengyao Wu3

  • 1University of Amsterdam, The Netherlands.

Nonlinear Dynamics, Psychology, and Life Sciences
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Summary
This summary is machine-generated.

This study reveals that increased information costs or reduced memory in uninformed traders can destabilize stock markets. This leads to chaotic price dynamics and significant deviations from fundamental values.

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Area of Science:

  • Financial economics
  • Market dynamics
  • Agent-based modeling

Background:

  • Stock markets exhibit complex dynamics due to heterogeneous agent interactions.
  • Existing models may not fully capture realistic price behavior and information absorption.

Purpose of the Study:

  • To investigate stock market instability using a modified agent-based model.
  • To analyze the impact of new information and investor behavior on market stability.
  • To understand how markets absorb information during periods of instability.

Main Methods:

  • Modified Diks and Dindo (2008) model with logistic strategy switching.
  • Analysis of nonlinear interactions between informed and uninformed traders.
  • Exploration of bifurcations and chaotic dynamics.

Main Results:

  • Market dynamics become locally unstable with increased information costs or decreased memory.
  • Prices can deviate significantly from fundamental values, indicating inefficient information absorption.
  • The model demonstrates a route to chaos through bifurcation.

Conclusions:

  • Investor behavior and information costs are critical drivers of stock market instability.
  • The modified model provides a more robust framework for studying realistic market price dynamics.
  • Understanding these dynamics is crucial for market stability and efficient information processing.