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Asymmetric Information and Learning by Imitation in Agent-Based Financial Markets

  • Luca Gerotto
  • Paolo PellizzariEmail author
  • Marco Tolotti
Conference paper
  • 339 Downloads
Part of the Communications in Computer and Information Science book series (CCIS, volume 1047)

Abstract

We describe an agent-based model of a market where traders exchange a risky asset whose returns can be partly predicted purchasing a costly signal. The decision to be informed (at a cost) or uninformed is taken by means of a simple learning by imitation mechanism that periodically occurs.

The equilibrium is characterized describing the stationary distribution of the price and the fraction of the informed traders. We find that the number of agents who acquire the signal decreases with its cost and with agents’ risk aversion and, conversely, it increases with the signal-to-noise ratio and when learning is slow, as opposed to frequent. Moreover, price volatility appears to directly depend on the fraction of informed traders and, hence, some heteroskedasticity is observed when this fraction fluctuates.

Keywords

Agent-based modeling Bounded rationality Information in financial markets 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of EconomicsCa’ Foscari UniversityVeniceItaly
  2. 2.Department of ManagementCa’ Foscari UniversityVeniceItaly

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