2022/09 LEM Working Paper Series

On the evolutionary stability of the sentiment investor

Andrea Antico, Giulio Bottazzi and Daniele Giachini
  Keywords
 
Learning; Market Selection; Investor Sentiment; Model Misspecification; Financial Markets.


  JEL Classifications
 
C60, D53, D81, D83, D91, G11, G12
  Abstract
 
The behavioural finance literature attributes the persistent market misvaluation observed in real data to the presence of deviations from rational thinking of the actors involved. Cognitive biases and the use of simple heuristics can be described using expected utility maximising agents that adopt incorrect beliefs. Along these lines, Barberis et al. (1998) introduce a model which is able to replicate the behavior of both under-reaction and over-reaction to news. The representative agent they consider is characterized by an imperfect learning model. An interesting question that emerges is if, and to what degree, the heuristic mechanism they propose is evolutionary stable, that is how resilient is their representative agent to other agents possibly trading in the market. In fact, if the biased agent asymptotically disappears from the market, the misvaluation patters generated by its behavior does not survive in the long term. The present paper investigates this question comparing the performance of the agent described in Barberis et al. (1998) with the one of a pure Bayesian competitor.
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