2022/09 | LEM Working Paper Series | ||||||||||||||||
On the evolutionary stability of the sentiment investor |
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Andrea Antico, Giulio Bottazzi and Daniele Giachini |
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Keywords | |||||||||||||||||
Learning; Market Selection; Investor Sentiment; Model Misspecification; Financial Markets.
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JEL Classifications | |||||||||||||||||
C60, D53, D81, D83, D91, G11, G12
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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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