Strategically biased learning in market interactions - Giulio Bottazzi; Daniele Giachini (Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM), 2022)
We consider a market economy where two rational agents are able to learn the distribution of future events. In this context, we study whether moving away from the standard Bayesian belief updating, in the sense of under-reaction to some degree to new information, may be strategically convenient for traders. We show that, in equilibrium, strong under-reaction occurs, thus rational agents may strategically want to bias their learning process. Our analysis points out that the underlying mechanism driving ex-ante strategical decisions is diversity seeking. Finally, we show that, even if robust with respect to strategy selection, strong under-reaction can generate low realized welfare levels because of a long transient phase in which the agent makes poor predictions.
Keywords: C60; D53; D81; D83; G11; G12; 330; Learning; Strategic interaction; Behavioral Bias; Financial Markets