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The main aim of this work is to incorporate selected findings frombehavioural finance into a Heterogeneous Agent Model using the Brock and Hommes(1998) framework. Behavioural patterns are injected into an asset pricingframework through the so-called `Break Point Date', which allows us to examinetheir direct impact. In particular, we analyse the dynamics of the model aroundthe behavioural break. Price behaviour of 30 Dow Jones Industrial Averageconstituents covering five particularly turbulent U.S. stock market periodsreveals interesting pattern in this aspect. To replicate it, we apply numericalanalysis using the Heterogeneous Agent Model extended with the selectedfindings from behavioural finance: herding, overconfidence, and marketsentiment. We show that these behavioural breaks can be well modelled via theHeterogeneous Agent Model framework and they extend the original modelconsiderably. Various modifications lead to significantly different results andmodel with behavioural breaks is also able to partially replicate pricebehaviour found in the data during turbulent stock market periods.

Behavioural breaks in the heterogeneous agent model: the impact of herding, overconfidence, and market sentiment