A well-defined agent-based model able to match the
widely observed properties of financial assets is valuable for
testing the implications of various empirically observed heuristics
associated with investors behaviour. In this paper, we extend one
of the most successful models in capturing the observed behaviour
of traders, and present a new behavioural asset pricing model
with heterogeneous agents. Specifically, we introduce a new be-
havioural bias in the model, loss aversion, and show that it causes
a major difference in the agents interactions. As we demonstrate,
the resulting dynamics achieve one of the major objectives of the
field, replicating a rich set of the stylized facts of financial data.
In particular, for the first time our model enables us to match
the following empirically observed properties: conditional heavy
tails of returns, gains/loss asymmetry, volume power-law and long
memory and volume-volatility relations.