  While the investors' responses to price changes and their price forecasts are
well accepted major factors contributing to large price fluctuations in
financial markets, our study shows that investors' heterogeneous and dynamic
risk aversion (DRA) preferences may play a more critical role in the dynamics
of asset price fluctuations. We propose and study a model of an artificial
stock market consisting of heterogeneous agents with DRA, and we find that DRA
is the main driving force for excess price fluctuations and the associated
volatility clustering. We employ a popular power utility function,
$U(c,\gamma)=\frac{c^{1-\gamma}-1}{1-\gamma}$ with agent specific and
time-dependent risk aversion index, $\gamma_i(t)$, and we derive an approximate
formula for the demand function and aggregate price setting equation. The
dynamics of each agent's risk aversion index, $\gamma_i(t)$ (i=1,2,...,N), is
modeled by a bounded random walk with a constant variance $\delta^2$. We show
numerically that our model reproduces most of the ``stylized'' facts observed
in the real data, suggesting that dynamic risk aversion is a key mechanism for
the emergence of these stylized facts.
