  We study the mean escape time in a market model with stochastic volatility.
The process followed by the volatility is the Cox Ingersoll and Ross process
which is widely used to model stock price fluctuations. The market model can be
considered as a generalization of the Heston model, where the geometric
Brownian motion is replaced by a random walk in the presence of a cubic
nonlinearity. We investigate the statistical properties of the escape time of
the returns, from a given interval, as a function of the three parameters of
the model. We find that the noise can have a stabilizing effect on the system,
as long as the global noise is not too high with respect to the effective
potential barrier experienced by a fictitious Brownian particle. We compare the
probability density function of the return escape times of the model with those
obtained from real market data. We find that they fit very well.
