  Factorial moments are convenient tools in nuclear physics to characterize the
multiplicity distributions when phase-space resolution ($\Delta$) becomes
small. For uncorrelated particle production within $\Delta$, Gaussian
statistics holds and factorial moments $F_q$ are equal to unity for all orders
$q$. Correlations between particles lead to a broadening of the multiplicity
distribution and to dynamical fluctuations. In this case, the factorial moments
increase above 1 with decreasing $\Delta$. This corresponds to what can be
called intermittency. In this letter, we show that a similar analysis can be
developed on financial price series, with an adequate definition of factorial
moments. An intermittent behavior can be extracted using moments of order 2
($F_2$), illustrating a sensitivity to non-Gaussian fluctuations within time
resolution below 4 hours. This confirms that correlations between price returns
start to play a role when the time resolution is below this threshold.
