  We prove a moderate deviation principle for the continuous time interpolation
of discrete time recursive stochastic processes. The methods of proof are
somewhat different from the corresponding large deviation result, and in
particular the proof of the upper bound is more complicated. The results can be
applied to the design of accelerated Monte Carlo algorithms for certain
problems, where schemes based on moderate deviations are easier to construct
and in certain situations provide performance comparable to those based on
large deviations.
