  We present a time-dependent Langevin description of dynamics of stock prices.
Based on a simple sliding-window algorithm, the fluctuation of stock prices is
discussed in the view of a time-dependent linear restoring force which is the
linear approximation of the drift parameter in Langevin equation estimated from
the financial time series. By choosing suitable weighted factor for the linear
approximation, the relation between the dynamical effect of restoring force and
the autocorrelation of the financial time series is deduced. We especially
analyze the daily log-returns of S$&$P 500 index from 1950 to 1999. The
significance of the restoring force towards the prices evolution are
investigated from its two coefficients, slope coefficient and equilibrium
position. The new simple form of the restoring force obtained both from
statistical and theoretical analyses suggests that the Langevin approach can
effectively present the macroscopical and the detail properties of the price
evolution.
