  We present an empirical study of the subordination hypothesis for a
stochastic time series of a stock price. The fluctuating rate of trading is
identified with the stochastic variance of the stock price, as in the
continuous-time random walk (CTRW) framework. The probability distribution of
the stock price changes (log-returns) for a given number of trades N is found
to be approximately Gaussian. The probability distribution of N for a given
time interval Dt is non-Poissonian and has an exponential tail for large N and
a sharp cutoff for small N. Combining these two distributions produces a
nontrivial distribution of log-returns for a given time interval Dt, which has
exponential tails and a Gaussian central part, in agreement with empirical
observations.
