  We investigate the correlation properties of transaction data from the New
York Stock Exchange. The trading activity f(t) of each stock displays a
crossover from weaker to stronger correlations at time scales 60-390 minutes.
In both regimes, the Hurst exponent H depends logarithmically on the liquidity
of the stock, measured by the mean traded value per minute. All multiscaling
exponents tau(q) display a similar liquidity dependence, which clearly
indicates the lack of a universal form assumed by other studies. The origin of
this behavior is both the long memory in the frequency and the size of
consecutive transactions.
