  The common assumption of universal behavior in stock market data can
sometimes lead to false conclusions. In statistical physics, the Hurst
exponents characterizing long-range correlations are often closely related to
universal exponents. We show, that in the case of time series of the traded
value, these Hurst exponents increase logarithmically with company size, and
thus are non-universal. Moreover, the average transaction size shows scaling
with the mean transaction frequency for large enough companies. We present a
phenomenological scaling framework that properly accounts for such
dependencies.
