  A simple analytically solvable model exhibiting a 1/f spectrum in an
arbitrarily wide frequency range was recently proposed by Kaulakys and
Meskauskas (KM). Signals consisting of a sequence of pulses show that inherent
origin of the 1/f noise is Brownian fluctuations of the average intervent time
between subsequent pulses of the pulse sequence. We generalize the KM model to
reproduce the variety of self-affine time series exhibiting power spectral
density S(f) scaled as power of their frequency f. Numerical calculations with
the generalized discrete model (GDM) reproduce power spectral density S(f)
scaled as power of frequency 1/f^b for various values of b, including b =1/2
for applications in financial markets. The particular applications of the model
proposed are related with financial time series of share volume traded.
