  We show that the moments of the distribution of historic stock returns are in
excellent agreement with the Heston model and not with the multiplicative
model, which predicts power-law tails of volatility and stock returns. We also
show that the mean realized variance of returns is a linear function of the
number of days over which the returns are calculated. The slope is determined
by the mean value of the variance (squared volatility) in the mean-reverting
stochastic volatility models, such as Heston and multiplicative, independent of
stochasticity. The distribution function of stock returns, which rescales with
the increase of the number of days of return, is obtained from the steady-state
variance distribution function using the product distribution with the normal
distribution.
