  Price fluctuations of commodities like cotton and wheat are thought to
display probability distributions of returns that follow a L\'evy stable
distribution. Recent analysis of stocks and foreign exchange markets show that
the probability distributions are not L\'evy stable, a plausible result since
commodity markets have quite different features than stock markets. We analyze
daily returns of 29 commodities over typically 20 years and find that the
distributions of returns decay as power laws with exponents $\alpha$ which have
values $\alpha > 2$, outside the L\'evy-stable domain. We also find that the
amplitudes of the returns display long-range time correlations, like stocks,
while the returns themselves are uncorrelated for time lags $\approx$ 2 days,
much larger than for stocks ($\approx$ 4 min).
