This paper analyzes two price discovery processes: OLS learning from public information and a Bayesian learning made feasible by futures markets. The former tends to produce cobweb behaviour. In the latter, there is no cobweb, there is a faster convergence to Muth Rational Expectations, and the forecast errors are positively serially correlated The evidence drawn from the Sydney Futures Exchange is consistent with the Bayesian learning process.