We outline a method for quantifying the error of a sequence prediction.  With sequence predictions represented by semimeasures $\nu(x)$ we define their error to be $-\log_2 \nu(x)$.  We note that enumerable semimeasures are those which model the sequence as the output of a computable system given unknown input.  Using this we define the simulation complexity of a computable system $C$ relative to another $U$ giving an \emph{exact} bound on their difference in error.  This error in turn gives an exact upper bound on the number of predictions $\nu$ gets incorrect.