All established methods for detecting positive selection at the molecular level rely on comparisons between nucleotide sequences. An exceptional method that purports to detect selection on the basis of a single genomic sequence has recently been proposed. This method uses a measure called "codon volatility," defined for each codon as the ratio between the number of nonsynonymous codons that differ from the codon under study at a single nucleotide position and the number of sense codons that differ from the codon under study at a single nucleotide position. Here, we examine various properties of codon volatility and its derivatives and use simulation of evolutionary processes to determine whether they can be used to detect selective pressures. Codons for only four amino acids (glycine, leucine, arginine, and serine) show any variation in codon volatility. Thus, codon volatility is mainly a proxy for amino acid usage, rather than for codon usage, with 65% of all synonymous changes and 27% of all nonsynonymous changes being undetectable by this measure. Genes identified by the volatility method as being subject to positive selection tend to have idiosyncratic amino acid compositions (e.g., they are glycine rich or arginine poor). An additional property of codon volatility is the near zero variance of its mean expectation, which translates into overestimated statistical significance estimates, especially in the absence of corrections for multiple comparisons. A comparison with measures of selection inferred through comparative methodology reveals no relationship between the results of the two methods. Finally, we show that codon volatility can increase in the absence of positive Darwinian selection; that is, increased codon volatility is not indicative of positive selection.