We believe that in order to test for weak form efficiency in the market a vast pool of individual stocks must be analyzed rather than a stock market index. In this paper, we use a model-based bootstrap to generate a series of simulated trials and apply a modified chart pattern recognition algorithm to all stocks listed on the Toronto Stock Exchange (TSX). We compare the number of patterns detected in the original price series with the number of patterns found in the simulated series. By simulating the price path we eliminate specific time dependencies present in real data, making price changes purely random. Patterns, if consistently identified, carry information which adds value to the investment process, however, this informativeness does not guarantee profitability. We draw conclusions on the relative efficiency of some sectors of the economy. Although, we fail to reject the null hypothesis of weak form efficiency on the TSX, some sectors of the Canadian economy appear to be less efficient than others. In addition, we find negative dependency of pattern frequencies on the two moments of return distributions, variance and kurtosis.