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The pairs trading strategy is a popular method for trading financial assets. One of the reasons for such popularity is that the result of this type of operation depends solely on the relationship between the price of two assets, and not on the overall market condition. The possibility of spotting inefficiencies in assets pricing is what allows the investor to make consistent profits using a systematic method for trading financial contracts. Based on the opening of a long and short position, this statistical arbitrage strategy seeks to profit when the prices of both assets converge to their historical behavior. The objective of this paper is to analyze the performance of the pairs trading strategy for different frequencies of data in the Brazilian Stock Market. The study was based on Perlin (2009), which shows that market inefficiencies are higher for stock data sampled in higher frequency, in this case daily, weekly and monthly. The present research extends the range of frequencies to the intraday universe with stock prices sampled at 1, 5, 15, 30 and 60 minutes and daily. The period of the database starts from 1st January 2008 until 31st December 2011. The selection of stocks comprises the twenty assets with the highest number of contracts negotiated in the period. The methodology employed in this research uses training periods and periods of technical negotiations. In the training period, the selection of pairs for each stock is based on the lowest quadratic variation of their normalized prices. In the trading period, the strategy checks the performance of the previously defined trades. The results of the study, which compared the Sharpe ratios of the pairs trading strategy for the different frequency of the data, confirm the primary hypothesis that the higher sampling frequency, the higher evidence of market inefficiency. [ABSTRACT FROM AUTHOR]