This study applies a genetic algorithm (GA) to generate trading rules for currency trading based on a single technical indicator named the Relative Strength Index (RSI) as well as multiple timeframes from which we extract the feature. The target trading currency pair is EUR/USD and trading time horizon is one hour. Using more than one timeframe may improve the assessment of the overbought or oversold conditions of the target currency pair, since different traders may have different trading time horizons and thus a trader may consider the overall condition for trading a currency pair from both its longer and shorter timeframes. Therefore, this paper uses a combined signal from a relatively longer timeframe (two hours) and a relatively shorter timeframe (30 minutes), other than the target timeframe (one hour). In addition, since the parameters of the RSI are also crucial for obtaining the best trading rules, we use a GA to search for the best parameters of each RSI. Moreover, we design a GA chromosome to encode trading timing by designating when to buy, sell, and close the position. The experimental results presented in this paper show that the combined signal from multiple timeframes, including that from the target timeframe, improves trading performance.