本文以台灣五十成分股為研究標的，從作多角度進行區間突破與肯特納通道兩種通道突破系統回測。研究期間坐落於2007/8/27至2015/2/4，資料頻率為三十分鐘，藉子期間的選擇去除趨勢後，探討下列策略於台灣五十成分股之績效。
一、 上界＝近四十天以來最高收盤價、下界＝近二十天以來最低收盤價
以三十分K收盤價突破產生進出場訊號
二、 上界＝近二十天以來最高的最高價、下界＝近四十天以來最低的最低價
以三十分K收盤價突破產生進出場訊號
三、 上界＝近二十天以來最高的最高價、下界＝近四十天以來最低的最低價
以三十分K最高價突破產生進出場訊號
四、 上界＝20EMA+10ATR*2、下界＝20EMA-10ATR*2
以三十分K收盤價突破產生進出場訊號
五、 上界＝20EMA+14ATR*2、下界＝20EMA-14ATR*2
以三十分K收盤價突破產生進出場訊號
上述策略進行敏感度分析挑出最佳策略後，運用蒙地卡羅排列模擬進一步檢視成分股績效品質，並觀察策略下成分股報酬率與股價波動度是否存在關係。附錄揭露蒙地卡羅排列模擬達顯著、以及最佳策略下負報酬的個股之報酬結構與股價走勢。綜合上述，本研究得到以下結論:
一、 經通道參數調整後，本文定義的策略對台灣五十成分股回測績效都不錯，且具備統計上顯著。
二、 經敏感度分析後，最佳策略為:上界＝近二十五天以來最高的最高價、下界＝近四十天以來最低的最低價，以三十分K最高價突破產生進出場訊號。經蒙地卡羅排列模擬檢測後，顯著水準5%下，有六檔成分股績效品質特別良好，放寬顯著水準10%下，則另增加三檔。
三、 在最佳策略下，成分股報酬表現與股價波動度存在中度正相關。

This study backtest two kinds of breakout trading systems- Trading Range Breakout and Keltner Channel- for constituent stocks in Taiwan top 50. The data period is from 2007/8/27 to 2015/2/4 with thirty-minute frequency. We detrend the data via selecting sub period. We defined five strategies with different structure and executed sensitivity analysis in terms of parameters of upper and lower boundary.
1. Upper boundary=the maximum close price within the latest 40 days
Lower boundary= the minimum close price within the latest 20 days
Signal occurs when the close price of thirty-minute candlestick breakout the range.
2. Upper boundary=the maximum high price within the latest 20 days
Lower boundary= the minimum low price within the latest 40 days
Signal occurs when the close price of thirty-minute candlestick breakout the range.
3. Upper boundary=the maximum high price within the latest 20 days
Lower boundary= the minimum low price within the latest 40 days
Signal occurs when the high price of thirty-minute candlestick breakout the range.
4. Upper boundary=20EMA+10ATR*2
Lower boundary=20EMA-10ATR*2
Signal occurs when the close price of thirty-minute candlestick breakout the range.
5. Upper boundary=20EMA+14ATR*2
Lower boundary=20EMA-14ATR*2
Signal occurs when the close price of thirty-minute candlestick breakout the range.
We selected the best strategy to executed Monte-Carlo permutation simulation to check the quality of return among constituent stocks, and checked whether there exist a relationship between returns and volatility of prices. The appendix shows return patterns for stocks with negative total return and stocks which are remarkable under the execution of Monte-Carlo permutation simulation. The empirical findings are summarized as follows:
1. After adjusting parameters of upper and lower boundary, the performance of breakout trading systems we defined are well and statistically significant during research period.
2. The best strategy we found is:
Upper boundary=the maximum high price within the latest 25 days
Lower boundary= the minimum low price within the latest 40 days
Signal occurs when the high price of thirty-minute candlestick breakout the range.
Monte-Carlo permutation simulation demonstrates that there are six stocks with high quality of return when significant level is 5%, and nine stocks when significant level is 10% under the best strategy.
3. There is moderately positive correlation between returns and volatility of prices under the best strategy.

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