摘要
本研究以臺灣期貨交易所發行之臺灣股價指數期貨為研究標的，採用MultiCharts程式交易軟體，開發一個交易模型及時間模組、空間模組、型態模等三模組搭配停損與停利模型，利用費波那契數列取1分鐘週期、3分鐘週期、5分鐘週期、8分鐘週期及13分鐘週期進行最佳化，回測歷史區間為2009年1月1日至2019年12月31日止進行當沖交易最佳化，最佳化結果取每週期淨利排序前十名參數組合成投資組合策略，取出5組不同周期的投資組合共50個交易策略。
本研究結果發現利用5組投資組合套用在2020年1月1日至2020年8月31日止，不論是1分鐘週期、3分鐘週期、5分鐘週期、8分鐘週期及13分鐘週期投資組合皆為獲利，而且有4組策略投資報酬率都優於模擬回測時的投資報酬率，同時驗證了模組化開發的有效性及分散風險的優勢。研究過程中也發現單一策略與組合策略明顯存在策略最大可能虧損的差異性，組合策略所產生的最大可能虧損小於單一策略最大可能虧損，也證明了量化交易可以有效降低投策略虧損。
關鍵詞：臺灣股價指數期貨、MultiCharts、費波那契數列、當沖交易、量化交易

Abstract
This research uses the TAIFEX issued by Taiwan Futures Exchange as the research subject, and uses the MultiCharts program trading software to develop a trading model comprised of a time module, a space module, and a pattern module, with stop loss and stop profit models. This study uses the Fibonacci sequence to take the 1-minute period, 3-minute period, 5-minute period, 8-minute period, and 13-minute period to optimize. This study uses a strategy back-testing on historical interval from January 1, 2009 to December 31, 2019, an optimization of current transactions was carried out. The results of the back-testing were combined with the top ten parameters of each period's net profit ranking to form a portfolio strategy. A total of 50 trading strategies were derived from the 5 sets of portfolios representing the different time periods optimized.
The results of this study show that the use of these 5 sets of investment portfolios applied from January 1, 2020 to August 31, 2020, whether it be the 1-minute period, 3-minute period, 5-minute period, an 8-minute period, or a 13-minute period investment portfolio were all profitable, and the returns on investment of four of the five portfolios were better than the return on investment during the simulation back testing, which verifies the effectiveness of modular development and the advantages of risk diversification. During the research process, it was also found that there is a clear difference between the maximum possible loss of a single strategy and that of a combination strategy. The maximum possible loss of a combination strategy is less than the maximum possible loss of a single strategy, which proves that quantitative trading as a strategy is effective at reducing investment loss.
Keywords: TAIFEX, MultiCharts, Fibonacci Sequence, Day-trade, optimization, Quantitative Trading

1. 丁鵬(2012) 量化投資:策略與技術，中國。電子工業出版社
2. 李佳儒(2010) 譯The Evaluation and Optimization of Trading Strategies(2nd edition) Robert Pardo 著(P16~24)，寰宇出版股份有限公司
3. 姜林杰祐(2012)程式交易方法與實務應用(P135~P146)，新陸書局股份有限公司
4. 張林忠（2012）分析師的關鍵報告，寰宇出版股份有限公司
5. 莊文澤(2018) 臺灣指數期貨商品當沖交易與K線交易策略績效之研究，國立高雄科技大學財務管理系碩士論文
6. 鄧運隆等人(2009)TradeStation 2000i程式交易全攻略(P66)，寰宇出版股份有限公司
7. 鐘淳豐(2012) PowerLanguage程式交易語法大全，寰宇出版股份有限公司