本研究提出了一種新型的自動股票交易系統,只使用一個簡單但常見的技術指標即移動平均線(Moving Average),並放寬參數以拓展其解空間。本方法也分析了加權移動平均(Weighted Moving Average)和指數移動平均(Exponential Moving Average)。此外,本方法使用經過改良的量子啟發式禁忌搜索演算法(Global best Quantum Tabu Search)以達到快速及穩定搜索合適的交易策略。且股票市場擁有大量歷史資訊,因太過久遠而失去參考價值,所以本方法結合滑動視窗在訓練-測試區間以不同長度進行實驗,並提出了隔年同期訓練-測試區間及分別持錢或持股的兩段式訓練,以解決更全面的股票交易問題。除了買低賣高的交易方式,交易系統還採用另一種合法的交易方式,融券。實驗結果表明,我們的方法改善了移動平均的能力;隔年同期訓練-測試及兩段式訓練的滑動視窗可以改善交易系統的表現;交易系統採用融券交易時可以顯著提高投資利潤。
This research proposes a novel dynamic trading system utilizing only one simple but common technical indicator, the moving average (MA), albeit in a way which differs from traditional methods. We also analyze the weight moving average (WMA) and exponential moving average (EMA), which has the multiplying factor of MA. In addition, a modified evolutionary algorithm, the globe best-guide quantum-inspired tabu search algorithm (GQTS), was created to quickly and stably search for the optimal combination of MA parameters. In order to avoid the overfitting problem, this approach applied the sliding window, and raised the 2-phase sliding window and year-on-year training period to address more comprehensive stock trading problems. In addition to normal stock trading, this system adopts another legal trading method, short selling. The experiment results reveal that our method has a greatly improved MA ability. The result indicates that the WMA always has the best performance in four different targets. The sliding window period with 2-phase and year-on-year can improve the performance of the trading system. When the trading system adopts short selling it can significantly improve investment profit.