臺灣博碩士論文加值系統

近年來，在股票交易市場中擁有一個好的交易策略能夠使投資人獲得良好投資收益，因此如何找出良好交易策略已成為投資人眼中最為重要的事情。本研究中，我們針對投資組合交易策略最佳化問題進行研究，目標是為了幫助投資人在股票市場中取得最大獲利。我們提出了一個以遺傳演算法為基礎的方法，為了提高搜尋能力，我們平衡了演算法在演化過程中的探索與開發行為，使得族群在演化過程中擁有足夠的多樣性。另外，我們加入考慮破產風險與交易難度的懲罰機制，最終所得出的策略具有良好的報酬率、減少了破產風險且降低了交易難度。相較於文獻上的其他方法或台灣加權指數買進且持有交易策略，實驗結果顯示本文所提出之演算法對於投資組合交易策略最佳化問題的穩定性、最大獲利與風險控制皆有良好表現。

In recent years, having a good trading strategy in the stock trading market enables investors to obtain good investment returns. Therefore, how to find a good trading strategy has become the most important thing for investors. In this study, we focus on optimizing investment portfolio trading strategies, which’s goal is to help investors maximize profits in the stock market. We propose a method based on the genetic algorithms. In order to improve the search capability, we balance the exploration and exploitation behaviors of the algorithm in the evolutionary process, which results in sufficient diversity in the population during the evolutionary process. Additionally, we also incorporate a penalty mechanism that considers bankruptcy risks and trading difficulties. The resulting strategy has a good return rate, reduces bankruptcy risks, and lowers trading difficulties. Compared with other methods in the literature or the buy and hold trading strategy of Taiwan capitalization weighted stock index, the experimental results show that the algorithm proposed in the study has a good performance on the stability of investment portfolio trading strategies, making maximum profit and risk control.

中文摘要 i
ABSTRACT ii
誌謝 iii
目錄 iv
表目錄 vii
圖目錄 ix
第一章 緒論 1
1.1 研究背景 1
1.1 研究動機與目的 1
1.2 研究架構 3
第二章 問題塑模 4
第三章 相關研究 6
3.1 股票相關技術指標 6
3.1.1 移動平均線 6
3.1.2 隨機指標 6
3.1.3 相對強弱指標 7
3.1.4 指數平滑異同平均線 8
3.1.5 布林通道 10
3.2 破產風險與交易難度 11
3.2.1 破產風險 11
3.2.2 交易難度 14
3.3 解決量化交易問題的機器學習技術 16
3.3.1 支持向量機 16
3.3.2 人工神經網路 17
3.3.3 長短期記憶神經網路 19
3.4 解決量化交易問題的啟發式演算法 20
3.4.1 遺傳演算法 20
3.4.2 粒子群最佳化演算法 24
第四章 設計方法 27
4.1 方法架構 27
4.2 遺傳演算法建構交易策略 28
4.2.1 問題編碼 29
4.2.2 適存值評估 33
4.2.3 算術交配運算子 34
4.2.4 遮罩式突變運算子 34
4.2.5 輪盤選擇運算子 36
4.3 實例說明 .37
第五章 效能分析與比較 40
5.1 實驗設計說明 40
5.2 本研究所提方法在優化個股交易策略方面的效能比較 41
5.3 本研究所提方法在優化投資組合交易策略方面的效能比較 48
5.3.1 突變率與突變運算子之實驗比較 48
5.3.2 加入懲罰機制 (破產風險與交易難度) 之實驗比較 51
5.3.3 問題編碼僅使用布林通道之實驗比較 54
5.3.4 應用於更長測試集的實驗結果 55
第六章 結論 59
參考文獻 60
附錄 (一) 64

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