結合交易點預測之動態投資組合管理系統

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姓名

黃俞翔(Yu-hsiang Huang) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

結合交易點預測之動態投資組合管理系統
(Dynamic Portfolio Management with Trading Signal Prediction)

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摘要(中)

投資組合管理系統旨為將有限的資金，在眾多投資標的中，做有效的配置，並賺取更多的報酬，其獲利的兩大關鍵，在於進出場時機判斷及資產的配置。過去大部分研究皆針對特定的功能，如交易訊號的預測、資產的配置、投資目標的設定。然而實際投資時，需要這些功能同時運作，並相互合作，才能真正獲利，因此本研究結合Trading signal prediction[9]、Time Invariant Portfolio Protection[9]、Optimal Dynamic Asset Allocation[20]，形成一投資組合管理系統。我們以固定明確的期望報酬作為投資目標，每次重新配置時，以最可能達到目標報酬的方式選擇投資標的；投資過程中並結合資產配置機制，使投資組合在資產有效運用下，兼具資產保護的特性。我們藉由轉折點切割股價，利用後傳遞類神經網路學習並預測交易訊號，作為進出場時機點判斷及投資項篩選。同時本研究針對交易訊號轉化方式，提出新的計算方法，以解決原方法中在實用時會遭遇到的最佳化問題。實驗結果顯示，本研究提出的交易訊號轉化方式，解決原方法在實作時所需參數調整的問題，又能取得與原方法參數最佳化後相似的投資效果；另外實驗證明本研究之投資組合管理系統，在市場下跌時，利用資產保護機制，可減少投資組合資產的損失，但也可能造成市場上升時，投資組合獲利不及市場。為解決固定報酬目標對於獲利的限制，當投資組合達到階段性投資目標時，系統將設定新一輪的投資目標，持續投資以克服市場上升時獲利不佳的情況。實驗顯示，此項措施在長期投資中，藉由設定適當的報酬率，可達到更高的投資報酬。

摘要(英)

The goal of portfolio management is to allocate the limited money into multiple securities effectively to earn more money. The two key factors of obtaining high profit are “the trading time” and “asset allocation”. Most of the past researches focus on one specific problem, for example, trading signal prediction, asset allocation, adaptive investment goal setting etc. But in real investment, investors need solutions for all these problems to achieve investment goal. This research combines trading signal prediction [9], Time Invariant Portfolio Protection [10], Optimal Dynamic Asset Allocation [20] into a portfolio management system. In the first part, we use turning points to partition the stock price, and use Back-propagation neural network (BPNN) to learn and predict the trading signal for each stock. We propose a new way to calculate the trading signal to avoid parameter tuning required in [9]. The second part is asset allocation. With asset protection mechanism (TIPP), we set an explicit ROI as the investment goal. We then allocate money for investment target for their probability to reach the investment goal in each rebalance. The experiment shows that the new way to calculate trading signal has similar performance with the original method but avoids the parameter tuning problem. Furthermore, with asset protection mechanism, our portfolio management system would receive less damage in encountering bear market. However, the fixed investment return goal would limit the profit in bull market. Therefore, we start a new round when the portfolio reaches the investment goal, and successfully makes the portfolio management system conquer the problem in bull market. For long-term investment, this mechanism could get better performance by setting appropriate return rate.

關鍵字(中)

★ 投資組合
★ 交易訊號預測

關鍵字(英)

★ portfolio management
★ trading signal prediction

論文目次

中文摘要 I
Abstract II
目錄 III
圖目錄 IV
表目錄 V
一、緒論 1
二、相關研究 3
2.1 投資策略 3
2.2 資產配置─ 4
2.3 交易訊號的預測─ 5
三、研究方法 8
3.1 投資風險與資金管控─ 8
3.2 交易訊號處理及預測─ 9
3.3 投資組合配置 12
3.3.1 進場之程序 12
3.3.2出場之程序─ 14
四、實驗 16
4-1 實驗投資標的之選擇 16
4-2技術指標之選擇 17
4-3不同交易訊號轉化方式投資結果 18
4-4不同市場表現下，投資組合投資結果 19
4-5不同市場表現下，達目標報酬後持續投資之投資結果 20
4-6不同投資時間長度下，投資組合投資結果 23
4-7長期投資下，投資組合投資結果與資產總值變化 25
4-8長期投資下，投資組合在不同目標報酬之資產總值變化 28
五、結論與未來展望 31

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指導教授

張嘉惠(Chia-Hui Chang)

審核日期

2013-8-7

推文