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論文名稱 Title |
利用基因表達規劃之投資組合方法 Portfolio Investment Based on Gene Expression Programming |
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系所名稱 Department |
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畢業學年期 Year, semester |
語文別 Language |
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學位類別 Degree |
頁數 Number of pages |
101 |
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研究生 Author |
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指導教授 Advisor |
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召集委員 Convenor |
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口試委員 Advisory Committee |
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口試日期 Date of Exam |
2016-02-17 |
繳交日期 Date of Submission |
2016-02-18 |
關鍵字 Keywords |
投資組合管理、相關係數、技術指標、股票投資、權重計算、顯著性 technical indicator, weighting, stock investment, portfolio redemption, significant, correlation coefficient |
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統計 Statistics |
本論文已被瀏覽 5693 次,被下載 403 次 The thesis/dissertation has been browsed 5693 times, has been downloaded 403 times. |
中文摘要 |
本論文中,我們結合了使用李承翰的交易訊號與股票排名的方法,以及蔡宗榮提出的投資組合交易結構,來形成一個投資組合管理的股票投資方法。 為了找出用來為股票排名的顯著性技術指標,我們首先計算了多個技術指標與次日報酬率的相關係數。我們發現RSI、CMO、MOM、BIAS、OSC、TAPI,以及MACD是顯著性的技術指標。 我們提出三個為這些顯著性的技術指標產生權重的方法,分別是W^((1))、W^((2)),以及W^((3))。為了得到穩定的權重方程式,我們將三年的資料切割成權重區間(第一年)、集合區間(第二年),以及測試區間(第三年)。權重區間用來計算同一組內的各個技術指標之間的權重。集合區間用來計算不同組的技術指標之間的權重。測試區間則是用來計算最後的投資組合報酬率。 我們的權重區間開始自1995年初,至2013年底,並自2002年初開始交易直到2015年底。我們的方法在使用(W^((1) ),W^((1) ))的權重組合情況下的平均年化報酬率為15.79%。除此之外,若在投資組合大小與贖回門檻值被限制在3到10之間與40%到80%之間的情況下,平均年化報酬率為18.52%,這也優於buy-and-hold方式的年化報酬率(9.26%)與李承翰的方法的年化報酬率(11.05%)。 關鍵詞:技術指標、相關係數、投資組合管理、顯著性、權重計算、股票投資 |
Abstract |
In this thesis, we combine the stock ranking method with the trading signals generated by Lee et al. and the portfolio redemption scheme proposed by Tsai et al. to form a stock investment method with portfolio management. To find significant technical indicators for ranking stocks, we first calculate Pearson's product moment correlation coefficient of several technical indicators and the one-day-ahead returns. We find that the technical indicators RSI, CMO, MOM, BIAS, OSC, TAPI, and MACD are significant. Three weighting methods W^((1)), W^((2)) and W^((3)) are used to weight these significant indicators. To get stable weight functions, the data of every three years are divided into the weighting interval (first year), aggregating interval (second year) and testing interval (third year). The weighting interval is used for calculating the weights of the indicators within a group; the aggregating interval is used for calculating the aggregative weight of each group of indicators; the testing interval is used to calculate the investment return of the portfolio. Our weighting interval starts from 1995/1/5 and ends on 2013/12/31, and we start trading from 2002/1/4 until 2015/12/31. The average annualized return of our method is 15.79% with the weight combination (W^((1) ),W^((1) )). Furthermore, if the portfolio size and the redemption threshold are confined to 3 ≤ P ≤ 10 and 40% ≤ T ≤ 80%, respectively, the average annualized return is 18.52%, which is better than the annualized returns of the buy-and-hold strategy (9.26%) and Lee's method (11.05%). Keywords: technical indicator, correlation coefficient, portfolio redemption, significant, weighting, stock investment |
目次 Table of Contents |
TABLE OF CONTENTS 論文審定書 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i THESIS VERIFIVATION FORM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii 論文公開授權書. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii 謝辭. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv 摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii Chapter 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Chapter 2. Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4 2.1 Gene Expression Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Dynamic Time Warping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.3 Lee's Trading Strategy Training Method. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12 2.4 Tsai's Scoring Function for Funds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18 2.5 Technical Indicators of Stocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 2.5.1 Moving Average . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 2.5.2 Exponential Moving Average . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 2.5.3 Momentum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21 2.5.4 Oscillator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.5.5 Relative Strength Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.5.6 Chande Momentum Oscillator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.5.7 Bias Ratio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.5.8 Moving Average Convergence/Divergence . . . . . . . . . . . . . . . . . . . . . . . .22 2.5.9 Total Amount Per Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.5.10 On Balance Volume . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23 Chapter 3. Our Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24 3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.2 Stock Trading and Portfolio Redemption . . . . . . . . . . . . . . . . 26 3.3 The Scoring Functions with Technical Indicators . . . . . . . . . . . . 27 3.4 The Weights of the Indicators . . . . . . . . . . . . . . . . . . . . . . 29 Chapter 4. Experimental Results . . . . . . . . . . . . . . . . . . . . . . 35 4.1 Target Stocks and Technical Indicators . . . . . . . . . . . . . . . . . 35 4.2 Correlation Test between Technical Indicators and Returns . . . . . . 35 4.3 Experimental Environment . . . . . . . . . . . . . . . . . . . . . . . . 39 4.4 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.5 Similarity Analysis of the Trading Process . . . . . . . . . . . . . . . 48 Chapter 5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Appendixes A. The Full Results of ADF Test and Correlation Test . . . . . . . . 59 |
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