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研究生:王緯揚
研究生(外文):Wei-Yang Wang
論文名稱:台灣加權股價指數投資績效與持有期間之研究
論文名稱(外文):A Study of Investment Performance and Holding Periods of Taiwan Stock Index
指導教授:林兆欣林兆欣引用關係
指導教授(外文):Chao-Hsin Lin
學位類別:碩士
校院名稱:國立高雄第一科技大學
系所名稱:風險管理與保險所
學門:商業及管理學門
學類:風險管理學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:中文
論文頁數:42
中文關鍵詞:投資績效持有期間技術分析
外文關鍵詞:Technical AnalysisInvestment PerformanceHolding Period
相關次數:
  • 被引用被引用:1
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  • 收藏至我的研究室書目清單書目收藏:1
本研究主要目的是探討投資績效與持有期間兩者間的關聯性,並以2007年1 月2 日至12 月31 日之台灣加權股價指數為研究對象,將技術指標與創新買賣策略相結合來探討在不同買賣時點尋找其最佳投資報酬率,抑或利用技術分析圖形來判斷整體大盤走勢。實證結果顯示,就傳統技術指標而言,以MACD指標所獲得的報酬率為最高,至於在MA 與RSI 指標方面,若將兩者時間間距拉長,即可提高其報酬獲利率。就創新買賣策略而言,若將青年法則與百米策略相結合,其所得到的報酬率為負值,表示該策略應搭配其他指標,以期達到積極投資目的;至於在老頭法則與馬拉松策略方面,該策略適合保守穩健型的投資者,且其平均獲利率高達9.00%,若針對指標時間間距進行調整,且拉長研究資料筆數,應可獲得較佳的結果。
This study explored the relationship between investment performance and holding periods. The study samples are Taiwan Stock Index from Jan, 2 to Dec, 31 2007. The study targets on the decision system concluded by the operation of technical analysis and the innovative trading strategy, and that is in order to earn excess returns in different transaction timing. Moreover, the study applies technical diagram to forecast market movement.
The results revealed that investors could earn the highest return which is according to the indicator of Moving Average Convergence and Divergence (MACD). In addition, the return will increase if the periods of measurement could be extended towards indicators of Moving average (MA) and Relative Strength Index (RSI). However, the returns in terms of innovative trading strategy are negative if we link up Youth rule with Hectometre strategy. It means that the combination strategy should link up other indicators, and that could achieve the objective of constructive investment. In respect to the researching of Old Man rule and Marathon strategy, the average return rate is up to 9% which means that both of the strategies agree with moderate investments. Furthermore, we could get better results if sample periods are extended and timing of indicators is adjusted.
目 錄
中文摘要 -----------------------------------------------i
英文摘要 -----------------------------------------------ii
致謝 -------------------------------------------------- iii
目錄 -------------------------------------------------- iv
表目錄 -------------------------------------------------v
圖目錄 ------------------------------------------------ vii
壹、緒論 ---------------------------------------------- 1
一、研究動機與目的 ------------------------------------ 1
二、研究方法與步驟 -------------------------------------2
貳、理論基礎與相關文獻 -------------------------------- 5
一、技術分析理論架構 ---------------------------------- 5
二、技術指標探討 ---------------------------------------9
三、相關文獻回顧 --------------------------------------12
參、研究方法 ----------------------------------------- 15
一、研究範圍與資料來源 ------------------------------- 15
二、技術指標分析 ------------------------------------- 17
(一) 移動平均線 -------------------------------------- 17
(二) 相對強弱指標 ------------------------------------ 20
(三) 指數平滑異同移動平均線 ---------------------------21
肆、實證結果與分析 ----------------------------------- 24
一、 移動平均線 ---------------------------------------24
二、 相對強弱指標 ------------------------------------ 31
三、 MACD、MA 及RSI 三者相互比較 --------------------- 35
伍、結論與建議 --------------------------------------- 38
參考文獻 --------------------------------------------- 40

表目錄
表3-1 青年法則進場時機判斷表 ------------------------- 18
表3-2 老頭法則進場時機判斷表 ------------------------- 19
表3-3 百米策略買賣點判斷表 --------------------------- 20
表3-4 馬拉松策略買賣點判斷表 ------------------------- 21
表3-5 第2 組策略建議買進時機表 ----------------------- 22
表3-6 第2 組策略建議出場時機表 ----------------------- 22
表3-7 第3 組策略建議買進時機表 ----------------------- 22
表3-8 第3 組策略建議出場時機表 ----------------------- 23
表4-1 MA 指標(6 日,12 日)之投資報酬分析表 ----------- 24
表4-2 MA 指標(6 日,12 日)之買賣時點與價格 ----------- 25
表4-3 MA 指標(12 日,24 日)之投資報酬分析表 ---------- 26
表4-4 MA 指標(12 日,24 日)之買賣時點與價格 ---------- 27
表4-5 MA 指標(24 日,48 日)之投資報酬分析表 ---------- 28
表4-6 MA 指標(24 日,48 日)之買賣時點與價格 ---------- 28
表4-7 青年法則之投資報酬分析表 ----------------------- 29
表4-8 青年法則之買賣時點與價格 ----------------------- 30
表4-9 老頭法則之投資報酬分析表 ----------------------- 30
表4-10 老頭法則之買賣時點與價格 ---------------------- 31
表4-11 MA 指標各項投資策略報酬率比較表 --------------- 31
表4-12 百米策略之投資報酬分析表 ---------------------- 32
表4-13 百米策略之買賣時點與價格 ---------------------- 32
表4-14 馬拉松策略之投資報酬分析表 -------------------- 33
表4-15 馬拉松策略之買賣時點與價格 -------------------- 34
表4-16 12、26 日DIF 與MACD 策略之投資報酬分析表 ------ 35
表4-17 12、26 日DIF 與MACD 策略之買進賣出時機與價格 -- 36
表4-18 MA 與RSI 指標各項投資策略報酬率比較表 --------- 37
表4-19 MACD、MA 與RSI 指標各項投資策略報酬排行 ------- 37

圖目錄
圖1-1 研究流程圖 -------------------------------------- 4
圖3-1 研究樣本期間選擇流程圖 ------------------------- 16
圖4-1 大盤走勢圖 ------------------------------------- 24
圖4-2 MA 指標(6 日,12 日)之走勢圖 ------------------- 26
圖4-3 MA 指標(12 日,24 日)之走勢圖 ------------------ 27
圖4-4 MA 指標(24 日,48 日)之走勢圖 ------------------ 29
圖4-5 百米策略之走勢圖百米策略之走勢圖 --------------- 33
圖4-6 馬拉松策略之 ----------------------------------- 34
圖4-7 DIF 與MACD 之走勢圖 ---------------------------- 36
一、 中文部份
1. 王毓敏與黃瑞靜,2001,“價量關係-台股指數期貨市場之研究”,台灣金融財務季刊,第2 輯,第2 期,頁97-114。
2. 李文興,1996,期貨與選擇權,聯經。
3. 吳榮訓與廖高賢,2007,“價量關係-台股指數期貨市場之研究”,資訊管理學報,第14卷,第2期,頁111-138。
4. 杜金龍,1998,技術指標 : 在臺灣股市應用的訣竅,金錢文化。
5. 杜金龍,2005,技術分析入門,財訊。
6. 杜金龍,2007,杜金龍教室20堂投資必修課 : 台股選股與選時能力入門,智富文化。
7. 周建新與陳振遠,2002,“濾嘴法則操作績效與台灣期貨市場效率性之研究”,中國管理評論,第5卷,第4期,頁104-119。
8. 胡勝益,1998,投資理財:理論/策略/實務,大社會文化。
9. 許溪南與賴彌煥,2000,“權變投資組合保險在台灣股市之應用”,風險管理學報,第2卷,第2期,頁89-118。
10. 陶璀,2007,“用蒙特卡羅模擬方法檢驗RSI 指標的有效性”,金融經濟,第2007 卷,第8 期,頁114-115。
11. 黃光廷,2002,技術分析、基本分析與投資組合避險績效之研究,國立成功大學,碩士論文。
二、英文部分
1. Alexander, S. S., 1961, “Price Movement in Speculative Markets:Trends or Random Walks,” Industrial Management Review, pp.7-26.
2. Alexander, S. S., 1964, “Price Movements in Speculative Markets:Trends or Random Walks,” Industrial Management Review Vol.2, pp.25-46.
3. Appel, G., 1960, The Moving Average Convergence Divergence Trading Method. Signalert Corp, Great Neck, NY.
4. Appel, G. and W. F. Hitschler, 1979, Stock Market Trading System, South Carolina: Traders Press.
5. Armano, G., A. Murru and F. Roli, 2002, “Stock Market Prediction by a Mixture of Genetic-Neural Experts,” International Journal of Pattern Recognition and Artificial
Intelligence Vol.16, No.5, pp.501-526.
6. Bessembinder, H. and Chan, K., 1995, “The Profitability of Technical Trading Rules in the Asian Stock Markets,” Pacific-Basin Finance Journal, Vol.3, pp.257- 284.
7. Brock, W., J. Lakonishok, and B. LeBaron, 1992, “Simple Technical Trading Rules and the Stochastic Properties of Stock Returns,” Journal of Finance, Vol.47, pp.1731-1764.
8. Chan, W.S., and Y.K. Tse, 1993, “Price-Volume Relation in Stocks: A Multiple Time Series Analysis on the Singapore Market,” Asia Pacific Journal of Management,
39-56.
9. Chang, E. J., Eduardo José Araújo Lima and Benjamin Miranda Tabak, 2004, “Testing for Predictability in Emerging Equity Markets,” Emerging Markets Review,
Vol.5, No.3, pp.295-316
10. Dunis, C. L., Jason Laws and Ben Evans, 2006, “Trading Futures Spreads: An Application of Correlation and Threshold Filters,” Applied Financial Economics,
Vol.16, No.12, pp. 903-914.
11. Dunis, C. and Jia Miao, 2007, “Trading Foreign Exchange Portfolios with Volatility Filters: The Carry Model Revisited,” Applied Financial Economics, Vol.17, No.3, pp. 249-255.
12. Fama, E. and M. E. Blume, 1966, “Filter Rules and Stock Market Trading Profits,” Journal of Business, pp.226-241.
13. Gunasekarage, A. and D. M. Power, 2001, “The Profitability of Moving Average Trading Rules in South Asian Stock Market,” Emerging Markets Review, Vol.2,
pp.17-33.
14. Hurst, J. M., 1970, The Profit Magic of Stock Transaction Timing. Englewood Cliffs, N.J.: Prentice-Hall
15. Isakov, D.and M. Hollistein, 1999, “Application of Simple Technical Trading Rules to Swiss Stock Prices: Is It Profitable?” Financial Markets and Portfolio
Management, Vol.13, No.1, pp.9-26.
16. Jegadeesh, N. and S. Titman, 1993, “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency,” Journal of Finance,Vol.48, pp.65-91.
17. Lee, Chun I., Pan, Ming-Shiun and Liu, Y. Angela, 2001, “On Market Efficiency of Asian Foreign Exchange Rates: Evidence from a Joint Variance Ratio Test and Technical Trading Rules,” Journal of International Financial Markets, Institutions and Money, Vol.11, No.2, pp.199-214.
18. Levy, R.A., 1967, “Relative Strength as a Criterion for Investment Selection,” Journal of Finance, Vol. 22, pp.595-610.
19. Lindemann, A., C. L. Dunis and P. Lisboa, 2005, “Probability Distributions and Leveraged Trading Strategies: an Application of Gaussian Mixture Models to the Morgan Stanley Technology Index Tracking Fund,” Quantitative Finance, Vol. 5, No. 5, pp. 459-474.
20. Lisboa, P., C. L. Dunis and A. Lindemann, 2004, “Probability distributions, trading strategies and leverage: an application of Gaussian mixture models,” Journal of Forecasting, Vol.23, No.8, pp. 559-585.
21. Patel, C., 1980, Technical Trading Systems for Commodities and Stocks, Trading Systems Research, Walnut Creek, California.
22. Pring, M. J., 1985, Technical Analysis Explained. 2nd ed., N.Y.: McGraw-Hill.
23. Pruitt S.W. and White, R.E., 1988, “The CRISMA trading System: Who Says Technical Analysis can’t Beat the Market ? ” Journal of Portfolio Management, Vol.14, Spring, pp.55-58.
24. Sweeney, R. J., 1988, “Some New Filter Rule Tests: Methods and Results,” Journal of Financial and Quantitative Analysis, Vol. 23, No.3, pp.285-300.
25. Thomas C. S. and T. T. L. Chong, 2007, “A comparison of MA and RSI returns with exchange rate intervention,” Applied Economics Letters, Vol.14, No.5-6, pp.371-383.
26. Wilder, J. W., 1978, New Concepts in Technical Trading Systems. New York: Trend Research.
27. Wong, W. K., M. Manzur and Chew, B. K., 2003, “How Rewarding is Technical Analysis? Evidence from Singapore Stock Market,” Applied Financial Economics, Vol.13, No.7, pp.543-551.
28. Wong, W. K., J. Du and T. T. L. Chong, 2006, “Do the Technical Indicators Reward Chartists in Study on the Stock Markets of Chinese Mainland, Hong Kong and Taiwan?” China Journal of Finance, Vol.11, pp.1-25.
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