臺灣博碩士論文加值系統

　　本研究係以每日股票市場行情來建立型態辨識函數。所取樣本為2000/1/1 至2008/3/31 的摩根概念股及中國概念股，以EXCEL 軟體為研究工具進行函數開發，對辨識函數所辨識出之K 線型態進行頻次及報酬的彙總分析。並參考Caginalp and Laurent(1998)對趨勢的定義方法，適當的設計樣本後續走趨條件，然後使用卜瓦松分配進行檢
定，探討其K 線型態在台灣股票市場是否含有意義。本研究所得之結論為：
1.在電子股中，看漲型態「白三兵」及「外側三紅」出現，後續五日平均皆出現正報酬，依該型態做進場動作可獲得正報酬。而「內困三黑」型態出現則應做出場的動作。
2.本研究在類股中，「晨星」及「夜星」只出現在電子股，即後續價格趨勢會和原趨勢相反。個股中的「晨星」則具有反轉效力，而「夜星」只有摩根概念股才有反轉效力。
3.無論在類股或個股中，「白三兵」、「外側三紅」、「內困三黑」及「外側三黑」四種型態的出現，並不具有反轉意義，即後續價格趨勢並不受影響。
4.本研究的個股實證結果「白三兵」是不具反轉意義，此和Caginalp and Laurent(1998)實證結果認為「白三兵」有反轉意義之結論不同。
5.本研究的摩根概念股實證結果「晨星」是具有反轉意義，此和陳蕾如(2004)之個股實證結果「晨星」不具反轉意義之結論不同。

　This research sought to develop the functions for Candlestick Patterns based on the daily stock market performance, sampling from the Morgan Concept Stock and the Chinese Concept Stock between 2000/1/1 and 2008/3/31. EXCEL software was used as the tool to analyze the the frequency of occurrence and potential rewards of the Candlestick Patterns. This study adopted the trend definitions from Caginalp and Laurent’s method (1998). A Poisson distribution-based approach was also used to examine and test whether Candlestick Patterns have predictive power in the Taiwan stock market. This research concludes as follows:

　First, for the electronic sector, "Three White Soldiers" and "Three Outside Up” anticipate a rising. When the following daily averages for five days all appear the positive reward, according to that patterns, purchasing can generate the reward. However, when " Three Inside Down " appears, doing the opposite is more proper.

　Second, only "Morning Star" and "Evening Star" appear in the electronic stocks, that is, the price trends after these signals appear tend to reverse.. "Morning Star" has reversal effect on the Morgan Concept Stock and the Chinese Concept Stock, but only "Evening Star" has the reversal effect on the Morgan Concept Stock.

　Third, no significant trend reversal occurs for "Three White Soldiers", "Three Outside Up", "Three Inside Down" and "Three Outside Down".

　Fourth, "Three White Soldiers" doesn''t predict trend reversal for neither the Morgan Concept Stocks nor on the Chinese Concept Stocks, which differs from the results reported by Caginalp and Laurent (1998) .

　Fifth, this study finds that the "Morning Star" predicts trend reversal for the Morgan Concept Stocks, which differs from the conclusion reached by Chen (2004).

第一章 緒論1
第一節 研究動機1
第二節 研究目的2
第三節 研究範圍3
第四節 研究方法4
第二章 文獻探討6
第一節 技術分析理論6
第二節 日本K 線理論13
第三節 卜瓦松分配17
第三章 型態函數20
第一節 日本K 線圖20
第二節 K 線型態辨識函24
第三節 K 線型態統計34
第四章 實證結果與分析39
第一節 樣本說明與研究方法39
第二節 型態K 線資訊內涵43
第三節 K 線型態資訊彙整51
第五章 結論及建議56
第一節 結論56
第二節 建議57

一、英文文獻
[1]Alexander, Sindey. S.(1961), Price Movements in Speculative Markets: Trends or Random Walks, in P. Cootner, ed. The Random Character of Stock Market Price , 199-218.
[2]lexander, Sindey. S. (1964), Price Movements in Speculative Markets：Trends or Random Walks ,No. 2, in P. Cootner, ed The Random Character of Stock Market Prices (MIT Press, Cambridge, Mass), 338-372.
[3]nand, S., and Chin, W., N., and Khoo, S., C.(2001), Charting Patterns on Price History, National University of Singapore.
[4]Brock,William, Joseph Lakonishok, and Blake LeBaron(1992), Simple technical trading rule and the stochastic properties of stock returns, Journal of Finance, 47,1731-1764.
[5]BenZion, U., P. Klein, Y. Shachmurove and J. Yagil (2001), Efficiency differences between the S&P 500 and Tel-Aviv 25 indices: A moving average comparison, Working paper, University of Ben-Gurion.
[6]Caginalp, G. and Laurent, H(1998), The Predictive Power of Price Patterns, Applied Mathematical Finance, 5, 181-205.
[7]Coutts J., and K. C. Cheung(2000), Trading Rules and Stock Return: Some Preliminary Short Run Evidence from The Hang Seng 1985-1997, Applied Financial Economics, 579-586.
[8]Chang, P. H. K. and Osler (2000), Methodical Madness: The Head-and-Shoulders Pattern in Foreign Exchange, Economic Journal. 636-661.
[9]Chu, J., and Osler, C.,L.(2003), Identifying Noise Traders: The Head-and-Shoulders Pattern In U.S. Equities. Federal reserve bank of NEW YORK.
[10]Dempster, M., A., H. and Jones, C., M.(1998), Can Technical Pattern Trading Be Profitably Automated?2.The Head & Shouldersl, University of Cambridge.
[11]Dong, M. and Zhou, X., S. (2000), Analyzing visual technical patterns- a neural network based saliency analysis, IEEE 2000, 1-5.
[12]Dong, M. and Zhou, X., S. (2002), Exploring the fuzzy nature of technical patterns of U.S. stock market, IEEE 2000.
[13]Dunis C. L. and J. Miao (2005), Optimal trading frequency for active asset management: Evidence from technical trading rules, Journal of Asset Management, 5, 305-326.
[14]Edwards, R. D. and J. Magee (1997), Technical Analysis of Stock Trends, 7th edition, AMACOM, N.Y., N.Y., 3-7.
[15]Edwards R. D. and James M. S.(2003), On the Existence of Visual Technical Patterns in the UK Strock Market, Journal of Business Finance & Accounting, 30,263-293.
[16]Gunasekaragea, A. and D. M. Power (2001), The profitability of moving average trading rules in South Asian stock markets, Emerging Markets Review, 2, 17-33.
[17]Hudson, R., M. Dempsey and K. Keasey (1996), A note on the weak from efficiency of capital markets: The application of simple technical trading rules to UK stock prices-1935 to 1994, Journal of Banking and Finance, 20, 1121-1132.
[18]Hsu, P. H. and C. M. Kuan (2005), Reexamining the profitability of technical analysis with data snooping checks, Journal of Financial Econometrics, 3, 606-628.
[19]Kwon, K.,Y. and Kish, R., J(2002), A Comparative Study of Technical Trading Strategies and Return Predictability: [20]An Extension of Brock, Lakonishok, and LeBaron(1992) Using NYSE and NASDAQ Indices, The Quarterly Review of Economics and Finance, 42, 611-631.
[21]Lee, K.H., Jo, G..S.(1999), Expert System for Predicting Stock Market Timing Using a Candlestick Chart, Expert Systems with Applications, 16(4), 357-364.
[22]Lo, A.W, H. Mamaysky, and J. Wang(2000),Foundations of technical analysis: computational algorithms, statistical inference, and empirical implementation, Journal of Finance, 55, 1705-1765.
[23]Leigh, W., and Modani, N., and Purvis, R., and Roberts, T.(2002), Stock Market Trading Rule Discovery Using Technical Charting Heuristics, Expert systems with applications, 23, 155-159
[24]Leigh, W., and Paz, M., and Purvis, R.(2002), An Analysis of a Hybrid Neural Network and Pattern Recognition Technique for Predicting Short-term Increases in the NYSE Composite Index, The international journal of management science, omega 30, 69-76.
[25]Leigh, W., and Paz, M., and Purvis, R.(2002), Market Timing: a Test ofA Charting Heuristic, Economics Letters, 77, 55-63.`
[26]Leigh, W., and Purvis, R., and Ragusa, J., M.(2002), Forecasting the NYSE Composite Index With Technical Analysis, Pattern Recognizer, Neural Network, and Genetic Algorithm: a Case Study In Romantic Decision Support, Decision Support Systems, 32,361-377.
[27]Lai, M. M., K. G. Balachandher and F. M. Nor (2003), An examination of the random walk model and technical trading rules in the Malaysian stock market, Quarterly Journal of Business and Economics, 41, 81-104.
[28]Mandelbrot, B.(1963), The variation of certain speculative prices, J.Business, 36, 392.
[29]Murphy, J. J. (1986), Technical analysis of the futures markets: A comprehensive guide to trading methods and applications, 1st edition, New York Institute of Finance, N.Y., 1-7.
[30]Markov, D.(2002), Information content in stock market technical patterns: a spline regression approach, university of Notre dame, Indiana.
[31]Morris (2006), Candlestick Charting Explained: Timeless Techniques for Trading Stocks and Futures(3st ed.), McGraw-Hill Professional.
[32]Nison, S.(1991), Japanese Candlestick Charting Techniques, New York, NY: New York Institute of Finance.
[33]Neftci, S. N.(1991), Naïve Trading Rules in Financial Markets and Weiner-Kolmogorov Prediction Theory: A Study of Technical Analysis, Journal of Business, 64, 549-571.
[34]Ranter, M., and Leal, R. P. C. (1999), Test of technical trading strategies in the emerging equity markets of Latin America and Asia, Journal of Banking and Finance, 23, 1887-1905.
[35]Roberts, M. C. (2002), The Value of Technical Analsis, The Ohio State University.
[36]Szakmary, A. N., W. N. Davidson and T. V. Schwarz (1999), Filter tests in Nasdaq stocks, The Financial Review, 34, 45-70.
[37]Thomas N. Bulkowski, Encyclopedia of Chart Patterns, New York: John Wiley&Sons, Inc., 2000
[38]Tian, G., G. H. Wan and M. Guo (2002), Market efficiency and the returns to simple technical trading rules: New evidence from U.S. equity market and Chinese equity markets, Asia-Pacific Financial Markets, 9, 241-258.

二、中文文獻
[1]安芷誼(2005)，技術分析對台灣股票市場投資績效之探討－移動平均線法，銘傳大學國際企業學系碩士在職專班未出版碩士論文。
[2]吳德生(2005)，技術分析對香港股市有效性之探討－以KD、MACD、MA、RSI 為技術指標，國立台北大學企業管理研究所碩士論文。
[3]杜金龍(2006)，最新技術指標在台灣股市應用的訣竅（三版），台北：財訊出版社。
[4]林惠玲、陳正倉(2006)，應用統計學（三版），台北：雙葉出版社。
[5]林天運(2007)，大盤未來走勢預測- KD 指標的實證分析，國立成功大學國際企業研究所未出版碩士論文。
[6]姚庭俊(2003)，K線理論對股價預測能力之研究，中山大學企業管理研究所在職班未出版碩士論文。
[7]韋月桂(2003)，台灣期貨市場交易策略之研究，台灣大學財務金融研究所碩士論文。
[8]徐坤豪(2005)，運用K 線、KD 指標於台股指數期貨效果之研究，東吳大學會計學研究所碩士論文。
[9]徐俊明(2005)，投資學理論與實務（五版），台北：新陸書局股份有限公司。
[10]徐清俊、郭敏吉(2007)，中國概念股股價與投資績效之研究，遠東學報，26(3)，233-248。
[11]陳文魁(2004)，金融特殊投資策略-陰陽線新注解（初版），台北：寰宇出版社。
[12]陳映廷(2007)，濾嘴法則與乖離率是否可以獲取超額報酬？－以台灣50指數型基金為例，中興大學財務金融研究所未出版碩士論文。
[13]陳蕾如(2004)，K線與型態辨識函數之開發及技術分析之應用，義守大學財務金融研究所未出版碩士論文。
[14]黃文宏(2004)，技術分析在台灣股票市場之實證研究，國立雲林科技大學財務金融系未出版碩士論文。
[15]黃韋中(2006)，主控戰略即時盤態（初版），台北：寰宇出版股份有限公司。
[16]黃嘉斌譯(2004)，陰陽線詳解（初版），台北：寰宇出版社。（譯自Martin J. Pring, 2004）。
[17]楊銘(1998)，中國概念投資總覽（初版），台北：財訊出版社。
[18]葉建佑(2004)，技術分析法則之績效研究－美國個股之實證，中興大學財務金融研究所未出版碩士論文。
[19]趙永昱(2002)，技術分析交易法則在股市擇時之實證研究，中山大學財務管理學系研究所碩士論文。
[20]蔣岡霖(2000)，應用股價技術圖型比對分析預測未來股價趨勢，大葉大學事業經營研究所未出版碩士論文。
[21]蔡尚儒(2000)，台灣店頭市場技術分析的實證研究，中正大學財務金融研究所碩士論文。
[22]蔡幸雄(2004)，K線變株（初版），蔡幸雄。
[23]蔡斌仕(1995)，台灣股市技術分析之實證研究，台灣大學財務金融研究所碩士論文。
[24]魯秉鈞(2001)，技術分析於臺灣股票市場的應用，東海大學管理研究所碩士論文。
[25]寰宇財務顧問公司譯(1997)，強力陰陽線（初版），台北：寰宇出版社。（譯自Gregory L. Morris,1994）。
[26]寰宇證券投資顧問公司譯(1999)，股票Ｋ線戰法（初版），台北：寰宇出版社。（譯自Steve Nison,1997）。
[27]謝劍平(2002)，現代投資學（再版），台北：智勝文化事業。
[28]鍾文翔(2006)，線形玄機（初版），台北：寰宇出版股份有限公司。
[29]羅仙法、蘇玄啟(2006)，移動平均線交易策略在台灣股票市場之應用，2006現代財務論壇學術研討會論文集，台中，2006年04月28日。
[30]鐘淳豐(2001)，配合價量關係技術型態在台灣股票市場的應用，政治大學財務管理研究所碩士論文。