臺灣博碩士論文加值系統

本研究主要探討公司規模及資訊之揭露程度對技術分析獲利性之影響。呂宜峰(2004)之研究中呈現”公司規模可解釋整體資訊之揭露程度”,故本研究以台灣上市公司中最大與最小市值兩組不同公司規模樣本作比較，看技術分析在不同公司規模之獲利表現。主要研究方法係採用Brock, Lakonishok, and Lebaron(1992)一天期平均線，並根據Metghalchi, Chang, and Marcucci(2007) 之採用50,100,150,200天期移動平均線，利用區間突破交易法則(Trading Range Break-out rules,TRB)，當短天期平均線超過長天期平均線的1.01倍時，出現交叉向上的現象，代表買入訊號，反之當短天期平均線跌破長天期平均線的0.99倍時，出現交叉向下的現象，代表賣出訊號，探討投資人運用移動平均線之技術分析法則投資於台灣上市公司高總市值股票（20 檔）及低總市值股票（20檔）是否具有獲利能力。實證結果顯示，低總市值股票買入日報酬運用100天,150天及200天期移動平均線之獲利表現優於高總市值股票，也就是說，小規模公司之資訊揭露程度較低，投資人於從事投資買入決策時，可藉由移動平均線法則獲得較佳報酬，另無論是高市值或低市值之股票族群皆是買入日較賣出日有較佳的報酬，且幾乎能擊敗買入持有策略，賺取超額報酬。
卓越預測能力(SPA)測試結果，無論高總市值股票或低總市值股票皆可藉由長天期移動平均線法則獲得超額報酬並打敗買進持有策略。本研究實證結果並不支持台灣上市公司為弱式效率市場，採技術分析仍有其參考價值。

This research addresses the effect of firm size and information dissemination on the profitability of technical analysis. We study the profitability of technical trading for the samples of the 20 largest and 20 smallest listed firms in Taiwan Stock Exchange. Our research methodology uses trading range break-out rules combing 1-day moving average of Brock, Lakonishok, and Lebaron (1992) and 50-day, 100-day, 150-day, and 200-day moving averages of Metghalchi, Chang, and Marcucci (2007). The empirical evidence shows that the profitability of trading rules of (1, 100), (1, 150), and (1,200) is larger for the firms with smallest firm size than those with largest firm size. The implications provide that the degree of information dissemination is lower for small firms so that investors gain higher returns by using technical trading analysis. Furthermore, we find that the returns of buy-days are higher than those of sell-days and they also beat the buy-and-hold returns. Finally we employ Superior Predictive Ability tests to rank the profitability of technical trading. The results shows that longer period moving average trading rules perform better than shorter period moving average trading rules. This research also presents that the weak-form market efficiency is not supported for Taiwan stock markets.

第一章、前言 1
第一節、研究背景與動機 1
第二節、研究目的 5
第三節、研究架構和流程 6
第二章、文獻回顧 7
第三章、研究資料與方法 12
第一節、資料說明 12
第二節、研究方法 12
第三節、卓越預測能力(Superior Predictive Ability,SPA) 14
第四章、實證結果與分析 16
第一節、樣本之敘述統計量 16
第二節、實證結果 19
第五章、結論 22
參考文獻 24
ㄧ、國內文獻 24
二、國外文獻 26
三、參考網站 31

ㄧ、國內文獻
方國榮（1991），「證券投資最適指標之研究：技術面分析」，國立台灣大學商學研究所碩士論文。
呂宜峰（2004），「資訊揭露程度與公司特徵之關聯性研究-以國內IC相關產業為例」，中國文化大學會計研究所碩士論文。
杜金龍（1998），「技術指標在台灣股市應用的訣竅」，金錢文化出版有限公司。
李淑惠，2006，技術分析指標與股價漲跌非線性關係之獲利能力之探討，台灣管理學刊，第六卷，第一期，129-156頁。
李良俊(2003)，台灣股票市場技術分析有效性之研究，實踐大學企業管理研究所未出版之碩士論文。
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之碩士論文。
林金賢，李淑慧(2006)，技術指標與股價漲跌幅非線性關係之獲利能力之探討，台灣管理學刊，6(1)，129-156。
林俊宏(2006)，成交量對技術分析指標在期貨市場操作績效之影響，國立交通大學管理科學研究所未出版之碩士論文。
林才熙（1990），「以技術分析方法之獲利性檢定台灣股市之弱勢效率－CRISMA交易系統之研究」，國立台灣大學商學研究所碩士論文。
林宗永（1989），「證券投資技術分析指標獲利性之實證研究」，國立政治大學企業管理研究所碩士論文。
洪美惠（1996），「技術分析應用台灣股市之研究－移動平均線、乖離率指標與相對強弱指標之研究」，東海大學管研所碩士論文。
高梓森（1994），「台灣股市技術分析之實證研究」，國立台灣大學財務金融研究所碩士論文。
高展偉(2005)，開盤八法應用於台灣期貨市場之實證研究，朝陽大學財務金融研究所未出版之碩士論文。
徐俊明(2004)，投資學原理(3版)，台北：新陸書局。
陳建全（1998），「台灣股市技術分析實證研究」，國立台灣大學商學研究所碩士論文。
陳正榮（2001），「以濾嘴法則檢驗台灣股票市場弱勢效率性之研究」，國立高雄第一科技大學財務管理研究所碩士論文。
陳信宏，陳昱志，鄭舜仁，2006，以時間數列模型檢定台灣股票市場弱勢效率性之研究，管理科學與統計決策，3(4)，8-17。
黃光廷，2002，技術分析、基本分析與投資組合避險績效之研究，國立成功大學會計學研究所未出版之碩士論文。
黃彥聖(1995)，移動平均法的投資績效，管理評論，14(1)，47-68。 董茲莉(1995)，由技術分析效果驗證我國股市效率性，國立中山大學企業管理研究所未出版之碩士論文。
楊基鴻(1994)，股票操作大全，新店市：產經日報社股份有限公司。
楊家維(2000)，技術分析應用於當沖之有效性研究－台灣股市之實證分析，國立台北大學經濟學研究所未出版之碩士論文。
葉日武（1987），「以技術分析研判股票市場進出時機之效果」，國立政治大學企業管理研究所碩士論文。趙永昱，2002，技術分析交易法則在股市擇時之實證研究，國立中山大學財務管理學系碩士在職專班論文。
趙永昱(2002)，技術分析交易法則在股市擇時之實證研究，國立中山大學財務管理學研究所未出版之碩士論文。
蔡宜龍(1990)，台灣股票市場技術分析有效性之衡量，國立成功大學工業管理研究所未出版之碩士論文。
盧廷當（1996），「以參考成交量之濾嘴法則檢定資本市場之弱勢效率性－台灣股票市場之實證研究」，國立交通大學管理科學研究所碩士論文。
謝政遠，2004，以移動平均線、相對強弱指標與成交量檢驗台灣股票市場的效率性，逢甲大學財務金融研究所未出版之碩士論文。
賴虹霖(2009)，技術分析之獲利能力：以美元投資全球股市之探討，東海大學管理學院財務金融研究所之碩士論文。
簡辰丞(2001)，結合MACD與類神經模糊技術之股票預測模型－以台灣金融股為例，靜宜大學企業管理研究所未出版之碩士論文。

二、國外文獻
Alexander, S. S., 1961, Price Movement in Speculative Markets:Trends or Random Walks, Industrial Management Review,2, 7-26
Alexander, S. S., 1964, Price Movements in Speculative Markets: Trends or Random Walks,No.2, Industrial Management Review,5,25-46.
Allen, F., and R. Karjalainen, 1999, Using Genetic Algorithms to Find Technical Trading Rules, Journal of Financial Economics,51,245-271.
Andrada-Felix, J. and Fernandez-Rodriguez, F., 2008, Improving Moving Average Trading Rules with Boosting and Statistical Learning Methods, Journal of Forecasting ,27, 433-449
Bessembinder, H., and Chan, K., 1995, The profitability of technical trading rules in the Asian stock markets, Pacific-Basin Finance Journal,3, 257-284.
Brock, W., J. Lakonishok, and B. LeBaron, 1992, Simple Technical Trading Rules and the Stochastic Properties of Stock Returns, Journal of Finance, 47,1731-1764.
Brown, S. J., W. N. Goetzmann, and A. Kumar,1988, The Dow Theory: William Peter Hamilton’s Track Record Reconsidered, Journal of Finance,53,1311-1333.
Chan, K., A. Hameed, and W. Tong, 2000, Profitability of Momentum Strategies in the International Equity Markets, Journal of Financial and Quantitative Analysis,35,153-172.
Chan, L. K. C., N. Jegadeesh, and J. Lakonishok, 1996, Momentum Strategies, Journal of Finance, 51, 1681-1713.
Chan, L. K. C., N. Jegadeesh, and J. Lakonishok, 1999, The Profitability of Momentum Strategies, Financial Analysts Journal ,55, 80-90.
Chang, E. J., Lima, E. J. A. and Tabak, B. M., 2004, Testing for Predictability in Emerging Equity Markets, Emerging Markets Review,5, 295-316.
Chang, P. H. K., and C. L. Osler, 1999, Methodological Madness: Technical Analysis and the Irrationality of Exchange-Rate Forecasts, Economic Journal,109,636-661.
Conrad, J. and Kaul, G.., 1988, Time-Variation in Expected Returns, Journal of Business,61, 409-25.
Cootner, P. H., 1962, Stock Price : Random Walk vs Systematic Changes, Industrial Management Review,3, 24-45.
Coutts, J. A. and Cheung, K. C., 2000, Trading Rules and Stock Returns: Some Preliminary Short-Run Evidence from The Hang Seng 1985-1997, Applied Financial Economics,10, 579-586.
Culter,D.M., J.M. Poterba and L.H. Summers, 1991, Speculative Dynamics, Review of Economic Studies,58, 529-546
Dooley, M. P., and J. R. Shafer., 1984, Analysis of Short-Run Exchange Rate Behavior: March 1973 to November 1981. Floating Exchange Rates and the State of World Trade Payments, 43-69, Cambridge, Mass: Harper & Row, Ballinger.
Edwards, R. D. and Magee, J., 1966, Technical Analysis and Stock Trends.
Fama, E. F., 1965, The Behavior of Stock Market Prices, Journal of Business, 33, 34-105.
Fama, E. F., 1970, Efficient Capital Markets: A Review of Theory and Work, Journal of Finance,25, 383-417.
Fama, E. and French, K.,1988, Dividend Yields and Expected Stock Return, Journal of Finance, 3-26.
Fama, E. F., and M. E. Blume, 1966, Filter Rules and Stock-Market Trading, Journal of Business,39, 226-241.
Fang, Y. and Xu, D.,2003, The Predictability of Asset Returns: An Approach Combining Technical Analysis with Time-Series Forecasts, International Journal of Forecasting,19, 369-385.
Forst, A. J. and R. R. prechter, 1978, Elliott Wave Principle, Key to Stock Market Profits, Chappaqua, NY: New Classics, Library.
Gencay, R., 1998, The Predictability of Security Returns with Simple Technical Trading Rules, Journal of Empirical Finance,5, 347-359.
Granville, J., 1963, Granville’s New Key to Stock Market Profits, Prentice Hall, Englewook cliff, NJ.
Gunasekarage, A. and Power, D. M., 2001, The Profitability of Moving Average Trading Rules in South Asian Stock Markets, Emerging Markets Review,2, 17-33.
Hansen, P.R., 2005, A Test for Superior Ability., Journal of Business & Economic Statistics, American Statistical Association,23,364-380.
Hsu, P. and C. Kuan, 2005, Reexamining the Profitability of Technical Analysis with Data Snooping Checks, Journal of Financial Econometrics,3, 606-628.
Hudson, R., Dempsey, M., and Keasey, K., 1996, A Note on The Weak form Efficiency of Capital Markets: The Application of Simple Technical Trading Rules to UK Stock Price---1935 to 1994, Journal of Banking & Finance,20, 1121-1132.
Ito, A., 1999, Profits on Technical Trading Rules and Time-Varying Expected Returns: Evidence from Pacific-Basin Equity Markets, Pacific-Basin Finance Journal,7, 283-330.
James, F. E., 1968, Monthly Moving Averages-An Effective Investment Toll, Journal of Financial and Quantitative Analysis, September, 315-326.
Jagadeesh, N. and Titman, S., 2001, Profitability of Momentum Strategies: An Evaluation of Alternative Explanations, Journal of Finance,56, 699-720.
Jensen, M. C., 1967, Random Walks: Reality or Myth-Comment, Financial Analysts Journal,23, 77-85.
Jensen, M. C., and G. Bennington, 1970, Random Walks and Technical Theories: Some Additional Evidences, Journal of Finance,25, 469-482.
Kwon, K.-Y. and kish, R.J.,2002, Technical Trading Strategies and Return Predictability:NYSE, Applied Financial Economics,12, 639-653.
Lai, M.-M., Balachandher, K. G., et al., 2002, 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.
Leuthold, R. M., 1972, Random Walk and Price Trends: The Live Cattle Futures Market. The Journal of Finance, 27, 879-889.
Levish, R. M., and L. R. Thomas., 1993, The Significance of Technical Trading Rule Profits in the Foreign Exchange Market: A Bootstrap Approach. Journal of International Money and Finance,12, 451-474.
Levy Robert A., 1967, Relative Strength as a Criterion for Investment Selection, Journal of Finance,22, 595-610
Lo, A. W., H. Mamaysky, and J. Wang, 2000, Foundations of Technical Analysis: Computation Algorithm, Statistical Inference, and Empirical Implementation, Journal of Finance,55, 1705-1765.
Loh, E., 2005, Profiting from Moving Averages and Time-Series Forecass: Asian-Pacific Evidence, Asia Pacific Journal of Economics and Business,9, 62-82.
Metghalchi, M., Y.H. Chang, and J. Marcucci, 2007, Is the Swedish Stock Efficient Evidence from Some Simple Trading Rules, International Review of Financial Analysis,17, 475-490.
Neely, C. J., and P. Weller,1999, Technical Trading Rules in the European Monetary System, Journal of International Money and Finance,18, 429-458.
Neely, C. J., P. Weller, and R. Dittmar, 1997, Is Technical Analysis in The Foreign Exchange Market Profitable A Genetic Programming Approach, Journal of Financial Quantitative Analysis,32, 405-426.
Patel, C.,1980, Technical Trading Systems for Commodities and Stocks, Trading Systems Research, Walnut Creek, California.
Pruitt, S. W. and R. E. White,1988, The CRISMA Trading System: Who Says Technical Analysis Can’t Beat the Market, Journal of Portfolio Management,55-58
Ratner, 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.
Raj, M. and D. Thurston, 1996, Effectiveness of Simple Technical Trading Rules in the Hong Kong Futures Markets, Applied Economics Letter,3, 32-36.
Rouwenhorst, K. G., 1998, International Momentum Strategies, Journal of Finance,53, 267-284.
Solt, M. E., and P. J. Swanson.,1981, On the Efficiency of the Markets for Gold and Silver. Journal of Business,54, 453-478.
Kakani, R.K. and Sundhar, S.,2006, Working Paper.
Sweeney, R. J., 1986, Beating the Foreign Exchange Market, Journal of Finance, 41, 163-182.
Sweeney, R. J., 1988, Some New Filter Rule Tests: Methods and Results, Journal of Financial and Quantitative Analysis,23, 285-300.
Szakmary, A., Davidson III, W. N. and Schwarz, T. V., 1999, Filter Tests in Nasdaq Stocks, Financial review,34, 45-70.
Tian, G. G., Wan, G. H. and Guo, M. Y., 2002, Market Efficiency and The Returns to Simple Technical Trading Rules: New Evidence from Us Equity Market and Chinese Equity Markets, Asia-Pacific Financial Markets,9, 241-258.
Van Horne, J. C., and G. G. C. Parker, 1967, The Random Walk Theory: An Empirical Test, Financial Analysts Journal,23, 87-92.
Wong W. K., M. Manzur, M. and Chew, B. K., 2003, How Rewarding Is Technical Analysis Evidence from Singapore Stock Market, Applied Financial Economics,13, 543-551.