臺灣博碩士論文加值系統

本研究以全球指數現貨與指數期貨兩市場的訊號做指數現貨交易，並使用技術分析法則檢定兩訊號之獲利性，研究立論於Brock, Lakonishok,and LaBaron(1992)之移動平均線法則，採用3 種長天期移動平均線(50,100,150)與1 天期短期平均線。實證結果顯示技術分析交易法則有顯著預測能力以獲取超額報酬，多數國家在這3 種交易法則下，指數期貨之獲利性會顯著地優於指數現貨。且全球20 個國家在指數現貨(1,150)交易法則之獲利性優於買進持有策略，證明市場並非弱式效率市場假說，技術分析有效。2004-2008 年與 2009-2013 年子樣本結果與全樣本結果一致。最後本研究採用Hansen(2005)之卓越預測能力(SPA)對交易策略做強度測詴，發現多數國家最佳預測交易策略為(1,150)交易法則，投資人可以利用(1,150)交易法則去獲取超額報酬。

This study applies two signals, which are global stock index and futures index, on stock index trading and tests the profitability with technical trading rule. Our methodology is based on moving average rules of Brock, Lakonishok and LaBaron(1992), and use three kinds of long-day moving average rules(50,100,150) and one-day-short-day moving average rule. The empirical results show that technical trading analysis rules have significantly profitability ability to obain abnormal return. In most countries, we find futures index return more significant than stock index return by three moving average rules. Furtherrmore, the profit of 20-country global stock index (1,150) trading rules is better than buy-and-hold strategy. This proves that the market does not follow the weak-form efficient market hypothesis, and that technical analysis is effective. The results in subsamples of year 2004 - 2008 and year 2009-2013 are consistent with the results in the full sample. Finally, we adopt Hansen(2005) Superior Predictive Ability to test the best realistic predictive rule, and we find that most countries have best predictive trading rules in the (1,150) trading rules. Accordingly, it is suggested that investors can use the (1,150) trading rules to obtain abnormal return.

第一章、 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 2
第三節 研究結構與流程 3
第二章、 文獻回顧 5
第一節 效率市場假說 5
第二節 技術分析之相關文獻 6
第三章、 研究資料與方法 11
第一節 研究資料 11
第二節 研究方法 11
第三節 移動平均線法則之報酬計算與報酬檢定方法 12
第四節 卓越預測能力(Superior Predictive Ability,SPA) 13
第四章、 實證結果與分析 16
第一節 敘述統計量 16
第二節 實證結果 16
第五章、 結論 22
參考文獻 24
附錄 28

魏嘉君(2008)，「技術分析指標之獲利能力:已開發國家與開發中國家整合探討」，東海大學財務金融研究所碩士論文。

洪美慧(1997)，「技術分析應用於台灣股市之研究－移動平均線、乖離率指標與相對強弱指標之評估」，東海大學管理研究所碩士論文。

程定國(2009)，「短中長期技術面整合策略之研究」，臺灣大學企業管理碩士專班學位論文。

李淑惠(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，第6 卷，第1 期，頁129-156。

Bessembinder, H. and Chan, K., 1995, The Profitability of Technical Trading Rules in the Asian Stock Markets, Pacific-Basin Finance Journal, 257-284.

Brock W., J. Lakonishok, and B. LeBaron, 1992, Simple Technical Trading Rule and the Stochastic Properties of Stock Return, Journal of Finance, 41, 1731-1764.

Coutts J. Andrew and Cheung Kwong-C, 2000, Trading Rules and Stock Returns: Some Preliminary Short Run Evidence from the Hang Seng 1985-1997, Applied Financial Economics, 579-586.

Coutts, J.A., Cheung K.C. (2000),“ Trading Rules and Stock Returns：Some Preliminary Short Run Evidence From The Hang Seng 1985-1997 ”, Applied Financial Economics, October, 579-586.

Cootner, Paul H, 1964, Stock Market Price: Random versus System Change, Industrial Management Review, 3, 24-25.

Fama, E. F., 1965,“The Behavior of Stock-Market Prices”, The Journal of Business, 34-105.

Fama, E. F.and M. E. Blume, 1966, “Filter Rules and Stock-Market Trading.” Journal of Business, vol.39, 226-241.

Fama, E. F., 1970 , “Efficient Capital Markets： A Review of Theory and Empirical Work.” Journal of Finance , vol. 25, No.2, 383-417.

Gunasekarage, Abeyratna , and David M. Power , 2001, “The Profitability of Moving Average Trading Rules in South Asian Stock Markets”,Emerging Markets Review, 2001, Vo1.2 ,17-33.

Hansen, P. R., 2005, A Test for Superior Predictive 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.

Kwon K.Y. and Kish R.J, 2002, “A Comparative Study of Technical Trading Strategies and Return Predictability: An Extension of Brock, Lakonishok and LeBaron, 1992, Using NYSE and NASDAQ Indices”, the Quarterly Review of Economics and Finance, 42 ,611-631.

LeBaron, B., 1998, Technical Trading Rules and Regime Shifts in Foreign Exchange, In: Acar, F., Satchell, S. (Eds.), Advanced Trading Rules. Butterworth-Heinemann, 5-40.

Metghalchi, M., Y.H. Chang, and J. Marcucci, 2007, Is the Swedish Stock Market Efficient? Evidence from Some Simple Trading Rules, International Review of Financial Analysis, 475-490.

Pruitt , Stephen W. , Richard 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 R.P.C. Leal , 1999, "Tests of technical trading strategies in the emerging equity markets of Latin America and Asia." Journal of Banking and Finance 23(12): 1887-1905.

Sweeney, R.J., 1990, Evidence on Short-term Trading Strategies, The Journal of Portfolio Management, Fall, 20-26.

Szakmary, Andrew N., Wallace N. Davidson III, and Thomas V. Schwarz , 1999,"Filter Tests In Nasdaq Stocks." The Financial Review 34(1): 45-70.

Van Horne, Jams C. and Parker, George G.. C, 1967, Technical Trading Rules: A Comment, Financial Analysts Journal, 35, 28-132.

White, H., 2000, A Reality Check for Data Snooping, Econometrica, 64, 1067-1126.

Wong W. K., M. Manzur, and B. K. Chew, 2003, How Rewarding Is Technical Analysis? Evidence from Singapore Stock Market, Applied Financial Economics, 13, 543-551.