跳到主要內容

簡易檢索 / 詳目顯示

研究生: 鐘以恂
Chung, Yi Hsun
論文名稱: 應用MACD及RSI為技術指標於台灣加權指數、日經225及香港恆生指數
Testing Moving Average Convergence / Divergence and Relative Strength Index on Hang Seng Index, Nikkei 225 and Taiwan Capitalization Weighted stock Index
指導教授: 山本竜市
Ryuichi Yamamoto
學位類別: 碩士
Master
系所名稱: 商學院 - 國際經營與貿易學系
Department of International Business
論文出版年: 2013
畢業學年度: 101
語文別: 英文
論文頁數: 47
中文關鍵詞: 技術指標
相關次數: 點閱:226下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 近年來,投資者在交易時所使用的技術指標越來越琳琅滿目。本研究探討MACD (Moving Average Convergence / Divergence) 以及 RSI (Relative Strength Index) 兩種技術指標,並利用香港恆生指數、日經225指數以及台灣加權指數1970年到2010年的實證資料來研究。我們分別在MACD和RSI指數裡面設置買賣點,並且加入fixed x% filtering rule和time-delay filter rule以過濾錯誤的交易訊號。
    本研究實證發現雖然有些技術分析所形成的最佳交易策略可以贏過Buy-and-hold的交易模式,但是總的來說,在我們的實證資料裡,MACD和RSI仍然不能顯著的創造比Buy-and-hold交易策略更好的報酬。


    The purpose of this paper is to test whether the use of two modern technical rules (i.e. the Moving Average Convergence and Divergence (MACD) and the Relative Strength Index (RSI) ) can produce a significant return comparing to the buy-and-hold strategy over the Hang Seng Index, Nikkei 225 Index and Taiwan Capitalization Weighted Stock Index during 1970 to 2010. Buy signals and sell signals are set by variables, and fixed x% filter rule and time-delay filter rule are applied to avoid false signals.
    We demonstrate that, although some technical trading analysis generates a higher total return or mean daily return, no strategies can dominate and outperform the buy-and-hold strategy in our sample period.

    Content
    1. Introduction…………..…………..…………..…………..…………..……………….1
    2. Literature Review…………..…………..…………..…………..…………..…………7
    2.1 The Basics of Technical Analysis…………..…………..………………………….…7
    2.2 The Dow Theory…………..…………..…………..…………..…………..……….…7
    2.3 Earlier Technical Analysis…………..…………..……………………………………9
    2.4 Modern Technical Analysis…………..…………..…………………………..…….14
    3. Data and Data Preliminary Analysis…………..…………..………………………..18
    3.1 Data…………..…………..………………………..…………..…………..………..18
    3.2 Summary Statistics on Return…………..…………..………………………………19
    4. Method…………..…………..…………………………………..…………..………24
    5. Empirical Results…………..…………..……………………………………………27
    6. Conclusion…………..…………..…………………………………………………..42
    Reference…………..…………..………………………..…………..…………………..44

    References
    Appel, G., (1999). Technical Analysis: Power Tools for Active Investors. Financial Times Prentice Hall.

    Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.

    Cheung, Y. W., & Chinn, M. D. (2001). Currency traders and exchange rate dynamics: a survey of the US market. Journal of International Money and Finance, 20(4), 439-471.

    Cootner, P. H. (1962). Stock prices: random vs. systematic changes. Industrial Management Review.

    Edwards, R. D., Magee, J., & Bassetti, W. H. C. (2007). Technical analysis of stock trends. CRC Press.

    Fama, E. F., & Blume, M. E. (1966). Filter rules and stock-market trading. The Journal of Business, 39(1), 226-241.

    Gartley, H. M. (1935). Profits in the Stock Market. Health Research Books.

    Gehrig, T., & Menkhoff, L. (2003). Technical Analysis in Foreign Exchange-The Workhorse Gains Further Ground (No. dp-278). Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Jensen, M. (1967). Random Walks: Reality or Myth-Comment. Financial Analysts Journal, November-December.

    Leuthold, R. M. (1972). Random walk and price trends: the live cattle futures market. The Journal of Finance, 27(4), 879-889.

    Lui, Y. H., & Mole, D. (1998). The use of fundamental and technical analyses by foreign exchange dealers: Hong Kong evidence. Journal of International Money and Finance, 17(3), 535-545.

    Lukac, L. P., Brorsen, B. W., & Irwin, S. H. (1988). A test of futures market disequilibrium using twelve different technical trading systems. Applied Economics, 20(5), 623-639.

    Lukac, L. P., & Brorsen, B. W. (1990). A comprehensive test of futures market disequilibrium. Financial Review, 25(4), 593-622.

    Menkhoff, L. (1997). Examining the use of technical currency analysis. International Journal of Finance & Economics, 2(4), 307-318.

    Menkhoff, L., & Taylor, M. P. (2007). The obstinate passion of foreign exchange professionals: technical analysis. Journal of Economic Literature, 936-972.

    Murphy, J. J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. Prentice Hall Press.

    Ni, H., & Yin, H. (2009). Exchange rate prediction using hybrid neural networks and trading indicators. Neurocomputing, 72(13), 2815-2823.

    Park, C. H., & Irwin, S. H. (2007). What do we know about the profitability of technical analysis?. Journal of Economic Surveys, 21(4), 786-826.

    Pring, M. J. (1991). Technical analysis explained: The successful investor's guide to spotting investment trends and turning points (Vol. 4). New-York: McGraw-Hill.

    Rhea, R., & Greiner, P. (1932). Dow Theory Comment.

    Smidt, S. (1965). Amateur speculators. Cornell Studies in Policy Administration.

    Sullivan, R., Timmermann, A., & White, H. (1999). Data‐snooping, technical trading rule performance, and the bootstrap. The journal of Finance, 54(5), 1647-1691.

    Chong, T. T. L., & Ng, W. K. (2008). Technical analysis and the London stock exchange: testing the MACD and RSI rules using the FT30. Applied Economics Letters, 15(14), 1111-1114.

    Taylor, M. P., & Allen, H. (1992). The use of technical analysis in the foreign exchange market. Journal of international Money and Finance, 11(3), 304-314.

    無法下載圖示 此全文未授權公開
    QR CODE
    :::