| 研究生: |
鄭永欣 Cheng, Yung-Hsin |
|---|---|
| 論文名稱: |
技術交易法則是否能夠在台灣股票市 場獲利? Is technical rule useful in Taiwan stock market? |
| 指導教授: |
山本竜市
Yamamoto, Ryuichi |
| 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: | 2009 |
| 畢業學年度: | 97 |
| 語文別: | 英文 |
| 論文頁數: | 38 |
| 中文關鍵詞: | 技術分析 |
| 外文關鍵詞: | Technical Rules |
| 相關次數: | 點閱:127 下載:44 |
| 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 |
本文強烈地支持技術分析在台灣股票市場的有效性。本研究使用簡單技術分析法則-移動平均線法和區間突破法則,此兩法則在Brock el al(1992) 的文獻中被證明在道瓊工業指數具有獲利性。本文引用此兩法則於1981-2008的台灣股票加權指數。根據實證結果顯示,由此兩法則所產生的報酬率和利用拔靴法模擬出來的序列資料產生的報酬率結果並不一致。除此之外,即使考慮了交易成本,這些簡單技術交易法則仍然能在不同的類股指數中獲利。
The results in this paper strongly support the practicability of technical rules in Taiwan. Two of simplest rules-moving average and trading range break which were proved to be useful in Brock el al(1992) also possess predictive power in Taiwan stock index from 1981 to 2008. The return generated from these technical rules are not consistent with four null model, random walk, AR(1), the AR-GARCH and AR-GARCH-M. Besides, the returns from these technical rules can remain positive after cutting transaction costs. These technical rules can also apply to sector index and still gain excess returns.
Catalog
Abstract 1
Background and Motivation 3
Previous Works 4
Data 6
Technical Trading Rules 7
Empirical Results: Traditional Tests 8
Sample Statistics 8
Variable Length Moving Average Strategy 10
Fixed length Moving Average Strategy 13
Fixed length Trading Range Break Strategy 15
Bootstrap Methodology 16
Empirical Results: Bootstrap Tests 18
Random Walk Process 18
AR(1) process 21
AR(1)-GARCH(1,1)process 23
AR(1)-GARCH(1,1)-M Process 22
Trading Profits and Transaction Costs 25
Empirical results for Financial Sector index and Electric Sector index 29
Conclusions 35
References 36
1. Alexander, S.S.,1961, price movements in speculative markets: Trends or random
walks
2. Bessembinder, H. and K. Chan., 1995, “The Profitability of Technical Trading
Rules in the Asian Stock Market.” , Pacific-Basin Finance Journal 3, 257-284.
3. Bessembinder, H. and K. Chan., 1998, “Market Efficiency and the Returns to
Technical Analysis” Financial Management, 27,5-17.
4. Brock, William, Josef Lakonishock, and Blake LeBaron, 1992, Simple Technical trading rules and the stochastic properties of stock returns, Journal of Finance 47,
1731-1764
5. Brown, S. J., William A. , Goetzmann, Alok, K., 1998, “The Dow Theory: William Peter Hamilton’s Track Reconsidered,” The Journal of Finance, August, pg.
1311-1333
6. Cootner, P. H. , 1964, “Stock Market Price: Random vs. System change,”
Industrial Mamagement Review, Vol.3 , pg. 24-45, Spring.
7. Cowles, A. , 1993, “Can Stock Market Forecasters Forecast? ”, Econometrica,
July, pg. 579-586, October.
8. Fama, E. F. , French, K., 1992, “Technical analysis of stock trends ”, 86.
9. Fama, E. F. ,Blume, M. E. , 1966, “Filter Rules and Stock Market Trading
Profits, ” Journal of Business, pg. 226-241
10. Fama, E. F. , 1970, “Efficient Capital Markets: A Review of Theory and Empirical
Work”, Journal of Finance 25, pg. 383-417, May
11. Jesen, M. C. , Benington, G. A. , 1970, “Random Walks and Technical Theories:
Some Additional Evidence ” , Journal of Finance, XXIII, May, pg.77-85.
12. 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).pg. 1887-1905
13. Sweeny, R J. , 1988, “Some New Filter Rule Test: methods and Results,” Journal
of Financial and Quantitative Analysis, pg.285-300
14. Sullivan, R., A. Timmermann and H. White, 1999. “Data-Snooping, Technical Trading Rule Performance, and the Bootstrap,” The Journal of
Finance, October, pg. 1647-1691
15. Pruitt, S.W. , Richard E. W., 1988, “The CRISMA trading system: Who says technical analysis can’t beat the market?”, Journal of Portfolio Management,
pg.55-58
16. 方國榮,1991,「證券投資最適決策指標之研究─技術面分析」台灣大學商學
研究所未出版論文
17. 賴宏祺,1996,「技術分析有效性之研究」,中興大學企業管理學研究所未出
版論文
18. 洪志豪,1999,「技術指標KD、MACD、RSI與WMS%R之操作績效實證」台灣大
學國際企業管理研究所未出版論文