| 研究生: |
鍾任群 Jen-Chun Chung |
|---|---|
| 論文名稱: |
量化寬鬆政策背景下的美國股票市場弱式效率性之實證 - 以移動平均線黃金交叉與死亡交叉之技術分析檢驗 |
| 指導教授: |
高櫻芬
Yin‑Feng Gau |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 財務金融學系在職專班 Executive Master of Finance |
| 論文出版年: | 2018 |
| 畢業學年度: | 106 |
| 語文別: | 中文 |
| 論文頁數: | 62 |
| 中文關鍵詞: | 量化寬鬆 、弱式效率市場 、技術分析 、移動平均線 、黃金交叉 、死亡交叉 |
| 相關次數: | 點閱:16 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 |
證券市場是否符合弱式效率市場假說?技術分析交易策略是否能為投資人帶來超額報酬?這樣的話題不論是在國內/外一直是備受爭議的議題。而美國聯準會因2008年金融海嘯導致經濟衰退的情況下,於2009年3月18日至2014年10月29日實施了一項非傳統的貨幣政策-『量化寬鬆』,本研究的目的就是要探討在美國實施量化寬鬆政策下,投資人是否能透過技術分析的方法來打敗大盤(即買進持有策略),而技術分析是選用以20日與60日移動平均線為基礎的黃金交叉和死亡交叉買賣策略,本文的研究期間係以自2009年3月18日至2014年10月29日為止的每日收盤價的歷史資料來進行實證,進而探討在量化寬鬆政策背景下的美國股票市場是否具有弱式效率性。
Fed implemented an unconventional monetary policy, quantitative easing (QE), from Mar. 18, 2009 to Oct. 29, 2014 to deal with the economic recession led by the financial tsunami in 2008. The purpose of this study is to discuss if investors can beat the buy-and-hold strategy by technical analysis under the background of QE. The technical analysis indicators we use are golden cross and death cross based on the 20-day and 60-day moving average. We use the historical daily closing price data from Mar. 18, 2009 to Oct. 29, 2014 to examine if the US equity market under the background of QE supports the weak form efficient market hypothesis.
一、中文部分
1.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碩士論文。
2.杜金龍(2002),技術指標在台灣股市應用的訣竅,台北:財訊出版社。
3.林士銘(2013),黃金交叉與死亡交叉對台灣股價指數預測能力之實證研究-1983~2012,私立銘傳大學風險管理與保險學系碩士在職專班碩士論文。
4.陳賢達(2007),技術分析在股票市場產生超額報酬可能性之實證探討-以寶來台灣50ETF為例,國立臺灣科技大學商業及管理學系碩士論文。
5.許博炫(2001),技術分析之有效性檢定與資料探查誤差研究:道瓊工業指數之實證,國立交通大學國立交通大學碩士論文。
6.黃彥聖(1995),「移動平均法的投資績效」,管理評論,第十四卷第一期:47-68。
7.趙永昱(2002),技術分析交易法則在股市擇時之實證研究,中山大學財務管理研究所碩士論文。
8.樓禎祺、何培基(2003),股價移動平均線之理論與實證-以台灣股市模擬投資操作為例,育達研究叢刊,第五、六期合刊,27-52。
9.賴宏祺(1997),技術分析有效性之研究,國立中興大學企業管理學系碩士論文。
10.賴勝章(1990),台灣股票市場弱式效率性實證研究-以技術分析檢驗,國立臺台灣大學。
11.謝劍平(2007),投資學-基本原理與實務,台北:智勝文化。
二、英文部分
1.Brunnermeier, M. and Pedersen,L., 2009, Market Liquidity and Funding Liquidity, Review of Financial Studies, 22(6): 2201-2238.
2.Brock, W., Lakonishok, J., and LeBaron, B., 1992, Simple technical trading rules and the stochastic properties of stock returns, Journal of Finance, 47(5): 1731-1764.
3.Coe, T. S. and Laosethakul K.,2010, Should Individual Investors Use Technical Trading Rules to Attempt to Beat the Market? Working Paper of Sacred Heart University.
4.Coutts, JA, and Cheung, K-C., 2000, Trading rules and stock returns: some further short run evidence from the Hang Seng 1997-2008, Applied Financial Economics, 10:579-586.
5.Eng, William F., The Technical Analysis of Stock, Options & Futures: Advanced Trading Systems and Technioues, Chicago: Probus Publishing, 1988.
6.Fama, E. F., and Blume, M. E., 1966, Filter rules and stock market trading, Journal of Business, 39: 226-241.
7.Fifield, S.G.M., Power, D.M., and Sinclair, C. D., 2005, An analysis of trading strategies in eleven European stock markets. European Journal of Finance, 11(6): 531-548.
8.Gunasekarage, A. and Power, D.M., 2001, The profitability of moving average trading rules in South Asian stock markets, Emerging Markets Review, 2(1): 17-33.
9.Hsu, P.-H., and Kuan, C.-M., 2005, Reexamining the profitability of technical analysis with data snooping checks. Journal of Financial Econometrics, 3(4): 606-628.
10.Jensen, M.J., and Bennington, G., 1970, Random walks and technical theories: Some additional evidence, Journal of Finance, 25: 469-482.
11.Kwon, K.-Y., and Kish, R.J., 2002, Technical trading strategies and return predictability: NYSE. Applied Financial Economics, 12(9): 639-653.
12.Levy, R.A , and Jensen, M.C., 1967, Random walks: Reality or myth, Financial Analysts Journal, 23: 77-85.
13.Marshall, B.R., and Cahan, R.H., 2005, Is technical analysis profitable on a stock market which has characteristics that suggest it may be inefficient? Research in International Business and Finance, 19: 384-398.
14.Marshall, B.R., Young, M.R., and Rose, L.C. 2006. Candlestick technical trading strategies: Can they create value for investors? Journal of Banking & Finance, 30: 2303-2323.
15.Metghalchi M., Marcucci J. and Chang Y.-H.,2012, Are moving average trading rules profitable? Evidence from the European stock markets, Journal Applied Economics, 44:1539-1559.
16.Sweeney, R. A., 1988, Some new filter rule tests: Methods and results, Journal of Financial and Quantitative Analysis, 23: 285-300.
17.Shynkevich A.,2012, Performance of technical analysis in growth and small cap segments of the US equity market, Journal of Banking and Finance, 36(1):193-208.
18.Teweles, Richard J. and Bradley, Edward S., The Stock Market, 4th ed., New York: John Wiley & Sons Inc., 1982.
19.Urquhart A., Gebka B., and Hudson R., 2015, How exactly do markets adapt? Evidence from the moving average rule in three developed markets. Journal of International Financial Markets, Institutions and Money, 38: 127-147.
20.Van Horne, J. C., and Parker, G. C., 1967, The random walk theory: An empirical test, Financial Analysts Journal, 23(6): 87-92.