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博碩士論文 etd-0710102-145012 詳細資訊
Title page for etd-0710102-145012
論文名稱
Title
技術分析交易法則在股市擇時之實證研究
A Empirical Study on Stock Market Timing with Technical Trading rules
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
90
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2002-07-05
繳交日期
Date of Submission
2002-07-10
關鍵字
Keywords
市場擇時、拔靴複製法、移動平均法則、區塊重複抽樣、技術交易法則
market timing, bootstrap method, technical trading rules, block resampling, moving average rule
統計
Statistics
本論文已被瀏覽 5733 次,被下載 8428
The thesis/dissertation has been browsed 5733 times, has been downloaded 8428 times.
中文摘要
近年來,已有許多研究指出金融資產的走勢具有非線性的特質,而且在某段期間內呈現趨勢,且有愈來愈多的證據顯示,技術交易法則能夠察覺金融時間序列的非線性現象,使財務研究領域重新引起對技術分析的興趣。
本研究評估移動平均線交易法則在十二個國家中的十四種股價指數的市場擇時能力,其中包括美國、英國、法國、日本與香港等已開發市場,另外包括新加坡、南韓、台灣、印尼、馬來西亞、菲律賓、泰國等亞洲新興市場。研究期間自1990年1月至2002年3月22日。本研究使用傳統檢定、bootstrap p-value test、Cumby-Modest的市場擇時能力檢定及模擬股票交易來評估移動平均線法則的預測能力。其結果顯示,移動平均線法則對已開發市場無市場擇時能力,然而,對亞洲新興市場則具有市場擇時能力。對於移動平均線法則在亞洲新興市場具市場擇時能力的發現與先前研究的發現相同,因此,本研究建議投資人在新興市場中可以使用一般人均熟知的移動平均線做為市場擇時參考,幫助投資人進行全球化資產配置,將可獲得較高的投資績效與較低的損失風險。

Abstract
In the last few years, it has been proved that the movements of financial asset have the property of non-linearity and show some tendency within a given period. Increasing evidence that technical trading rules can detect non-linearity in financial time series has renewed interest in technical analysis.
This study evaluates the market timing ability of the moving average trading rules in twelve equity markets in the developed markets and the emerging markets from January 1990 through Match 2002. We use traditional test, bootstrap p-value test, Cumby-Modest’s market timing ability test and simulation stock trade to evaluate market timing ability. The overall results indicate that the moving average trading rules have predictive ability with respect to market indices in the Asia emerging stock markets. These findings may provide investors with important asset allocation information.

目次 Table of Contents
頁次
第一章 緒論 …………………………………………………………….1
第一節 研究動機與目的………………………………………………..2
第二節 研究架構與流程………………………………………………..5
第二章 相關理論與文獻探討……………………………………………7
第一節 技術分析………………………………………………………..8
第二節 效率市場假說………………………………………………….10
第三節 行為財務學派與其對效率市場假說的質疑………………….12
第四節 金融時間序列呈非線性現象之文獻………………………….16
第五節 技術分析相關文獻探討……………………………………….18
第六節 技術分析實證文獻探討……………………………………….20
第三章 研究方法……………………………………………………….35
第一節 樣本與資料說明……………………………………………….35
第二節 技術交易法則與買賣時機的決定…………………………….36
第三節 市場擇時能力的檢定方法…………………………………….38
第四節 模擬操作之研究假設與操作策略設定……………………….44
第四章 實證結果與分析……………………………………………….48
第一節 樣本統計……………………………………………………….48
第二節 標準統計檢結果……………………………………………….59
第三節 拔靴複製p-value 檢定結果………..……………………….52
第四節 Cumby-Modest之市場擇時能力檢定結果…………………...53
第五節 模擬投資操作結果…………………………………………….54
第五章 結論…………………………………………………………….59

附錄
參考文獻…………………………………………………………………..60
附件一:附表……………………………………………………………..65
附件二:bootstrap p-value之Matlab計算程式……………………….84
附件三:異質變異結構的估計與檢定:White調整法………………….89
參考文獻 References
一、 中文文獻

1.何文榮、王永昌譯(2001),「投資學」,第二版,美商麥格羅.希爾。原著 Bodie, Zvi, A. Kane, and A. J. Marcus(1996), Essentials of Investments, 4th ed, McGraw-Hill.
2.杜金龍(2002),「技術指標在台灣股市應用的訣竅」,增訂版,財訊出版社。
3.林楚雄、劉維琪、吳欽杉(2000),「台灣股票店頭市場股價報酬與波動支分析」,亞太管理評論,第五卷第四期,頁435-449。
4.周翠如、齊思賢譯(2000),「葛林史班的非理性繁榮」,時報出版。原著Shiller, Robert J.(2000), Irrational Exuberance, Princeton University Press.
5.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研究」,東海大學管理研究所未出版碩士論文。
6.施惠萍(1999),「結構性變化的偵測與其在技術分析中的應用」,台灣大學經濟學研究所未出版碩士論文。
7.俞濟群、黃嘉斌譯(1995),「金融煉金術」,寰宇出版。原著Soros, George(1994), The Alchemy of Finance:reading the mind of the market,J. Wiley.
8.徐俊明(2001),「投資學:理論與實務」,第三版,新陸書局。
9.陳正榮(2001),「以濾嘴法則檢驗台灣股票市場弱式效率性之研究」,高雄第一科技大學財務管理研究所未出版碩士論文。
10.陳松男(1995),全球化投資動態分析,台北金融研究發展基金會。
11.陳建全(1998),「台灣股市技術分析之實證研究」,台灣大學商學研究所未出版碩士論文。
12.張定綺譯(1998),「與天為敵:人類戰勝風險的傳奇故事」,商業週刊出版。原著Bernstein, Peter L.(1996),Against The Gods: The Remarkable Story of Risk, John Wiley & Sons, Inc.
13.張智星(2000),「MATLAB程式設計與應用」,清蔚科技出版。
14.郭祥兆、韓宜芬(1994),「台灣加權股價指數非線性與混沌現象之研究」,管理科學學報,第十一卷第一期,頁49-69。
15.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」,國立交通大學科技管理研究所未出版碩士論文(英文)。
16.黃嘉斌譯(2000),「金融市場技術分析」,初版,寰宇出版。原著Murphy, John J.(1999),Technical Analysis of the Financial Markets, Prentice-Hall.
17.葉日武(2000),「現代投資學:原理、技巧與應用」,前程企管。
18.楊美齡譯(1996),「漫步華爾街:股市終身理財之道」,第一版。原著Malkiel, Burton G.(1996), A Random Walk Down Wall Street:Including a Lift-Cycle Guide to Personal Investing ,7th ed, W.W.Norton.
19.蔡尚儒(2000),「台灣店頭市場技術分析的實證研究」,中正大學財務金融研究所未出版碩士論文。
20.劉體中、魏駿愷譯(2001),終極投資人:投資大師與投資觀念,財訊出版社。原著LeBaron, D., and R. Vaitilingam(1999), The Ultimate Investor:The People and Ideas That Make Modern Investment, Capstone US .
21.謝玉華(1999),「以拔靴複製法檢驗技術分析交易策略」,鉻傳大學金融學研究所未出版碩士論文。
22.謝劍平(1998),「現代投資學-分析與管理」,初版,智勝文化。
23.鍾淳豐(2001),「配合價量關係技術型態在台灣股票市場的應用」,政治大學財務管理研究所未出版碩士論文。
24.鍾惠民、吳壽山、周賓凰、范懷文(2002),「財金計量」,雙葉書局。

二、英文文獻

1.Alexander, Sindey. S.(1961),“Price Movements in Speculative Markets: Trends or Random Walks,”in P. Cootner, ed.: The Random Character of Stock Market Prices (MIT Press, Cambridge, Mass.), pp.199-218.
2. (1964),“Price Movements in Speculative Markets: Trends or Random Walks, No. 2,”in P. Cootner, ed.: The Random Character of Stock Market Prices (MIT Press, Cambridge, Mass.), pp.338-372.
3.Bessembinder, H. and K. Chan(1995),“The Profitability of Technical Trading Rules in the Asian Stock Markets,”Pacific-Basin Finance Journal, 3, pp.257-284.
4. (1998),“Market Efficiency and the Returns to Technical Analysis,”Financial Management, 27, pp.5-17.
5.Blume, L., D. Easley, and M. O’Hara(1994),“Market Statistics and Technical Analysis: The Role of Volume,”Journal of Finance, 47, pp.153-181.
6.Brock, W., J. Lakonishok, and B. LeBaron(1992),“Simple Technical Trading Rules and the Stochastic Properties of Stock Returns,”Journal of Finance, 47, pp.1731-1764.
7.Brown, D. P., and R. H. Jennings(1989),“On Technical Analysis,”Review of Financial Studies, 2, pp.527-551.
8.Chen, Shu-Heng(2000),“Lecture 7:Rescale Range Analysis and the Hurst Exponent,”Financial Economics(I), Department of Economics, National Chengehi University.
http://econo.nccu.edu.tw/ai/staff/shc/course.htm
9.Coutts J. A., and K. C. Cheung(2000),“Trading Rules and Stock Returns: Some Preliminary Short Run Evidence from The Hang Seng 1985-1997,”Applied Financial Economics, October, pp.579-586.
10.Cumby, R. E., and D. M. Modest(1987), “Testing for Market Timing Ability,” Journal of Financial Economics, 19, pp.169-189.
11.Davison, A. C., and D. V. Hinkley(1997),Bootstrap Methods and Their Application, Cambridge University Press.
12.Efron, B. and R. J. Tibshirani (1993),An Introduction to Bootstrap, Chapman & Hall.
13.Fama, E. F., and M. E. Blume(1966),“Filter Rules and Stock Market Trading Profits,”Journal of Business, 39, pp.226-241.
14.Fama, E. F.(1970),“Efficient Capital Markets: A Review of Theory and Empirical Work,”Journal of Finance, 25, pp.383-417.
15. (1991),“Efficient Capital Markets: Ⅱ,”Journal of Finance, 46, pp.1575-1618.
16.Gencay, R. and T. Stengos(1998),“Moving Average Rules, Volume and the Predictability of Security Returns with Feedforward Networks,”Journal of Forecasting, 17, pp. 401-414.
17.Gunasekarage, A. and D. M. Power(2001), “The profitability of moving average trading rules in South Asian stock markets,” Emerging Markets Review, 2, pp.17-33.
18.Hansen, P. R.(2001),“An Unbiased and Powerful Test for Superior Predictive Ability,”Brown University, Department of Economics Working Paper.
http://chico.pstc.brown.edu/~phansen.
19.Henriksson, R. D., and R. C. Merton(1981),“On Market Timing and Investment Performance. II. Statistical Procedures for Evaluating Forecasting Skills,” Journal of Business, 54, pp.513-533.
20.Hudson, R., M. Dempsey, and K. Keasey(1996),“A Note on the Weak from Efficiency of Capital Markets: The Application of Simple Technical Trading Rules to UK Stock Prices-1935 to 1994,” Journal of Banking and Finance, 20, p.1121-1132.
21.Ito, Akitoshi(1999),“Profits on Technical Trading Rules and Time-varying Expected Returns: Evidence from Pacific-Basin Equity Markets,” Pacific-Basin Finance Journal, 7, pp.283-330.
22.James, F. E.(1968),“Monthly Moving Averages-An Effective Investment Toll?”Journal of Financial and Quantitative Analysis, September, pp. 315-326.
23.Jensen, M. C., and G. Bennington(1970),“Random Walks and Technical Theories: Some Additional Evidences,”Journal of Finance, 25, pp.469-482.
24.Levy, R. A.(1967a),“Relative Strength as a Criterion for Investment Selection,”Journal of Finance, 22, pp.595-610.
25. (1967b),“Random Walks: Reality or Myth,”Financial Analysts Journal, 23, pp.69-77.
26.Lee, C. I., K. C. Gleason, and I. Mathur(2001),“Trading Rule Profits in Latin American Currency Spot Rates,”International Review of Financial Analysis, 10, pp.135-156.
27.Lo, A. W., H. M. Mamaysky, and J. Wang(2000),“Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation,” Journal of Finance, 55, pp.1705-1770.
28.Mandelbrot, Benoit B.(1997), Fractals and Scaling in Finance, Springer.
29.Morton, Robert C.(1981),“On Market Timing and Investment Performance. Ⅰ. An Equilibrium Theory of Value for Market Forecasts,” Journal of Business, 54, pp.363-406.
30. (1981),“On Market Timing and Investment Performance. Ⅱ. Statistical Procedures for Evaluating Forecasting Skills,” Journal of Business, 54, pp.513-533.
31.Neftci, Salih. N.(1991),“Naive Trading Rules in Financial Markets and Weiner-Kolmogorov Prediction Theory: A Study of Technical Analysis,” Journal of Business, 64, pp.549-571.
32.Peters, Edgar E.(1991),Chaos and Order in the Capital Markets: A New View of Cycles, Prices, and Market Volatility, John Wiley & Sons.
33.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, pp.55-58.
34.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, pp.1887-1905.
35.Scholes, M., and J. Williams(1977),“Estimating Beta from Nonsynchronous Data,”Journal of Financial Economics, 5, pp.309-327.
36.Skouras, Spyros(2001),“Financial returns and efficiency as seen by an artifical technical analyst,” Journal of Economic Dynamics and Control, 25, pp.213-244.
37.Sullivan, R., A. Timmermann, and H. White(1999),“Data-Snooping, Technical Trading Rule Performance, and the Bootstrap,”Journal of Finance, 54, pp. 1647-1691.
38.Sweeney, Richard J.(1988),“Some New Filter Rule Tests: Methods and Results,”Journal of Financial and Quantitative Analysis, 23, pp.285-300.
39.Szakmary, A., W. N. Davidson Ⅲ, and T. V. Schwarz, 1999, Filter Tests in Nasdaq Stocks,”Financial Review, 34, pp.45-70.
40.Van Horne, J. C., and G. G. C. Parker(1967),“The Random Walk Theory: An Emperical Test,”Financial Analysts Journal, 23, pp.87-92.
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