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題名：擇股模式之建構：DEA方法之應用
作者：莊汪清 引用關係
作者(外文)：Wang-Ching Chuang
校院名稱：銘傳大學
系所名稱：管理研究所博士班
指導教授：黃旭男
林進財
學位類別：博士
出版日期：2008
主題關鍵詞：選股模式；經營績效；股票市價評價；資料包絡分析法；Stock Selection Strategy；Relative Operating Performance；Relative Stock Price Evaluation；Data Envelopment Analysis
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投資股票之目的在於追求獲利，如何使用簡單又有效的方法，選擇投資標的而獲得較高的報酬，一直是投資人所關注的一大課題。本文主要目的是發展股票屬性分類法則，以獲得適宜的股票交易策略，進而建置一個有效的決策模式。本文以台灣IC產業上市上櫃公司的股票為研究標的，研究期間為2001-2006年，此一時期適逢台灣股市各有上、下波動型態出現，有助於構建較為嚴謹的股票交易策略。本文以Chang et al. (1995)效能的觀點，採用財務比率指標作為衡量的標準，運用資料包絡分析法全距調整衡量(DEA-RAM)，評估樣本之相對經營績效與相對股票市價評價，並依據評估結果將上市櫃公司分成四類，實證結果顯示本文所提出的股票分類模式具有顯著的區別能力，透過本文提供的分類股票方法，投資人可獲得較為有效的投資操作。本文展示利用DEA建立股票擇股模式，產生很好的效果。在分類上亦有學者在DEA的架構下進行判別分析，稱為DEA-DA，本文另外，以Sueyoshi (2003)，Sueyoshi and Hwang (2004)之研究為藍本，根據投資決策的理念，以財務指標構建一判別函數，任何一家公司之財務資料代入此函數，若所得到的綜合指標高於一門檻值，則為高報酬的公司，否則為低報酬的公司。DEA-DA在IC產業類股中的擊中率是90.00%，而傳統DEA-RAM判別正確率也只有73.33%，研究結果顯示DEA-DA運用於台灣股票市場股票分類上具有明顯的鑑別力。
Investment in equities is driven mainly by the desire to achieve profits. Adopting a simple and effective approach of stock classification to achieve higher returns or assume lower risk is a key concern for investors. This study aims to construct a decision support system to develop classified rules based upon stock attributes to obtain suitable stock trading strategies which can facilitate moderating investment risk. This investigation takes listed companies are from Taiwanese integrated circuit sector as investigative subjects, and investigate a study period running from 2001 to 2006, a period during which the Taiwan stock market experienced both bull and bear markets, which is beneficial to certify the model of stock classification we set whether it is good at making decisions of equities investment for investors. Utilizing the terms of effectiveness offered by Chang et al. (1995), adopt the financial ratios as measure indexes. This novel model of stock classification assesses relative operating performance either by DEA-range-adjusted measure and relative stock price evaluation using the DEA-RAM. The evaluation results are then used to further classify listed stocks based on four attributes. Empirical results indicate that the proposed stock classification model can predict stock returns, enabling both institutional and individual investors to reduce the risks associated with equity investments. Results of this study further demonstrate that DEA is extremely effective in devising stock trading strategies. Based on both the DEA-DA method of Sueyoshi (2003) and Sueyoshi and Hwang (2004) and the concepts of investment decision, this study measures from the financial indices of Taiwanese banks to construct a discriminant function that allow investors to distinguish between superior and inferior stocks in terms of stock returns for the upcoming year. Analytical results indicate that the additive model just has a 73.33% hit rate, compared to a 90% hit rate for DEA-DA demonstrating that the latter has superior discriminant capability to that of the former. The results indicate that DEA-DA is an effective approach applied to select stocks.
1.Abad, C., Thore, S. A., and Laffarga, J., “Fundamental Analysis of Stocks by Two-stage DEA,” Managerial and Decision Economics, Vol. 25, No. 5, 2004, pp. 231-241.
2.Abarbanell, J. S. and Bushee, B. J., “Fundamental Analysis, Future Earnings and Stock Prices,” Journal of Accounting Research, Vol. 35, No. 1, 1997, pp. 156-177.
3.Ahmet, B. and Nustret, C., “Do Markets Overreact? International Evidence,” Journal of Banking and Finance, Vol. 23, No. 7, 1999, pp. 1121-1144.
4.Aida, K., Cooper, W. W., Pastor, J. T. and Sueyoshi, T., “Evaluating Water Supply Services in Japan with RAM: A Range-adjusted Measure of Inefficiency,” International Journal of Management Science, Vol. 26, No. 2, 1998, pp. 207-232.
5.Ali, I. and Seiford, L., “Translation Invariance in Data Envelopment Analysis,” Operations Research Letters, Vol. 9, No. 6, 1990, pp. 403-405.
6.Antonio Pedro Duarte, S. and Stam, A., “Second-order Mathematical Programming Formulations for Discriminant Analysis,” European Journal of Operational Research, Vol. 72, No. 1, 1994, pp. 4-22.
7.Athanassopoulos, A. D. and Thanassoulis, E., “Assessing Marginal Impacts of Investments on the Performance of Organizational Units,” International Journal of Production Economics, Vol. 39, No.1-2, 1995, pp. 149-164.
8.Bae, K. H. and Kim, J. B., “The Usefulness of Earnings versus Book Value for Predicting Stock Returns and Cross Corporate Ownership in Japan,” Japan and the World Economy, Vol. 10, No. 4, 1998, pp. 467-485.
9.Bala, K. and Cook, W. D., “Performance Measurement with Classification Information: an Enhanced Additive DEA Model,” The International Journal of Management Science, Vol. 31, No. 6, 2003, pp. 439-450.
10.Ball, R., and Brown, P., “An Emipirical Evaluation of Accounting Income Numbers,” Journal of Accounting Research, Vol. 6, No. 2, 1968, pp. 159-178.
11.Bange, M., “Do the Portfolios of Small Investors Reflect Positive Feedback Trading?” Journal of Financial and Quantitative Analysis,” Vol. 35, No. 2, 2000, pp. 239-255.
12.Banks, W. J. and Abad, P. L., “On the Performance of Linear Programming Heuristics Applied on a Quadratic Transformation in the Classification Problem,” European Journal of Operational Research, Vol. 72, No. 1, 1994, pp. 23-28.
13.Banuman, W. S. and Miller, R. E., “Investor Expectations and the Performance of Value Stocks versus Growth Stocks,” Journal of Portfolio Management, Vol. 23, No. 3, 1997, pp. 57-68.
14.Barber, B. M. and Odean, T., “Trading is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors,” Journal of Finance, Vol. 55, No. 2, 2000, pp. 773-806.
15.Barr, R., Reid, K. and Lanstein, R., “Persuasive Evidence of Market Inefficiency,” Journal of Portfolio Management, Vol. 11, No. 3, 1985, pp. 9-17.
16.Bartholdy, J., “Changes in Earnings-price Ratios and Excess Returns: A Case of Investor Over-Reaction,” International Review of Financial Analysis, Vol. 7, No. 3, 1998, pp. 237-252.
17.Basu, S., “Investment Perfromance of Common Stocks in Relation to Their P/E Ratios: A Test of the Efficient Market Hypothesis,” Journal of Finance, Vol. 32, No. 3, 1977, pp. 663-682.
18.Basu, S. “The Relationship between Earnings, Market Value and Return for NYSE Common Stocks: Further Evidence,” Journal of Financial Economics, Vol. 12, No. 1, 1983, pp. 129-156.
19.Beaver, W. H., Clarke, R. and Wright, W.F., “The Association between Unsystematic Security Returns and the Magnitude of Earnings Forecast Errors,” Journal of Accounting Research, Vol. 17, No. 2, 1979, pp. 316-340.
20.Beebower, G. L. and Varikooty, A. P., “Measuring Market Timing Strategies,” Financial Analysts Journal, Vol. 47, No. 6, 1991, pp. 78-92.
21.Beneish, M. D., Lee, C. M. and Tarpley, R. L., “Contextual Fundamental Analysis through the Prediction of Extreme Returns,” Review of Accounting Studies, Vol. 6, No. 2-3, 2001, pp. 165-189.
22.Blume, M. E., and Husic, F., “Price, Beta, and Exchange Listing,” Journal of Finance, Vol. 28, No. 2, 1973, pp. 283-299.
23.Bohl, M. T. and Brzeszczyński, J., “Do Institutional Investors Destabilize Stock Prices? Evidence from an Emerging Market,” Journal of International Financial Markets, Institutions & Money, Vol. 16, No. 4, 2006, pp. 370-383.
24.Breen, W., “Low Price-Earnings Ratios and Industry Relatives,” Financial Analysis Journal, Vol. 24, No. 4, 1968, pp. 125-127.
25.Caves, D. W., Christensen, L. R. and Diewert, W. E., “The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity,” Econometrica, Vol. 50, No. 6, 1982, pp.1393-1414.
26.Chan, C.W., Hamao, Y., and Lakonishok, J., “Fundamentals and Stock Returns in Japan,” Journal of Finance, Vol. 46, No. 6, 1991, pp. 1739-1764.
27.Chang, R. P., McLeavey, D. W. and Rhee, S. G., “Short-term Abnormal Returns of the Contrarian Strategy in the Japanese Stock Market,” Journal of Business Finance and Accounting, Vol. 22, No. 7, 1995, pp. 1035-1048.
28.Chang, P. L., Hwang, S. N., and Cheng, W. Y., “Using Data Envelopment Analysis to Measure the Achievement and Change of Regional Development in Taiwan,” Journal of Environmental Management, Vol. 43, No. 1, 1995, pp. 49-66.
29.Charitou, A. and Panagiotides, G., “Financial Analysis, Future Earnings and Cash Flows, and the Prediction of Stock Returns: Evidence for the UK,” Accounting and Business Research, Vol. 29, No. 4, 1999, pp. 281-298.
30.Charnes, A., Cooper, W. W., Golany, B., Seiford, L. and Stulz, J., “Foundation of Data Envelopment Analysis for Parato-Koopmans Efficient Empirical Production Functions,” Journal of Econometrics, Vol. 30, No. 22, 1985, pp. 91-107.
31.Chen, A. S., Leung, M. T. and Daouk, H., “Application of Neural Networks to an Emerging Financial Market: Forecasting and Trading the Taiwan Stock Index,” Computers & Operations Research, Vol. 30, No. 6, 2003, pp. 901-923.
32.Choe, H., Kho, B. C. and Stulz, R. M., “Do Foreign Investors Destabilize Stock Markets? The Korean Experience in 1997,” Journal of Fiancial Economics, Vol. 54, No. 2, 1999, pp. 227-264.
33.Chopra, N., Lakonishok, J. and Ritter, J. R., “Measuring Abnormal Performance: Do Stocks Overreact?,” Journal of Financial Economics, Vol. 31, No.2, 1992, pp. 235-268.
34.Chui, A. C. W., and Wei, K. C. J., “Book-to-Market, Firm Size, and the Turn-of-the-Year Effect: Evidence from Pacific Basin Emerging Markets,” Pacific Basin Finance Journal, Vol. 6, No. 3-4, 1998, pp. 275-293.
35.Cohen, R. B., Gompers, P. A. and Vuolteenaho, T., “Who Underreacts to Cash-flow News? Evidence from Trading between Individuals and Institutions,” Journal of Financial Economics, Vol. 66, No. 2-3, 2002, pp. 409-462.
36.Cooper, W. W., Park, K. S., and Pastor, J. T., “A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA,” Journal of Productivity Analysis, Vol.11, No. 1, 1999, pp. 5-42.
37.Daniel, K., Hirshleifer, D., and Subrahmanyam, A., “Investor Psychology and Security Market under and Overreactions,” Journal of Finance, Vol. 53, No. 6, 1998, pp. 1839-1886.
38.Daniel, K. and Titman, S., “Market Efficiency in an Irrational World,” Financial Analysts Journal, Vol. 55, No. 6, 1999, pp. 28-40.
39.DeBondt, W. F. M. and Thaler, R., “Does the Stock Market Overact?,” Journal of Finance, Vol. 40, No. 3, 1985, pp. 1575-1671.
40.DeBondt, W. F. M. and Thaler, R., “Further Evidence on Investor Overreaction and Stock Market Seasonality,” Journal of Finance, Vol. 42, No. 3, 1987, pp. 557-581.
41.Diakoulaki, D., Mavrotas, G.. and Papayannakis, L., “A Multicriteria Approach for Evaluating the Performance of Industrial Firms,” International Journal of Management Science, Vol. 20, No. 4, 1992, pp. 467-474.
42.D’Mello, J. P., Lahey, K. E. and Mangla, I. U., “An Empirical Test of the Relative Valuation Model of Portfolio Selection,” Financial Analysts Journal, Vol. 47, No. 2, 1991, pp. 82-90.
43.Eakins, S. G. and Stansell, S. R., “Can Value-based Stock Selection Criteria Yield Superior Risk-adjusted Returns: An Application of Neural Networks,” International Review of Financial Analysis, Vol. 12, No. 1, 2003, pp. 83-97.
44.Easton, P.D. and Magliolo, J. Ⅲ, “Accounting Earnings and Security Valuation: Empirical Evidenceof the Fundamental Links,” Journal of Accounting Research, Vol. 23(Supplemnt), 1985, pp. 54-77.
45.Edmister, R. O., and Greene, J. B., “Performance of Super-low-price Stocks,” Journal of Portfolio Management, Vol. 7, No. 1, 1980, pp. 36-44.
46.Edirishinghe, N. C. P. and Zhang, X., “Generalized DEA Model of Fundamental Analysis and its Application to Portfolio Optimization,” Journal of Banking & Finance, Vol. 31, No. 31, 2007, pp. 3311-3335.
47.Erenguc, S. S. and Koehler, G. J., “Survey of Mathematical Programming Models and Experimental Results for Linear Discriminant Analysis,” Managerial and Decision Economics Vol. 11, No. 4, 1990, pp. 215-225.
48.Fama, E. F. and French, K. R., “The Cross-section of Expected Stock Returns,” Journal of Finance, Vol. 47, No. 2, 1992, pp. 427-465.
49.Fama, E. F. and French, K. R. “Common Risk Factors in the Returns on Stocks and Bonds,” Journal of Financial Economics, Vol. 33, No. 1, 1993, pp. 3-56.
50.Farrelly, G. E., Ferris, K. R., and Reichensteing, W. R., “Perceived Risk, Market Risk and Accounting Determined Risk Measures,” The Accounting Review, Vol. 60, No. 2, 1985, pp. 278-288.
51.Ferson, W. E. and Harvey, C. R., “The Risk and Predictability of International Equity Returns,” Review of Financial Studies, Vol. 6, No. 3, 1993, pp. 527-566.
52.Fisher, R. A., “The Use of Multiple Measurements in Taxonomy Problems,” Annals of Eugenics, Vol. 7, 1936, pp. 179-188.
53.Frankel, R. and Lee, C. M. C. “Accounting Valuation, Market Expectation, and Cross-sectional Stock Returns,” Journal of Accounting and Economics, Vol. 25, No. 3, 1998, pp. 283-319.
54.Freed, N. and Glover, F., “A Linear Programming Approach to the Discriminant Problem,” Decision Sciences, Vol. 12, No. 1, 1981, pp. 68-73.
55.Freed, N. and Glover, F., “Resolving Certain Difficulties and Improving the Classification Power of LP Discrimininant Analysis Formulations,” Decision Sciences, Vol. 17, No. 4, 1986, pp.589-595.
56.Fritzmeier, L. H., “Relative Price Fluctuations of Industrial Stocks in Different Price Groups,” Journal of Business, Vol. 9, No. 2, 1936, pp. 133-154.
57.Gehrlein, W. V., “General Mathematical Programming Formulations for the Statistical Classification Problem,” Operation Research Letter, Vol. 5, No. 6, 1986, pp. 299-304.
58.Glen, J. J., “An Iterative Mixed Integer Programming Method for Classification Accuracy Maximizing Discriminant Analysis,” Computers & Operations Research, Vol. 30, No. 2, 2003, pp. 181-198.
59.Goodman, D. A., and Peavy, J. W., “The Low Price Effect: Relationship with Other Stock Market Anomalies,” Southwestern Finance Association Conference, New Orleans, March, 1985.
60.Grinblatt, M., Titman, S., and Wermers, R., “Momentum Investment Strategies, Portfolio Performance, and Herding: A Study of Mutual Fund Behavior,” American Economic Review, Vol. 85, No. 5, 1995, pp. 1088-1105.
61.Grinblatt, M. and Keoharju, M., “The Investment Behavior and Performance of Various Investor Types: A Study of Finland’s Unique Data Set,” Journal of Financial Economics, Vol. 55, No. 1, 2000, pp. 43-67.
62.Hameed, A. and Ting, S., “Trading Volume and Short-horizon Contrarian Profits: Evidence from Malaysian Stock Market,” Pacific-Basin Finance Journal, Vol. 8, No. 1, 2000, pp. 67-84.
63.Hart, J. V. D., Slagter, E. and Dijk, D. V., “Stock Selection Strategies in Emerging Markets,” Journal of Empirical Finance, Vol. 10, No. 1-2, 2003, pp. 105-132.
64.Harvey, C. R. “Predictable Risk and Returns in Emerging Markets,” Review of Financial Studies, Vol. 8, No. 3, 1995, pp. 773-816.
65.Haugen, R. A. and Baker, N. L., “Commonality in the Determinants of Expected Stock Returns,” Journal of Financial Economics, Vol. 41, No. 3, 1996, pp. 401-439.
66.Haugen, R. A., and Heins, A. J., “Risk and the Rate of Return on Financial Assets: Some Old Wine in New Bottles,” Journal of Financial and Quantitative Analysis, Vol. 10, No. 5, 1975, pp. 775-784.
67.Heins, A. J., and Allison, S.L., “Some Factors Affecting Stock Price Variability,” Journal of Business, Vol. 39, No. 1, 1966, pp. 19-23.
68.Huang, B. H., “Do Asian Stock Market Prices Follow Random Walk? Evidence from the Variance Ratio Test,” Applied Financial Economics, Vol. 5, No. 4, 1995, pp. 251-256.
69.Huang, B. N. and Yang, C. W., “The Fractal Structure in Multinational Stock Returns,” Applied Economics Letters, Vol. 2, No. 3, 1995, pp. 67-71.
70.Huang, B. N. and Yang, C. W., “An Empirical Investigation of Trading Volume and Return Volatility of the Taiwan Stock Market,” Global Finance Journal, Vol. 12, No. 1, 2001, pp. 55-77.
71.Huang, W., Nakamori, Y. and Wang, S. Y., “Forecasting Stock Market Movement Direction with Support Vector Machine,” Computers & Operations Research, Vol. 32, No. 10, 2005, pp. 2513-2522.
72.Hwang, S.N., Lin, C. T. and Chuang, W. C., “Stock Selection Using Data Envelopment Analysis-Discriminant Analysis,” Journal of Information and Optimization Sciences, Vol. 28, No. 1, 2007, pp. 33-50.
73.Hwang, S. N., Lin, C. T. and Chuang, W. C., “Formulating a Novel Stock Selection Model Using DEA and Grey Situation Decision Model,” Journal of Statistics & Management Science, Vol. 10, No. 1, 2007, pp. 103-127.
74.Jaffe, J., Keim, D. B., and Westerfield, R., “Earnings Yilds, Market Values, and Stock Returns,” Journal of Finance, Vol. 44, No. 1, 1989, pp. 135-148.
75.Jagannathan, R. and Korajczyk, R. A., “Assessing the Market Timing Performance of Managed Portfolios,” Journal of Business, Vol. 59, No. 2, 1986, pp. 217-235.
76.Jegadeesh, N., “Evidence of Predictable Behavior of Security Returns,” Journal of Finance, Vol. 45, No. 3, 1990, pp. 881-898.
77.Jegadeesh, N., and Titman, S.,”Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency,” Journal of Finance, Vol. 48, No. 1, 1993, pp. 65-91.
78.Kahneman, D., and Tversky, A., “Prospect Theory: An Analysis of Decision under Risk,” Economertrica, Vol. 47, No. 2, 1979, pp. 263-291.
79.Kahneman, D and Riepe, M. W., “Aspects of Investor Psychology,”Journal of Portfolio Management, Vol. 24, No. 4, 1998, pp. 52-65.
80.Kamesaka, A., Nofsinger, J. R. and Kawakita, H., “Investment Patterns and Performance of Investor Groups in Japan,” Pacific-Basin Finance Journal, Vol. 11, No. 1, 2003, pp.1-22.
81.Keith, K. S. L., “The Relationship between Size, Book-to-Market Equity Ratio, Earnings-Price Ratio and Return for the Hong Kong Stock Market,” Global Finance Journal, Vol.13, No. 2, 2002, pp. 163-179.
82.Kendal, S. M., Stuart, A. and Ord, J. K., The Advanced Theory of Statistics, Charles Grifin, London, 1983.
83.Kothari, S. P., and Shanken, J., “Book-to-market, Dividend Yield, and Expected Market Returns: A Time-series Analysis,” Journal of Financial Economics, Vol. 44, No. 2, 1997, pp. 169-203.
84.Kozmetsky, G. and Yue, P., “Comparative Performance of Global Semiconductor Companies,” Omega, International Journal of Management Science, Vol. 26, No. 2, 1998, pp. 153-175.
85.Lakonishok, J., Shleifer, A. and Vishny, R. W., “The Impact of Institutional Trading on Stock Prices,” Journal of Financial Economics, Vol. 32, No. 1, 1992, pp. 23-41.
86.Lakonishok, J., Shleifer, A., and Vishny, R. W. “Contrarian Investment, Extrapolation, and Risk,” Journal of Finance, Vol. 49, No. 5, 1994, pp. 1541-1578.
87.Lau, S. T., Lee, C. T., and McInish, T. H., “Stock Returns and Beta, Firms Size, E/P, CF/P, Book-to-market, and Sales Growth: Evidence from Singapore and Malaysia,” Journal of Multinational Financial Management, Vol. 12, No. 3, 2002, pp. 207-222.
88.Lee, Y. T., Lin, J. C., and Liu, Y. J., “Trading Patterns of Big versus Small Players in an Emerging Market: an Empirical Analysis,” Journal of Banking and Finance, Vol. 23, No. 5, 1999, pp. 701-725.
89.Leung, M. T., Daouk, H. and Chen, A. S., “Forecasting Stock Indices: A Comparison of Classification and Level Estimation Models,” International Journal of Forecasting, Vol. 16, No. 2, 2000, pp. 173-190.
90.Lev, B. and Thiagarajan, R., “Fundamental Information Analysis,” Journal of Accounting Research, Vol. 31, No. 2, 1993, pp. 190-215.
91.Lewellen, J., “Predicting Returns with Financial Ratios,” Journal of Financial Economics, Vol. 74, No. 2, 2004, pp. 209-235.
92.Lo, A. W. and MacKinlay, A. C. “Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test,” Review of Financial Studies, Vol. 1, No.1, 1988, pp. 41-66.
93.Mann, H. B. and Whitney, D. R., “On a Test of Whether one of Two Random Variables is Stochastically Larger than The Other,” Annals of Mathematical Statistics, Vol. 18, No. 1, 1947, pp. 50-60.
94.Markowski, E. P. and Markowski, C. A., “An Experimental Comparison of Several Approaches to the Discriminant Problem with Both Qualitative and Quantitative Variables,” European Journal of Operational Research, Vol. 28, No. 1, 1987, pp. 23-28.
95.Martikainen, T., “Stock Returns and Classification Pattern of Firm-specific Financial Variables: Empirical Evidence with Finnish Data,” Journal of Business Finance and Accounting, Vol. 20, No. 4, 1993, pp. 539-559.
96.McLachlan, G. L., Discriminant Analysis and Statistical Pattern Recognition, Wiley, NY, 1992.
97.McWilliams, J. D., “Prices, Earnings, and P-E Ratios,” Financial Analysts Journal, Vol. 22, May-June, 1966, pp. 169-179.
98.Nofsinger, J. R. and Sias, R. W., “Herding and Feedback Trading by Institutional and Individual Investors,” Journal of Fiance, Vol. 54, No. 6, 1999, pp. 2263-2295.
99.Odean, T., “Are Investors Reluctant to Realize their Losses?,” Journal of Finance, Vol. 53, No. 5, 1998, pp. 1775-1798.
100.Odean, T., “Do Investors Trade too Much?,” American Economic Review, Vol. 89, No. 5, 1999, pp. 1279-1298
101.Ou, J. A., “The Information Content of Nonearnings Accounting Numbers as Earnings Predictors,” Journal of Accounting Research, Vol. 28, No. 1, 1990, pp. 144-163.
102.Pendaraki, K., Zopounidis, C. and Doumpos, M., “On the Construction of Mutual Fund Portfolios: A Multicriteria Methodology and an Application to the Greek Market of Equity Mutual Funds,” European Journal of Operational Research, Vol. 163, No. 2, 2005, pp. 462-481.
103.Pinches, G. E., and Simon, G. M., “An Analysis of Portfolio Accumulatin Strategies Employing Low-priced Common Stocks,” Journal of Financial and Quantitative Analysis, Vol. 7, No. 3, 1972, pp. 1773-1796.
104.Pontiff, J. and Schall, L. D., “Book –to –market Ratios as Predictors of Market Returns,” Journal of Financial Economics, Vol. 49, No. 2, 1998, pp. 141-160.
105.Quah, T. S. and Srinivasan, B., “Improving Returns on Stock Investment through Neural Network Selection,” Expert Systems with Application, Vol. 17, No. 4, 1999, pp. 295-301.
106.Reilly, F. K. and Brown, K. C. Investment Analysis and Portfolio Management 6th ed., South-Western, New York, pp. 783-785, 2000.
107.Retzlaff-Roberts and Donna L., “Relating Discriminant Analysis and Data Envelopment Analysis to One Another,” Computers & Operations Research, Vol. 23, No. 4, 1996, pp. 311-322.
108.Rosenberg, B., Reid, K. and Lanstein, R., “Persuasive Evidence of Market Inefficiency,” Journal of Portfolio Management, Vol.11, No. 3, 1985, pp. 9-17.
109.Rouwenhorst, K.G., “International Momentum Strategies,” Journal of Finance, Vol. 53, No. 1, 1998, pp. 267-284.
110.Rouwenhorst, K. G., “Local Return Factors and Turnover in Emerging Stock Markets,” Journal of Finance, Vol. 54, No. 4, 1999, pp. 1439-1464.
111.Rubin, P. A., “A Comment Regarding Polynomial Discriminant Functions,” European Journal of Operational Research, Vol. 72, No. 1, 1994, pp. 29-31.
112.Schadler, F. P. and Eakins, S. G., “A Stock Selection Model Using Morningstar’s Style Box,” Financial Services Review, Vol. 10, No.1-4, 2001, pp.129-144.
113.Scharfstein, D. S., and Stein, J. C., “Herd Behavior and Investment,” American Economic Review, Vol. 80, No. 3, 1990, pp.465-479.
114.Schiereck, D., DeBondt, W. and Weber, M., “Contrarian and Momentum Strategies in Germany,” Financial Analysts Journal, Vol. 55, No. 6, 1999, pp.104-116.
115.Shapira, Z. and Venezia, I.,“Patterns of Behavior of Professionally Managed and Independent Investors,” Journal of Banking & Finance, Vol. 25, No. 8, 2001. pp. 1573-1587.
116.Shefrin, H., Statmean, M. and Constantinides, G.M., “The Disposition to Sell Winners too Early and Ride Losers too Long: Theory and Evidence,” Journal of Finance, Vol. 40, No. 3, 1985, pp. 777-790.
117.Shephard, R.W., “Theory of Cost and Production Functions,” Journal of Economic Literature, Vol. 1, No. 1, 1972, pp. 66-68.
118.Sinuany-Stern, Z., Mehrez, A. and Barboy, A., “Academic Departments Efficiency via Data Envelopment Analysis,” Computers and Operations Research, Vol. 21, No. 5, 1994, pp. 543-556.
119.Sinuany-Stern, Z. and Friedman, L, “Data Envelopment Analysis and the Discriminant Analysis of Ratios for Ranking Units,” European Journal of Operational Research, Vol. 111, No. 3, 1998, pp. 470-478.
120.Sloan, R. G., “Do Stock Prices Fully Reflect Information in Accruals and Cash Flows about Future Earnings?,” The Accounting Review, Vol. 71, No. 3, 1996, pp. 289-315.
121.Smith, C. A. B., “Some Examples of Discrimination,” Annals of Eugenics, Vol. 13, 1947, pp. 272-282.
122.Speranza, M. G., “A Heuristic Algorithm for a Portfolio Optimization Model Applied to the Milan Stock Market,” Computers and Operations Research, Vol. 23, No. 5, 1996, pp. 433-441.
123.Stam, A. and Ragsdale, C. T., “On the Classification Gap in Mathematical Programming Based Approaches to the Discriminant Problem,” Naval Research Logistics, Vol. 39, No. 4, 1992, pp. 545-559.
124.Sueyoshi, T., “DEA-discriminant Analysis in the View of Goal Programming,” European Journal of Operational Research, Vol. 115, No. 3, 1999, pp. 564-582.
125.Sueyoshi, T., “Extended DEA-Discriminant Analysis,” European Journal of Operational Research, Vol. 131, No. 2, 2001, pp. 324-351.
126.Sueyoshi, T., “Mixed Integer Programming Approach of Extended DEA-discriminant Analysis,” European Journal of Operational Research, Vol. 152, No. 1, 2004, pp. 45-55.
127.Sueyoshi, T., and Hwang, S. N., “A Use of Nonparametric Tests for DEA-Discriminant Analysis: A Methodological Comparison,” Asia-Pacific Operational Research, Vol. 21, No. 2, 2004, pp. 179-195.
128.Thore, S., Phillips, F., Rueflis, T. W. and Yue, P., “DEA and Management of the Product Cycle: The U.S. Computer Industry,” Computers and Operations Research, Vol. 23, No. 4, 1996, pp. 341-356.
129.Wermers, R., “Mutual Fund Herding and the Impact on Stock Price,” Journal of Finance, Vol. 54, No. 2, 1999, pp. 581-622.
130.Wilson, J. M., “Integer Programming Formulations of Statistical Classification Problems,” International Journal of Management Science, Vol. 24, No. 6, 1996, pp. 681-689.
131.Wong, F. S., Wang, P. Z., Goh, T. H. and Quek, B. K., “Fuzzy Neural Systems for Stock Selection,”Financial Analysis Journal, Vol. 48, No. 1, 1992, pp. 47-52.
132.Wong, K.A. and Lye, M.S., “Market Values, Earnings’Yields, and Stock Returns: Evidence from Singapore,” Journal of Banking and Finance, Vol. 14, No. 2-3, 1990, pp. 311-326.
133.Yang, J. J. W.,“The Information Spillover between Stock Returns and Institutional Investor’s Trading Behavior in Taiwan,” International Review of Finacial Analysis, Vol. 11, No. 4, 2002, pp. 533-547.
134.Zhu, J., “Multi-factor Performance Measure Model with an Application to Fortune 500 Companies,” European Journal of Operational Research, Vol. 123, No. 1, 2000, pp. 105-124.
二、中文部分
1.高強、黃旭男、Sueyoshi，管理績效評估：資料包絡分析法，台北：華泰文化，2003年7月。new window
 
 
 
 
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