臺灣博碩士論文加值系統

本研究以台灣股票市場上市公司為樣本建立效率組合，樣本資料的期間為2003年至2010年，樣本期間共8年，以銷售面的財務資料作為投入與產出變數計算公司的相對效率值以建立組合，配合CAPM一因子、Fama-French三因子和四因子時間序列模型來驗證公司內部的管理效率與股價報酬率之間的關係，並且驗證新興市場中以管理效率作為選股指標是否能夠獲得超額報酬，是否公司效率為一有效的股票投資指標。
本研究並加入DEA三階段方法，排除掉環境變動與運氣因素，得出管理階層純粹的管理效率並建立DEA三階段下的效率組合，並且比較DEA一階段與三階段的組合何者的效率值較能夠成為投資指標，何者的效率指標有超額報酬的存在。
研究結果發現效率最差的幾組組合的報酬率最低，而效率愈好的組合卻不一定有較高的報酬；但是效率愈好的組合其風險愈低，而效率愈差的組合風險則最高。透過迴歸模型來看組合的報酬率，效率最佳的組合表現較效率最差的組合佳，但是其超額報酬表現仍是低於市場的，造成超額報酬為負其原因可能台灣新興市場的特性，其股價波動可能受到一些當地資訊以及政治因素等造成波動，而在一般的風險因子的解釋下可能仍無法取得正向的超額報酬。但是，仍可透過long-short策略買入效率佳的公司並且short效率差的公司來獲得正的超額報酬。
透過DEA三階段方法所建立的純粹效率組合，其結果與DEA一階段下的結果相似，效率最高的表現較效率最差的來得好，且可透過long-short策略來得到超額報酬，但是從敘數統計來看DEA三階段與DEA一階段相比下組合整體的報酬率較高，且整體的風險也較低。

This paper use the companies listed on TSE as the sample to establish the efficiency portfolio for the period 2003-2010 and use sales measure as input and output variables to calculate the relative efficiency value to create a portfolio. This paper also employ CAPM, Fama-French three-factor, and Carhart four-factor time series model to investigate the relationship between the management efficiency and the stock returns and verify whether management efficiency in the emerging markets can be a benchmark to get excess returns.
This paper add three-stage DEA to exclude circumstances and luck factors to calculate purely administrative efficiency value and establish three-stage DEA efficiency portfolio comparing with DEA one-stage efficiency portfolio to indicate which efficiency benchmark is better to get the excess return.
The results showed that the worst efficiency portfolio got the lowest rate of return, the portfolio with better efficiency didn’t absolutely have higher returns. However, the portfolio with better efficiency have less risk, the portfolio with worse efficiency have higher risk. According to the regression model, the best efficiency portfolio outperform than the worst efficient portfolio, but the excess return perform lower than the market. The reason causing the negative excess return may come from the emerging markets characteristics. Stock price may be affected by local information and political information that cause the general risk factors may not be able to obtain a positive excess return. However, it can still through the long-short strategy get the positive excess returns.
The result of three-stage DEA method is similar with DEA result. The most efficient portfolio outperform than the worst efficiency portfolio, and through a long-short strategy can get the excess return. According to the descriptive statistics, the three-stage DEA result has the better stock returns and lower risk.

目錄
指導教授推薦函 I
審定書 II
摘要 III
Abstract IV
銘謝 V
表目錄 VIII
圖目錄 VIII
第一章 緒論 1
第一節 研究動機與背景 1
第二節 研究目的 3
第三節 研究流程 4
第二章 文獻探討 6
第一節 效率評估與DEA資料包絡分析 6
第二節 傳統CAPM理論 7
第三節 Fama-French三因子模型 8
第四節 動能效果與Carhart四因子模型 10
第五節 效率與股價報酬率探討 11
第三章 研究方法 13
第一節 DEA資料包絡分析 13
第二節 DEA 三階段模型 16
第三節 效率迴歸模型 18
第四章 實證研究 25
第一節 研究對象與資料來源 25
第二節 變數選取與說明 26
第三節 DEA一階段與資產訂價模型迴歸結果 35
第四節 DEA三階段與資產訂價模型迴歸結果 41
第五章 結論與研究建議 49
第一節 結論 49
第二節 研究建議 51
參考文獻 52
授權書 55

表目錄
表 3- 1 三因子組合分類表 20
表 3- 2 動能因子組合分類表 23
表 4- 1 研究廠商家數 25
表 4- 2 DEA投入變數敘述統計 27
表 4- 3 DEA產出變數敘述統計 27
表 4- 4 2003年投入產出Pearson相關係數表 28
表 4- 5 2004年投入產出Pearson相關係數表 29
表 4- 6 2005年投入產出Pearson相關係數表 29
表 4- 7 2006年投入產出Pearson相關係數表 30
表 4- 8 2007年投入產出Pearson相關係數表 30
表 4- 9 2008年投入產出Pearson相關係數表 31
表 4- 10 2009年投入產出Pearson相關係數表 31
表 4- 11 2010年投入產出Pearson相關係數表 32
表 4- 12 DEA一階段組合敘述統計 35
表 4- 13 CAPM迴歸結果 37
表 4- 14 Fama-French三因子迴歸結果 39
表 4- 15 Carhart 4因子迴歸結果 40
表 4- 16 DEA三階段組合敘述統計 42
表 4- 17 DEA三階段CAPM迴歸結果 43
表 4- 18 DEA三階段Fama-French三因子迴歸結果 45
表 4- 19 DEA三階段Carhart 4因子迴歸結果 47
圖目錄
圖 1- 1 研究流程圖 5
圖 3- 1 射線投入差額和非射線投入差額 15

Alam, I., and Sickles, R. (1998). The relationship between stock market returns and technical efficiency innovations: evidence from the U.S. airline industry. Journal of Productivity Analysis, 9, 35-51.
Ball, R. (1978). Anomalies in relationships between securities’ yields and yield- surrogates. Journal of Financial Economics, 6, 103-126.
Banker, R. D., Charnes, A. & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30 (9), 1078-1092.
Banz, R. (1981). The relationship between return and market value of common stocks. Journal of Financial Economics, 9, 3-18.
Bhandari, L. C. (1988). Debt/equity ratio and expected common stock returns: empirical evidence. Journal of Finance, 43, 507-528.
Black, F. (1972). Capital market equilibrium with restricted borrowing. Journal of Business, 45, 444-445.
Black, F., M. Jensen & M. Scholes (1972). The capital asset pricing model: some empirical tests. in: M. Jensen ed.. Studies In the theory of capital markets (Praeger, New York, NY).
Carhart, M. (1997). On the persistence in mutual fund performance. Journal of Finance, 52, 57-82.
Charnes, A., Cooper, W. W. & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
Demerjian, P., Levy, B. & McVay, S. (2012). Quantifying managerial ability: a new measure and validity tests. Management Science, 58, 1229-1248.
Demsetz, H. (1973). Industry structure, market rivalry, and public policy. Journal of Law and Economics, 16, 1-9.
Fama, E., and French, K. (1992). The cross-section of expected stock returns. Journal of Finance, 47, 427-465.
Fama, E., and French, K. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3-56.
Fama, E., and French, K. (1995).Size and book-to-market factors in earnings return. Journal of Finance, 50, 131-155.
Fama, E., and Macbeth, J. (1973). Risk, return and equilibrium: empirical tests. Journal of Political Economy, 57, 1121-1152.
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, 120 (3), 253-281.
Fried, H. O., Lovell, C. A. K., Schmidt, S. S. & Yaisawarng, S. (2002). Accounting for environmental effects and statistical noise in data envelopment analysis. Journal of Productivity Analysis, 17, 157-174.
Frijns, B., Margaritis, D., & Psillaki, M. (2012). Firm efficy and stock returns. Journal of Productivity Analysis, 37, 295-306.
Habib, M. and A. Ljungqvist (2005). Firm value and managerial incentives: a stochastic frontier approach.” Journal of Business, 78, 2053 – 2093.
Jegadeesh, N., and Titman, S. (1993). Returns to buying winners and selling losers: implications for stock market efficiency. Journal of Finance, 48, 65-91.
Jegadeesh, N., and Titman, S. (2001). Profitability of momentum strategies: an evaluation of alternative explanations. Journal of Finance,56, 699-720.
Levy, R. A. (1967). Relative strength as a criterion for investment selection. Journal of Finance, 22, 595-610.
Lintner, J. (1965). The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets. Review of Economics and Statics, 47, 13-37.
Markowitz, H. (1952). Portfolio selection. Journal of Finance, 7, 77-91.
Newey, W., and West, K. (1987). A simple positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55, 703-708.
Nguyen, G., and Swanson, P. (2009). Firm characteristics, relative efficiency, and equity returns. Journal of Financial and Quantitative Analysis, 44, 213-236.
Peltzman, S. (1977). The gains and losses from industrial concentration. Journal of Law and Economics, 20, 229-263.
Rosenberg, B., Reid, K., & Lanstein, R. (1985). Persuasive evidence of market inefficiency. Journal of Portfolio Management, 11, 9-17.
Sharpe, W. F. (1964). Capital asset prices: a theory of market equilibrium under conditions of risk. Journal of Finance, 19, 425-442.
Shepherd, R. W. (1970). Theory of cost and production functions. Princeton University Press, Princeton, NJ.
Stattman, D. (1980). Book values and stock returns. The Chicago MBA: A Journal of Selected Papers, 4, 25-45.
Zhu, J. (2000). Multi-factor performance measure model with an application to Fortune 500 companies. European Journal of Operational Research, 123, 105-124.