資本資產定價模型之檢驗，無論就計量方法或模型設定的探討，皆呈現多元論述。本文參酌 Gibbons (1982) 發展之多變量時間序列迴歸模型，重新檢視線性資本資產定價模型之有效性。考慮計量方法對誤差項分配的假設可能使得估計結果產生歧異，本研究同時採用「最大概似法」及「一般化動差法」進行參數估計，並針對截距項之估計結果進行聯合檢定。
　　本研究之實證樣本取自1935年至2004年間，美國 NYSE、AMEX 與 NASDAQ 三市場之超額月報酬資料。實證結果顯示，無論採用最大概似法或一般化動差法進行參數估計，其聯合檢定的結果皆拒絕 Sharpe-Lintner CAPM 對無風險利率之假設。而個別投資組合的期望報酬率與系統風險係數呈現顯著的正相關，顯示Beta係數雖具解釋能力，惟可能仍存有其他變數可以強化Beta係數未能反應的部分。此外，上述兩種計量方法獲得一致的結論，顯示在本研究的實證樣本中，最大概似法強勢分配的假設並未實際影響模型之參數估計與聯合檢定的結果。

This study re-examines the validity of the Sharpe-Lintner version of the capital asset pricing models (CAPM). Conventional maximum likelihood estimation and testing approach, e.g., Gibbons (1982), might suffer from incorrect distributional assumption and leads to incorrect conclusions. As a result, I employ the generalized method of moments approach which does not require restrictive distributional assumption and still provides consistent estimates and correct testing results. Using returns data on 25 portfolios sorted by size and BM ratios, the results indicate that the Sharpe-Lintner CAPM is not consistent with the real data.

目　錄
第一章　緒論..........................................	1
第二章　文獻探討....................................	4
　第一節　投資組合理論之文獻探討..........	4
　第二節　計量方法之文獻探討.................	7
第三章　投資組合理論模型.......................	12
　第一節　平均數－變異數分析.................	13
　第二節　分離理論.................................	16
　第三節　資本資產定價模型....................	17
第四章　研究方法.....................................	23
　第一節　最大概似法...............................	23
　第二節　一般化動差法...........................	28
　第三節　統計檢定..................................	33
第五章　實證結果與分析............................	36
　第一節　資料敍述與模型說明..................	36
　第二節　實證結果與分析.........................	41
第六章　結論與建議..................................	46
參考文獻.................................................	49

　　　　　　　　　　　　表　次
表一　樣本敍述統計量.................................	38
表二　最大概似法之估計結果.......................	42
表三　一般化動差法之估計結果....................	44
表四　聯合檢定結果....................................	45

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