本文以模擬實驗法比較四種預期報酬模式(市場模式(MM)、CAPM、三因子模式(3FM)及四因子模式(4FM))分別搭配OLS 估計式、GARCH 模式及其與OLS 混合在短期事件研究法中偵測異常報酬的能力。另外，也使用Jensen’s績效指標來評估上述後三種模式。研究發現：在傳統法架構下，OLS法並不比另兩種較複雜的估計式差；3FM 與4FM 略優於MM 和CAPM，因其有較低的估計偏誤和較小的型一錯誤，但其實MM 和CAPM 已有不錯的表現。在Jensen’s績效指標架構下，CAPM 優於3FM 和4FM，因其有較低的型一錯誤和較高的檢定力。但當事件日不確定及(或)異常報酬很小時，兩種架構的檢定力均偏弱。

This paper compares the performance of four expected return estimation models—the MM, CAPM, 3FM, and 4FM—separately using OLS estimator, GARCH model, and mix of OLS and GARCH—for finding AR in traditional short-horizon event study, using simulation experiments. Moreover, Jensen’s performance index is employed to evaluate the last three models. The conclusions are that under a traditional framework, OLS is not inferior to the other complex estimators. 3FM and 4FM somewhat dominate the MM and CAPM because of lower estimation bias and slightly smaller Type I error, though the last two models’performance is already satisfactory. Under Jensen’s performance index, CAPM is superior to 3FM and 4FM due to lower Type I error and higher power. Both event-study frameworks have weak power in experiencing uncertain event day and/or tiny AR.