報酬與風險一直為投資人所關切的議題。本研究依據Fama and French(1992)的三因子模型為研究模型的基本架構，加入近年來波動性研究都將其重心擺在其上的獨特性波動風險因子，本文使用過去未討論過的GARCH(1,1)配置三因子殘差變異數作為獨特性波動風險因子，形成四因子資本資產定價模型，試探討此四因子模型對於股票報酬的關聯性。本研究方法以Panel data模型進行分析研究，將檢定結果加以比較三因子模型與四因子模型是否有何差異。
	本研究結果顯示：在三因子模型中，所有風險因子皆為顯著且具有解釋能力；而四因子資本資產定價模型中，加入了獨特性波動風險因子，所有變數仍然皆為顯著且具有解釋能力，並且四因子模型的判定係數較三因子模型高，因此可以得知，四因子模型的配適能力較三因子模型好，並且獨特性波動風險因子存在於台灣股票市場，對於股票報酬可以更具有解釋能力，此為一新貢獻。
	與被解釋變數的關聯性方面，研究結果得知貝它係數與淨值市價比對股票報酬率呈現負向關係，而規模效果與股票報酬率為正向關係，其與過去文獻的結果有不同的論調，然而，這可能是因為資料本質的不同、選取時間的長度不同、亦或是研究方法的不同，因而產生不同的影響。而新解釋變數─獨特性波動風險因子與股票報酬率為正向關係，表示獨特性的波動越大，則股票報酬率將會越高，此與過去研究發現有相同的結果。

In this paper we follow Fama and French (1992). We employ the common three risk factors in Fama and French (1992) and take another new risk factor- Idiosyncratic Volatility Risk (called IVR) in our model. We want to know the relationship among these four risk factors and the stock return and compare the results of the three-factor model with the four-factor model. We analyze our empirical data with Panel Data model. The sample period is from 1996 to 2006. In summary, all factors are significant in explaining stock returns in the three–factor model. In the four-factor modal, even we take IVR in our model; all risk factors are still significant in explaining stock returns. Moreover, the   in the four-factor modal is higher than in the three–factor model. In this paper, we find there is negative relation between Beta (or BE/ME) and stock return. Besides, we find there is positive relation between Market value and stock return. The other factor-IVR has positive relation with stock return as well. Our result is the same with the result from Chiang (2003).This is, the higher the idiosyncratic volatility of the Taiwan listed stocks is, the higher the return of the Taiwan listed stocks increases.

第一章 緒論 …………………………………………………………………………1
第一節 研究動機與目的…………………………………………………………1
第二節 研究流程…………………………………………………………………3
第三節 研究架構…………………………………………………………………4

第二章 文獻探討 ……………………………………………………………………5
第一節 股票報酬單一風險因子及多風險因子相關文獻探討  ………………5
弟二節 獨特性風險因子相關文獻探討 ………………………………………13
第三節 Panel data模型相關文獻探討 ………………………………………16

第三章 研究方法……………………………………………………………………17
第一節 研究模型的選取 ………………………………………………………17
第二節 變數的定義及概念 ……………………………………………………32
第三節 變數衡量方式 …………………………………………………………35
第四節 資料檢定 ………………………………………………………………36

第四章 實證結果分析………………………………………………………………39
第一節 資料來源與處理 ………………………………………………………39
第二節 估計模型之介紹 ………………………………………………………41
第三節 Panel data模型之分析 ………………………………………………43

第五章 結論與建議…………………………………………………………………52
第一節 研究結論 ………………………………………………………………52
第二節 研究限制 ………………………………………………………………54
第三節 研究建議 ………………………………………………………………54

參考文獻 ……………………………………………………………………………55

表目錄
【表4-1】	應變數與解釋變數之基本統計量表………………………………39
【表4-2】	各變數原始序列單根檢定結果……………………………………40
【表4-3】	各變數一階差分序列單根檢定結果………………………………41
【表4-4】	Panel Data三因子模型選取結果…………………………………45
【表4-5】	Panel Data四因子模型選取結果…………………………………46
【表4-6】	三因子模型之檢定結果……………………………………………46
【表4-7】	四因子模型之檢定結果……………………………………………49


圖目錄
【圖1-1】	研究流程圖 …………………………………………………………3

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