本文主要探究Bornholt (2007)透過修正傳統CAPM均異效率（mean-variance）架構缺陷而得之報償貝它模型（reward beta model）於台灣股票市場之表現，並以此與傳統CAPM實證結果差異作出討論。本文亦試圖在橫斷面迴歸分析上，多引入分量迴歸（Quantile Regression）計量方法，希望透過分量迴歸之特點，以不分組方式直接對個股股票進行實證分析，以期更精確檢視報償貝它模型、CAPM理論宣稱是否成立，及相關風險因子在整體樣本中對於股票報酬之影響力。
實證結果發現，台灣股市並不能完全符合CAPM或是報償貝它模型之理論預期。在各風險因子對於橫斷面股市報酬之解釋力上，以CAPM貝它值而言，在未區分市場投資組合超額報酬率時，普通最小平方（Ordinary Least Square, OLS）均值估計結果發現該風險因子對橫斷面股市報酬是不具有顯著解釋力；然而進一步以分量迴歸檢視，卻發對於相對高（低）報酬率股票，其風險與報酬間為一顯著正（負）向關係。進一步區分正、負市場投資組合超額報酬率，OLS均值估計結果顯示在「正（負）報酬市場」下，CAPM貝它值與股票報酬為一正（負）向關係，表示在不同市場狀況下，風險與報酬將呈現兩股反向力量；然而在分量迴歸檢視下，卻發現到在給定「正（負）報酬市場」條件下，對於相對低（高）報酬率股票而言，CAPM貝它值是不具有顯著解釋力。本文也發現特定期間下股票報酬的高低，不僅受到該股票CAPM貝它值所影響，且其風險貼水程度，將與該股票報酬呈現正向關係。然而對於台灣股票市場而言，報償貝它值則不具顯著解釋力。

This paper investigates the empirical study of reward beta model in Taiwan stock market and compares the results with traditional CAPM. We demonstrate the relation between stock return and risk by utilizing the techniques of Ordinary Least Square (OLS) and Quantile Regression (QR). By the advantage of QR, we try to test individual stocks directly without grouping and to check whether the theorems of CAPM and reward beta model can be realized in actual financial market. We also intend to confirm whether the market price of risk differs under different conditional distribution.
The empirical results suggest that Taiwan stock market cannot meet the theorems of CAPM and reward beta model. For CAPM beta, there is no significant risk premium by OLS, but when using the technique of QR, we can detect that the market price of CAPM beta is significant in both tails of the conditional distribution – negative for the firms that underperform and positive for the firms that overperform. When the sample is split into periods according to whether the excess market return is positive or negative, there is a significant relationship between CAPM beta and return from the OLS method. We also detect this by QR and find out that when the excess market return is positive (negative), there is no significant relation between CAPM beta and the return for the firms that underperform (overperform). This paper also finds out that there is different risk premium for the firms under different conditional distribution. As for reward beta, it has no significant influence on the stock return from the OLS and QR technique.

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