自2003年起隨著台灣壽險業國外投資比率不斷提高，至2010年底國外投資比率已達34.47%，因此為了探討壽險業國外投資與績效並了解相關因素之影響，本研究檢視壽險公司之市占率和各險種保費收入比率與國外投資比率之間的關係，同時亦檢視美國政府十年期公債殖利率與投資報酬率之間是否具有正向關係。另一方面，探討已公開發行公司是否因需揭露財務報表而與未公開發行公司之間在國外投資比率和投資績效上有所差異。 本文以2004年至2008年台灣25家壽險公司的長期資料（longitudinal data），分析總合（pooled）、固定效果(fixed effects)和隨機效果（random effects）迴歸模型，並檢視模型之適合性檢定。另因反應變數之密度估計具長尾之特性，所以亦使用Koenker（2004）和Geraci and Bottai（2007）提出的長期資料分量迴歸（quantile regression for longitudinal data）分析作為探討。實證結果顯示，若壽險公司的市占率愈高，則其資產配置於國外的比重亦相對地提高，且壽險和年金險比率與國外投資比率之間呈現顯著地正相關；此外，公開發行公司的國外投資比率顯著高於未公開發行公司。在投資績效方面，美國政府十年期公債殖利率與投資報酬率之間為顯著的正相關。 長期資料分量迴歸分析實證結果顯示，當使用Koenker（2004）提出之方法時，則一般（ordinary）分量迴歸在50%、75%和90%條件分量下，隨著樣本期間年度的增加，壽險業的國外投資報酬率相對地上升；在10% 和25% 條件分量下，壽險公司市占率與國外投資報酬率之間是顯著的正相關。而使用Geraci and Bottai（2007）提出之隨機效果分量迴歸方法時，在50%條件分量下，國外投資比率與國外投資報酬率之間為顯著地正相關，再者匯率風險將降低台灣壽險業國外投資的意願，然而實行避險策略是有益於投資績效的提升。 / The foreign investment ratio for the life insurance industry in Taiwan has risen constantly since 2003 and reached 34.47% in 2010. In order to explore foreign investment and performance, and understand the impact of relevant factors in the life insurance industry, this study examines the relationship between the market shares of life insurance companies, types of premium income ratio and the foreign investment ratio. Simultaneously, this study also examines the relationship between the 10-year US Treasury Bond Yield Currency and investment return.On the other hand, we explore whether the difference between the publicly traded companies and non-publicly traded companies on the foreign investment ratio and the investment performance. In this dissertation, we analyze 25 Taiwanese life insurance companies between 2004 and 2008 using the pooled, fixed effects and random effects regression model. Due to the distribution of the response variable is characterized by the long tail, we explore the use of the quantile regression for longitudinal data by Koenker(2004)and Geraci and Bottai(2007). The empirical results show that the more market share of life insurance companies, the higher foreign investment ratio and there is significantly positive correlation between the life insurance, annuity ratio and the foreign investment ratio. In addition, the publicly traded company's foreign investment ratio is significantly higher than non-publicly traded company. In terms of investment performance, it’s significantly positive correlation between the U.S. 10-year Treasury Bond Yield Currency and return on investment. The empirical results about quantile regression for longitudinal data show that the return on foreign investment relatively enhance for the life insurance industry with the increase of the year during the sample period under the 50%,75% and 90% conditional qauntile when using the ordinary quantile regression proposed by Koenker(2004). There is significantly positive correlation between the market share and the return on foreign investment under the 10% and 25% conditional qauntile. When using the method proposed by Geraci and Bottai(2007), there is significantly positive correlation between the foreign investment ratio and the return on foreign investment under the 50% conditional qauntile. Furthermore, exchange rate risk will reduce the foreign investment willingness of the life insurance industry in Taiwan. However, the implementation of the hedging strategy is beneficial to enhance investment performance for the life insurance industry.

資本資產定價模型 (CAPM) 由Sharp (1964)、Lintner (1965)及Black (1972)發展出後，近年來已被廣泛的應用於衡量證券之預期報酬率與風險間之關係。一般而言，衡量結果之估計有兩個階段，首先由時間序列分析估計出貝它(beta)係數，然後再檢定廠商或投資組合之平均報酬率與貝它係數之關係。 Fama與MacBeth (1973)利用最小平方法估計貝它係數，再將由橫斷面迴歸方法所得出之斜率係數加以平均後，以統計t-test檢定之。然而以最小平方法估計係數，其估計值很容易受離群值之影響，因此本研究考慮以穩健估計 (robust estimator)來避免此一問題。另外，本研究亦將長期資料分析 (longitudinal data analysis) 引入CAPM裡，期望能檢定貝它係數是否能確實有效地衡量出系統性風險。 論文中以台灣股票市場電子業之實證分析來比較上述不同方法對CAPM的結果，資料蒐集期間為1998年9月至2001年12月之月資料。研究結果顯示出，穩健估計相對於最小平方法就CAPM有較佳的解釋力。而長期資料分析模型更用來衡量債券之超額報酬部分，是否會依上、中、下游或公司之不同而不同。 / The Capital Asset Pricing Model (CAPM) of Sharp (1964), Lintner (1965) and Black (1972) has been widely used in measuring the relationship between the expected return on a security and its risk in the recent years. It consists of two stages to estimate the relationship between risk and expected return. The first one is that betas are estimated from time series regressions, and the second is that the relationship between mean returns and betas is tested across firms or portfolios. Fama and MacBeth (1973) first used ordinary least squares (OLS) to estimate beta and took time series averages of the slope coefficients from monthly cross-sectional regressions in such studies. However it is well known that OLS is sensitive to outliers. Therefore, robust estimators are employed to avoid the problems. Furthermore, the longitudinal data analysis is applied to examine whether betas over time and securities are the valid measure of risk in the CAPM. An empirical study is carried out to present the different approaches. We use the data about the Information and Electronic industry in Taiwan stock market during the period from September 1998 to December 2001. For the time series regression analysis, the robust methods lead to more explanatory power than the OLS results. The linear mixed-effect model is used to examine the effects of different streams and companies for the security excess returns in these data.