由於醫療技術進步及政府對公共衛生的重視，延長了人類的壽命，加上生育率下降，世界各國紛紛邁入高齡化社會，這是全球所共同面對的課題。對販售年金險的壽險公司而言，為避免長壽風險帶來的損失，勢必應擬定一套健全的避險策略。然而，自然避險或證券化商品皆有實施的困難度及缺點，加上已有許多研究發現，人口統計變數與股票溢酬具有相關性，故本研究採用美國、日本、英國、德國及法國五個國家的死亡率數據參考Lee-Carter模型及經濟變數資料，配合資本資產訂價模型(CAPM)，期望利用有別於傳統生命表的動態死亡率模型，可更有效地找出死亡率變動與股票溢酬之間的關聯性，並在高齡化的趨勢下，可使壽險公司在風險管理上找到新的突破，提供壽險公司規避死亡率變動風險的另一種選擇，提升整體的避險效果。
本研究結果顯示，以G5的縱橫資料分析時，未預期死亡率與股票溢酬之間無顯著相關；以各國資料分析時，僅在累積未來三年及累積未來五年有少數呈顯著相關。表示，在Lee-Carter模型下，未預期死亡率與股票溢酬並無顯著關聯存在，似乎意味著當壽險公司使用動態的死亡率模型進行商品定價後，所產生的未預期死亡率風險可能無法透過資本市場來規避。另一方面，由於Lee-Carter模型所產生的未預期死亡率非常小，或許可利用費率調整的方式，將未預期死亡率風險反應於保費之中。

Because of the advances in health technology and of the improvement of public health, human life expectancy has been increasing significantly. Moreover, recent fertility declines have been more rapidly around the world, so ageing is a challenge for the whole world. In order to avoid the loss of longevity risk, life insurance companies need to develop robust hedging strategies. However, there are some difficulties and shortcomings for the insurance companies to execute nature hedge or securitization. 
Many researches have proved that links between stock premium and demographic characteristics, so this paper analyzes mortality rates of USA, Japan, England, Germany, and France over the period from 1950 to 2010 refer to the Lee-Carter model, economic variables, and CAPM. By using the dynamic mortality model different from traditional life table, we expect to find the links between stock premium and demographic characteristics and to provide another selection for the life insurance companies to hedge the risk of mortality changes.
According to the result from analyzing the five countries, it is no significant correlation between stock premium and demographic characteristics. By analyzing each country, there is some correlation only for three years and five years from now.
Hence, when the life insurance companies use dynamic mortality model, it is easily for them to predict the long-term trends because there is no significant correlation between stock premium and demographic characteristics. When the companies consider demographic risk to develop hedge strategies, they do not need to consider capital market instruments. Also, while designing insurance policies, the companies could put factors of demographic risk in to consideration and could increase the premium to disperse risks.

第一章 緒論................................................................................................................1
第一節 研究背景................................................................................................1
第二節 研究動機與目的....................................................................................3
第二章 文獻回顧........................................................................................................5
第一節 死亡率模型之發展................................................................................5
第二節 死亡率變動對資本市場報酬之影響....................................................8
第三章 研究方法......................................................................................................12
第一節 死亡率模型..........................................................................................12
第二節 研究假說..............................................................................................14
第三節 實證模型..............................................................................................16
第四節 資料來源與變數定義..........................................................................18
第五節 實證方法..............................................................................................21
第四章 實證結果......................................................................................................24
第一節 敘述性統計..........................................................................................24
第二節 G5 實證結果........................................................................................40
第三節 各國實證結果......................................................................................42
第五章 結論與建議..................................................................................................46
參考文獻......................................................................................................................47
附錄..............................................................................................................................49

圖1-1 G5與台灣之零歲平均餘命直條圖	1
圖1-2 G5與台灣之生育率直條圖	1
圖1-3 G5與台灣之扶養比、扶幼比及扶老比	2
圖4-1 各變數散佈圖(法國)	27
續圖4-1 各變數散佈圖(法國)	28
續圖4-1 各變數散佈圖(德國)	29
續圖4-1 各變數散佈圖(德國)	30
續圖4-1 各變數散佈圖(日本)	31
續圖4-1 各變數散佈圖(日本)	32
續圖4-1 各變數散佈圖(英國)	33
續圖4-1 各變數散佈圖(英國)	34
續圖4-1 各變數散佈圖(美國)	35
續圖4-1 各變數散佈圖(美國)	36

表3-1 單根檢定	21
表4-1  各變數敘述性統計表	25
續表4-1 各變數敘述性統計表	26
表4-2 各國參數間相關係數矩陣	37
續表4-2 各國參數間相關係數矩陣	38
續表4-2 各國參數間相關係數矩陣	39
表4-3  G5實證結果	41
表4-4 預測未來一年各國比較股票溢酬實證結果	43
表4-5 累積未來三年各國比較股票溢酬實證結果	44
表4-6 累積未來五年各國比較股票溢酬實證結果	45
附表1-1  Lee-Carter死亡率模型配適參數表( 、 )	49
附表1-2  Lee-Carter死亡率模型配適參數表( )	49
續附表1-2  Lee-Carter死亡率模型配適參數表( )	50
續附表1-2  Lee-Carter死亡率模型配適參數表( )	51
續附表1-2  Lee-Carter死亡率模型配適參數表( )	52
續附表1-2  Lee-Carter死亡率模型配適參數表( )	53
附表2 資料匯整表	54
附表3 各參數國家間相關係數矩陣	56
續附表3 各參數國家間相關係數矩陣	57

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