不同情境樹模型下利率風險量化方法之研究-應用於現金流量測試法

Abstract

本研究探討風險基礎資本額(Risk-Based Capital，簡稱RBC)中利率風險之量化方式，比較台灣與美國RBC利率風險量化方式之異同處，並且仿照美國現金流量測試法(Cash Flow Testing)量化不同保單預定利率之生死合險之利率風險值，資產面架構於不同情境樹模型的模擬值，進而比較不同模型下產生資產報酬率和數值的特性以及利率風險值之比較。

主要結論與建議： 一、 保單預定利率越高，利率風險值越大；初始總保戶人數越多，利率風險值越大；資產面報酬率不佳，且保

The main issue of this thesis is to compare the interest rate risk in the RBC of Taiwan with that of the United States and calculate the interest rate risk factors of different guaranteed interest rate policies by Cash Flow Testing. The asset returns of Cash Flow Testing are generated by different event tree models. We compare the features and interest rate risk factors in different event tree models. The main conclusions and suggestions are as followings: First, we have higher interest rate risk factor for higher guaranteed interest rate. Also, the larger the policyholders, the larger the interest rate risk factor. When the asset returns are worse and fewer policyholders want to surrender, the interest rate risk factor will be higher. Moreover, we can find that the interest rate risk factors are totally different in different event tree models. Second, the simulated numbers of model 1 are more diversified and these of model 2 and 3are more centralized. Model 1 is suitable for estimating the interest rate risk and model 2 and model 3 are suitable for the issues about optimal asset allocations. Thirdly, the original estimation method of interest rate risk of the United States is based on Duration Matching and the formula of interest rate risk of Taiwan and Cash Flow Testing of the United States are based on Cash Flow Matching. We can find that the Cash Flow Matching can describe the interest rate risk much precisely and different models lead to different interest rate factors. We suggest that if the government wants to change the formula of interest rate risk, they can reserve the formula but let the returns of corporate be stochastic. It can let many companies calculate the interest rate risk under the same standard.