Measuring And Securitization Of China’s Longevity Risk Based Onmortality Dependent Model

With the improvement of the living standard and the development of medication, the population average life expectancy has increased dramatically, resulting in a global issue, which is longevity risk. A lot of new methods of predicting mortality and pricing longevity bond are emerging around the world. But most of them show little consideration of the character of Chinese population and the limit of the data of the China’s mortality we can get. This article is mainly based on Lee-Carter model to predict mortality and do some modification. We extended the Lee-Carter model to a multi-country framework, which added a correlation of the residual in Lee-Carter model. Because of the deficiency and short time span, making a good use of this model is very important. In order to get the correlation of China and Taiwan, we first calculated the correlation between Taiwan and Austria、France、 Japan、Portugal、Spain、UK、USA, and put the average of them as the correlation of China and Taiwan. Later, we model a VECM(1) to further forecast kt and based on this we predicted the mortality of China for the following ten years. After we got the mortality, we used the KLD to compare the effectiveness and veracity between the KLD of real mortality and the traditional SVD and the KLD of real mortality and mortality forecast under VECM(1) considered dependence. The result shows that using VECM(1) under mortality dependence method is the most efficient way.Getting the mortality, we designed the longevity risk bond in the incomplete market to avoid risk. During the procedure, we employed the Wang’s transformation to achieve risk neutral, which improves the method of pricing longevity bond. At last, we designed a case to calculate the value of longevity risk bond using the function It gives us the value of male and female, with VF=9947285 and VM=9976451 respectively. This enhances the function and practicability of mortality forecasting model, which does a good to the development of financial and insurance industries.