两类相依死亡率模型下住房反向抵押贷款的定价研究

发布时间：2017-12-31 21:37

本文关键词：两类相依死亡率模型下住房反向抵押贷款的定价研究　出处：《南京财经大学》2014年硕士论文　论文类型：学位论文

【摘要】：我国已经进入人口老龄化快速发展时期,已有老龄人口1.69亿,占总人口数的12%。随着我国人口老龄化速度的加快,加之我国社会保障的覆盖面还比较低,社会保障制度严重滞后等原因,使得传统的家庭养老方式或社会养老保险正面临严峻挑战。此外,2012年我国城市家庭现住房完全自有率为84.7%,但是大多数老年人的生活并不富裕。所以我们有必要通过借鉴英美等国的运作经验,结合自身的实际情况,探索出一条适合中国国情的道路,将有效减缓我国现阶段面临的养老压力。住房反向抵押贷款既是一种新型的金融产品,又是一种重要的养老工具。它指的是满足一定年龄的投保人将自己的房屋产权抵押给金融机构诸如保险公司等,这些金融机构依据投保人的年龄,对其预期寿命和健康状况进行预测,对住房价值、预期增值率和折旧等因素进行综合评估,一次性或多次向投保人支付养老费用,直至其去世。而在寿险实务中,在处理涉及到多个生命的问题时往往假设各个生命之间是独立的,但事实上,因为受某些相同因素的影响,风险并不是独立的,他们的生命之间总是或多或少存在一定的正相关性。因此,投保人的剩余寿命是不能假定为独立的,大数定律和中心极限定理不再适用,而两重生命住房反向抵押贷款定价模型涉及夫妻双方,现实生活中,他们的寿命不能假定为独立,因此,本文把这种正相依性应用到两重生命住房反向抵押贷款定价模型当中。本文首先介绍了Mitchell and Piggott精算模型和Frank Copula参数模型,然后在Mitchell and Piggott精算模型的基础上,借鉴国内的相关研究成果进行相应的改进,讨论了两种相依结构下精算定价模型,即在同单调相依性的假设下和Frank Copula参数模型假设下推导出每月领取固定金额的计算公式和年金给付逐年等量和按比例递增的年金领取额计算公式,并且分别设定单生命和两重生命精算定价模型。最后针对同单调相依结构下进行精算定价模型和Frank Copula参数模型下分别进行精算定价模拟计算并进行相应的敏感性分析,得出结论并展望。
[Abstract]:China has entered the period of rapid development of population aging, with the aging population of 169 million, accounting for 12 percent of the total population. With the accelerated pace of population aging in China. In addition, the coverage of social security in China is still relatively low, the social security system is lagging behind and other reasons, making the traditional family pension or social pension insurance is facing severe challenges. In 2012, the total ownership rate of urban households in China was 84.7%, but the majority of the elderly were not rich. So we need to learn from the operation experience of the United States and the United States and other countries. Combined with its own actual situation, to explore a suitable road for China's national conditions, will effectively reduce the current situation of China's pension pressure. Housing reverse mortgage is a new type of financial products. It is also an important pension tool. It refers to the policy holder who meets a certain age to mortgage his house property right to financial institutions such as insurance companies, these financial institutions based on the age of the policy holder. To predict their life expectancy and health status, to the housing value, expected appreciation rate and depreciation and other factors for a comprehensive assessment, one-time or multiple payments to the insured pension costs. Until his death... and in life insurance practice, in dealing with issues involving multiple lives, it is often assumed that each life is independent, but in fact the risk is not independent because of some of the same factors. There is always a certain positive correlation between their lives. Therefore, the residual life of the policy holder can not be assumed to be independent, and the law of large numbers and the central limit theorem are no longer applicable. The reverse mortgage pricing model of dual life housing involves both husband and wife. In real life, their life span can not be assumed to be independent, therefore. This paper applies this positive dependency to the reverse mortgage pricing model of dual life housing. Firstly, this paper introduces the Mitchell and Piggott actuarial model and Frank. Copula parameter model. Then on the basis of Mitchell and Piggott actuarial model, referring to the relevant domestic research results, the paper discusses the actuarial pricing model under two dependent structures. That is, under the assumption of monotone dependence and Frank. Under the assumption of Copula parameter model, the formula of calculating the fixed amount of monthly payment and the formula of annual equal amount and proportional increase of annuity payment are derived. The actuarial pricing models of single life and double life were established respectively. Finally, the actuarial pricing model and Frank were carried out under the same monotone dependent structure. The actuarial pricing simulation and sensitivity analysis were carried out under the Copula parameter model. Draw a conclusion and look forward to it.
【学位授予单位】：南京财经大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F299.23;F832.4;F224

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