基于模糊MC模型的保险定价研究
发布时间：2019-06-09 21:49
【摘要】：保险定价问题是保险学研究中的核心问题之一,传统的保险定价问题都是建立在概率统计与随机过程的理论基础之上。考虑到决策者对市场形式的主观判断具有主观性的特点,本文引入模糊数学的思想来处理保险定价问题。 一方面,以保险定价中经典的Myers-Cohn模型为基础,引入模糊变量,对经典模型进行模糊化处理,得到了关于模糊MC保费的方程,并运用模糊数的相关运算法则,通过迭代的方法求解模糊保费。求解模型得到的模糊保费给出了可接受的保费价格的范围,有利于决策者在可接受的范围内考虑多方面的因素,最终确定具体保费价格。 另一方面,针对经典的Myers-Cohn模型将保险公司所有税赋转嫁给投保人、加大投保人投资风险的缺陷,本文改进了原有模型,提出将保险公司的部分投资收益回馈给投保人,而最终体现在保费价格的下调。对于保险公司投资收益的估计,本文引入最优模糊投资组合的方法,以模糊满意约束度作为投资风险水平的衡量标准,在给定风险承受水平下,根据模糊数学的相关性质,将模糊规划模型转化为确定线性规划问题,求解最优收益率。 最后本文构造了一个能同时包含随机和模糊信息的隶属函数,其中,随机信息体现在最优收益率,而模糊信息体现在隶属函数的模糊程度,并将新形式的隶属函数引入到改进的模糊MC模型中,求解出能包含更多信息的保费价格。
[Abstract]:Insurance pricing problem is one of the core problems in insurance research. The traditional insurance pricing problem is based on the theory of probability statistics and stochastic process. Considering that the subjective judgment of market form by decision makers is subjective, this paper introduces the idea of fuzzy mathematics to deal with the problem of insurance pricing. On the one hand, based on the classical Myers-Cohn model in insurance pricing, fuzzy variables are introduced to fuzzify the classical model, and the equation of fuzzy MC premium is obtained, and the related algorithm of fuzzy number is used. The fuzzy premium is solved by iterative method. The fuzzy premium obtained by solving the model gives the range of acceptable premium price, which is helpful for decision makers to consider many factors in the acceptable range and finally determine the specific premium price. On the other hand, in view of the defect that the classical Myers-Cohn model passes on all the taxes of the insurance company to the policy holder and increases the investment risk of the policy holder, this paper improves the original model and proposes to return some of the investment income of the insurance company to the policy holder. And ultimately reflected in the reduction of premium prices. For the estimation of investment return of insurance companies, this paper introduces the optimal fuzzy portfolio method, takes the fuzzy satisfactory constraint degree as the measure standard of investment risk level, under the given risk bearing level, according to the related properties of fuzzy mathematics, The fuzzy programming model is transformed into a linear programming problem and the optimal rate of return is solved. Finally, a membership function which can contain both random and fuzzy information is constructed, in which the random information is embodied in the optimal rate of return, and the fuzzy information is embodied in the fuzzy degree of the membership function. The new form of membership function is introduced into the improved fuzzy MC model to solve the premium price which can contain more information.
【学位授予单位】：中南大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F840.4
本文编号：2495930
[Abstract]:Insurance pricing problem is one of the core problems in insurance research. The traditional insurance pricing problem is based on the theory of probability statistics and stochastic process. Considering that the subjective judgment of market form by decision makers is subjective, this paper introduces the idea of fuzzy mathematics to deal with the problem of insurance pricing. On the one hand, based on the classical Myers-Cohn model in insurance pricing, fuzzy variables are introduced to fuzzify the classical model, and the equation of fuzzy MC premium is obtained, and the related algorithm of fuzzy number is used. The fuzzy premium is solved by iterative method. The fuzzy premium obtained by solving the model gives the range of acceptable premium price, which is helpful for decision makers to consider many factors in the acceptable range and finally determine the specific premium price. On the other hand, in view of the defect that the classical Myers-Cohn model passes on all the taxes of the insurance company to the policy holder and increases the investment risk of the policy holder, this paper improves the original model and proposes to return some of the investment income of the insurance company to the policy holder. And ultimately reflected in the reduction of premium prices. For the estimation of investment return of insurance companies, this paper introduces the optimal fuzzy portfolio method, takes the fuzzy satisfactory constraint degree as the measure standard of investment risk level, under the given risk bearing level, according to the related properties of fuzzy mathematics, The fuzzy programming model is transformed into a linear programming problem and the optimal rate of return is solved. Finally, a membership function which can contain both random and fuzzy information is constructed, in which the random information is embodied in the optimal rate of return, and the fuzzy information is embodied in the fuzzy degree of the membership function. The new form of membership function is introduced into the improved fuzzy MC model to solve the premium price which can contain more information.
【学位授予单位】：中南大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F840.4
【参考文献】
相关期刊论文 前10条
1 郑文瑞,吴丹阳,方红;模糊随机方法在震灾风险评价中的应用[J];吉林大学学报(地球科学版);2002年02期
2 王波;史安娜;;DCF保险定价模型的模糊化及其应用[J];财经理论与实践;2006年05期
3 龙玉国;;寿险公司全面风险模糊综合评判[J];贵州工业大学学报(社会科学版);2006年02期
4 杜江;梁昕雯;;基于模糊评判法的责任保险中的道德风险评估[J];甘肃社会科学;2009年04期
5 王达布希拉图;容炳华;;一类广义不确定利率下的寿险净保费模型[J];广州大学学报(自然科学版);2012年03期
6 陈迪红;贾锐锐;;模糊数学在环境污染责任保险费率厘定中的运用[J];经济数学;2011年02期
7 孙伟;保险企业竞争力模糊综合评价方法[J];科学中国人;2001年08期
8 薛晔;黄崇福;;灾害风险评估中原始数据模糊不确定性的处理方法[J];太原理工大学学报;2009年05期
9 高井贵;赵明清;;模糊利率下的寿险精算模型[J];系统工程学报;2010年05期
10 刘亮;;基于模糊数学的车险风险决策评价方法[J];沿海企业与科技;2011年08期
相关博士学位论文 前1条
1 滕焕钦;财产保险公司风险预警研究[D];山东大学;2011年
，本文编号：2495930
本文链接：https://www.wllwen.com/jingjilunwen/bxjjlw/2495930.html
