Mahboubeh Aalaei; Khadijeh Ebrahimnezhad
Abstract
In this article, fuzzy random variables are used to model interest rate uncertainty used in the calculation of whole life insurance premiums, and calculate the effect of this uncertainty on the price of life settlements. The fuzzy results obtained from deterministic and probabilistic pricing approaches ...
Read More
In this article, fuzzy random variables are used to model interest rate uncertainty used in the calculation of whole life insurance premiums, and calculate the effect of this uncertainty on the price of life settlements. The fuzzy results obtained from deterministic and probabilistic pricing approaches have been compared with the results of the stochastic approach. Also, the results have been analyzed for Iran life table, which has been issued to insurance companies since 1400, and for France life table, which was previously used by insurance companies. In addition, since 5-year survival probability for each cancers in Iran was lower than in the United States, the probability adjustment coefficient for Iran was higher than that of the United States. In addition, the interval obtained for the fuzzy probability price and the stochastic price for both Iran and France life tables are close to each other. But in most cases, the fuzzy price obtained based on the deterministic approach has a significant distance from the stochastic and fuzzy probability approaches. Also, the findings of the research indicate that the price calculated using the fuzzy deterministic approach for Iran life table is higher than France life table. While the results for fuzzy probabilistic approach and stochastic approach are completely opposite. In the other words, the price calculated for the Iran life table is lower than the France life table. This difference comes from the fact that the adjustment coefficients for these life tables are calculated for each person separately from related life tables.
Mahboubeh Aalaei
Abstract
In this paper, fuzzy set theory is implemented to model internal rate of return for calculating the price of life settlements. Deterministic, probabilistic and stochastic approaches is used to price life settlements in the ...
Read More
In this paper, fuzzy set theory is implemented to model internal rate of return for calculating the price of life settlements. Deterministic, probabilistic and stochastic approaches is used to price life settlements in the secondary market for the Iranian insurance industry. Research findings were presented and analyzed for whole life insurance policies using the interest rates announced in the supplement of Regulation No. 68 and Iranian life table, which recently has been issued to be used by insurance companies. Also, the results of three approaches were compared with surrender value, which indicates the surrender value is lower than the fuzzy price calculated based on the probabilistic and stochastic approaches and it is higher than the price calculated based on the deterministic approach. Therefore, selling life settlements in the secondary market in Iran based on calculated fuzzy price using probabilistic and stochastic approaches will benefit the policyholder. Also, the price is obtained in the form of an interval using the fuzzy sets theory and the investor can decide which price is suitable for this policy based on financial knowledge. Furthermore, in order to show validity of the proposed fuzzy method, the findings are compared to the results of using the random internal rate of return.