Journal of Insurance and Finance 2021 KCI Impact Factor : 0.67

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pISSN : 2384-3209
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2014, Vol.25, No.2

  • 1.

    Optimizing an Insurance Company's Portfolio with a Consideration of the RBC constraint

    최창희 | 2014, 25(2) | pp.3~32 | number of Cited : 6
    Abstract PDF
    This paper presents a mathematical formulation of a portfolio optimization problem that maximizes an insurance company's mean-variance utility function subject to the RBC requirement constraint, explaining how its optimal solution can be obtained. In addition, this research investigates how the changes in critical factors(such as risk-aversion factor, RBC requirement level and insurance company's capital level) influence the insurance company's optimal portfolio and investment profitability. Test results of this paper can be summarized as the following. First, increasing the RBC ratio significantly reduces the profitability of an insurer. Second, maintaining superfluous amount of capital within an insurance company can cause the investment-wise inefficiency. Third, it is possible that an insurance company can reduce its portfolio's volatility, while maintaining profitability by rebalancing its portfolio.
  • 2.

    Assessing Effects of the Policy Coordination between Monetary and Macroprudential Policy

    Donghun Joo | 2014, 25(2) | pp.33~71 | number of Cited : 4
    Abstract PDF
    This study assesses the effects of policy coordination between monetary and macroprudential policy using a new Keynesian DSGE model which includes financial sector explicitly. Monetary policy is implemented with a short term interest rate; on the other hand, macroprudential policy is implemented with loan to value(LTV) ratio or countercyclical capital buffer(CCB). Adding a new macroprudential policy tool to the economy improves the policy effectiveness in pursuing price and financial stability at the same time, though the price stability is hampered compared with an economy where the price stability was the only aim of the policy authority. Coordinated policy implementation turns out to be superior to uncoordinated one except the case in which CCB responds to cost shock as a macroprudential policy tool. As there exists the possibility of conflict between monetary and macropudential policy aims, clear governance system for the policy coordination is necessary.
  • 3.

    A Method of Hedging Mortality Rate Risks in Endowment Product Development

    Kim, Changki , Yang Ho Choi | 2014, 25(2) | pp.73~109 | number of Cited : 1
    Abstract PDF
    Forecasting mortality rate changes in the future is important and necessary for insurance businesses. An interesting observation is that mortality rates for a few age groups have improved recently and that other mortality rate risks may exist. If the life table constructed from a mortality model, which predicts mortality rates lower than those actually experienced by the life insurance policy holders, then the company will face losses from the sales of life insurance contracts. As a hedging strategy, the insurance company may promote the sale of polices, such as annuities or pure endowments, to offset the losses from the life insurance sales. We present a method of hedging mortality rate risks for the development of endowment policies using the hedge ratios of pure endowment in order to offset the losses from term life insurance. We also demonstrate a hedging strategy using the stochastic force of a mortality model, which is resulted from Malliavin calculus.
  • 4.

    A Study on Profit Analysis of Variable Life Insurance by Nested Stochastic Modeling

    심현우 | 2014, 25(2) | pp.111~137 | number of Cited : 1
    Abstract PDF
    For variable life insurance with GMXB(Guaranteed Minimum Benefit), the reserves for GMXB as a component of profit analysis are evaluated using stochastic scenario models, but the profit analysis as a whole is still performed via deterministic modeling methodologies. In this study, we recognize limitation of the above one-step methodology where stochastic modeling is applied only to reserves for GMXB; therefore, we extend it and develop principle-based nested stochastic modeling and then adapt it to profit analysis of variable life insurance. The detailed analysis reveals that the nested stochastic modeling eliminates the arbitrariness of best estimate assumptions arising from deterministic models and that the probability distribution of profit is asymmetric. Also, we show that the error in profit margin estimation can be reduced by fully-recalculating nested stochastic modeling, which recalculates the reserves for GMDB with new current market information loaded. The recalculation period of one year is found to be sufficient for the purpose of profit analysis of variable insurance.