2014, Vol.25, No.2

Journal of Insurance and Finance 2023 KCI Impact Factor : 0.59

pISSN : 2384-3209
https://journal.kci.go.kr/kiri

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.

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.

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.