Abstract
In this paper, we consider a mean---variance portfolio optimization problem for a fuzzy discrete-time insurance risk model. The model consists of independent, identically distributed net losses considered within successive time periods, and incorporates investment incomes from a two-asset portfolio. More precisely, in the beginning of each period, the surplus is invested in both a risk-free bond with fixed interest, and a risky stock with fuzzy return rate. Our purpose is to determine the proportion invested in the stock that maximizes the insurer's expected wealth, while reducing his risks. Therefore, for this fuzzy model, we formulate mean---variance optimization problems that also include constraints on ruin, and we present a method for determining the resulting optimal proportion to be invested in the risky stock. This method is illustrated in a numerical study in which the fuzzy return rate is considered to be an adaptive fuzzy number that generalizes the well-known trapezoidal fuzzy number.
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