A stochastic possibilistic programming model for bank hedging decision problems

For a practical bank hedging decision optimization problem, interest rates and price of futures contract may involve both fuzziness and randomness. For subjective nature of satisfaction, maximum desired values of loan demand, deposit supply and ratio of desired loan to deposit are often fuzzy. In this study, the authors consider and solve a stochastic possibilistic programming model of bank hedging decision problems with the above characters. They first use the expected value to obtain an auxiliary possibilistic linear programming problem which is further resolved by use of β-level cut. An (crisp) auxiliary bi-objective linear programming model is then proposed and solved by the present augmented maximin approach. For illustration purpose, a numerical bank hedging decision problem is solved.