半方差约束下的模糊随机收益率贷款组合优化模型

Optimization Model of Loan Portfolio with Fuzzy Random Return Rates under Semivariance Constraint

银行贷款的收益率在很多情况下具有模糊随机性。将贷款收益率刻画为模糊随机变量,使用半方差作为风险度量方式,建立半方差约束下的模糊随机收益率贷款组合优化模型,目的是在一定的半方差约束和置信水平下,最大化贷款组合的收益率不小于预置收益率的本原机会测度。应用集成模糊随机模拟、神经网络、遗传算法的混合智能算法进行求解,最后通过实例验证了模型和算法的可行性和有效性。

The return rates of loan in bank often have fuzzy random characteristic in many cases, this paper described the return rates as fuzzy random variables, used semivariance as the risk measure method, constructed the optimization model of loan portfolio with fuzzy random return rates under semivariance constraints. The purpose of the model is to maximize the primitive chance measure when the total return rate is no less than the preset value at a given confidence level under semivariance constraints. The hybrid intelligent algorithm was employed to solve the model, the algorithm integrates fuzzy random simulation, neural network and genetic algorithm. At last, numerical examples illustrate the feasibility and effectiveness of the model and the algorithm.