熵平衡损失下的信度保费

通过引入具有非对称性的平衡损失函数, 给出在该损失函数下的信度保费和最优信度保费及信度因子的非参数估计, 并通过随机模拟验证了所给方法的可行性. 结果表明, 这种新的非对称损失函数比对称损失函数能更好地衡量风险, 更公平地索取保费.

Credibility Premiums under Entropy-Balanced Loss Function

The authors introduced the asymmetry of balanced loss function gave the credibility premium and optimum credibility premium under this loss function. At the same time, we also gave the non parametric estimation of the credibility factor, and stochastic simulation to verify the feasibility of the method. Compared with the symmetric loss function, this asymmetric loss function can better measure risk, and more fairly obtain premiums.