Computing Sensitivities for Distortion Risk Measures
针对扭曲风险度量，提出一种基于广义似然比估计量的新敏感性估计量，并建立其中心极限定理，适用于不连续样本路径和扭曲函数。
Distortion risk measure, defined by an integral of a distorted tail probability, has been widely used in behavioral economics and risk management as an alternative to expected utility. The sensitivity of the distortion risk measure is a functional of certain distribution sensitivities. We propose a new sensitivity estimator for the distortion risk measure that uses generalized likelihood ratio estimators for distribution sensitivities as input and establish a central limit theorem for the new estimator. The proposed estimator can handle discontinuous sample paths and distortion functions.