Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1287/ijoc.2020.1016 | INFORMS JOURNAL ON COMPUTING |
Keywords | DocType | Volume |
sensitivity analysis, distortion risk measure, asymptotic analysis, functional limit theory | Journal | 33 |
Issue | ISSN | Citations |
4 | 1091-9856 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter W. Glynn | 1 | 1527 | 293.76 |
| Yijie Peng | 2 | 32 | 12.59 |
| Michael C. Fu | 3 | 1161 | 128.16 |
| Jian-Qiang Hu | 4 | 25 | 6.52 |