Kernel estimation for quantile sensitivities
Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Title of host publication | Proceedings - Winter Simulation Conference |
| Pages | 941-948 |
| Publication status | Published - 2007 |
| Externally published | Yes |
Publication series
| Name | |
|---|---|
| ISSN (Print) | 0891-7736 |
Conference
| Title | 2007 Winter Simulation Conference (WSC'07) |
|---|---|
| Place | United States |
| City | Washington |
| Period | 9 - 12 December 2007 |
Link(s)
Abstract
Quantiles, also known as value-at-risk in financial applications, are important measures of random performance. Quantile sensitivities provide information on how changes in the input parameters affect the output quantiles. In this paper, we study the estimation of quantile sensitivities using simulation. We propose a new estimator by employing kernel method and show its consistency and asymptotic normality for i.i.d. data. Numerical results show that our estimator works well for the test problems. © 2007 IEEE.
Citation Format(s)
Kernel estimation for quantile sensitivities. / Liu, Guangwu; Hongh, L. Jeff.
Proceedings - Winter Simulation Conference. 2007. p. 941-948 4419690.Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
