TY - GEN
T1 - Kernel estimation for quantile sensitivities
AU - Liu, Guangwu
AU - Hongh, L. Jeff
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=49749137009&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-49749137009&origin=recordpage
U2 - 10.1109/WSC.2007.4419690
DO - 10.1109/WSC.2007.4419690
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 1424413060
SN - 9781424413065
SP - 941
EP - 948
BT - Proceedings - Winter Simulation Conference
T2 - 2007 Winter Simulation Conference (WSC'07)
Y2 - 9 December 2007 through 12 December 2007
ER -