A nonparametric approach to calculating value-at-risk

Insurance: Mathematics and Economics - Tập 52 - Trang 255-262 - 2013
Ramon Alemany1, Catalina Bolancé1, Montserrat Guillén1
1Department of Econometrics, Riskcenter-IREA, University of Barcelona, Av. Diagonal, 690, 08034 Barcelona, Spain

Tài liệu tham khảo

Alemany, R., Bolancé, C., Guillén, M., 2012. Nonparametric estimation of value-at-risk. XREAP Working Paper series 2012-19, University of Barcelona 19, pp. 1–28. Altman, 1995, Bandwidth selection for kernel distribution function estimation, Journal of Statistical Planning and Inference, 46, 195, 10.1016/0378-3758(94)00102-2 Artzner, 1999, Coherent measures of risk, Mathematical Finance, 9, 203, 10.1111/1467-9965.00068 Azzalini, 1981, A note on the estimation of a distribution function and quantiles by a kernel method, Biometrika, 68, 326, 10.1093/biomet/68.1.326 Bolancé, 2010, Optimal inverse beta(3, 3) transformation in kernel density estimation, SORT-Statistics and Operations Research Transactions, 34, 223 Bolancé, 2012, A nonparametric approach to analysing operational risk with an application to insurance fraud, The Journal of Operational Risk, 7, 57, 10.21314/JOP.2012.103 Bolancé, 2012 Bolancé, 2003, Kernel density estimation of actuarial loss functions, Insurance: Mathematics and Economics, 32, 19, 10.1016/S0167-6687(02)00191-9 Bolancé, 2008, Inverse beta transformation in kernel density estimation, Statistics & Probability Letters, 78, 1757, 10.1016/j.spl.2008.01.028 Bolancé, 2008, Skewed bivariate models and nonparametric estimation for cte risk measure, Insurance: Mathematics and Economics, 43, 386, 10.1016/j.insmatheco.2008.07.005 Bowman, 1998, Bandwidth selection for smoothing of distribution function, Biometrika, 85, 799, 10.1093/biomet/85.4.799 Buch-Larsen, 2005, Kernel density estimation for heavy-tailed distributions using the Champernowne transformation, Statistics, 39, 503, 10.1080/02331880500439782 Cai, 2008, Nonparametric estimation of conditional VaR and expected shortfall, Journal of Econometrics, 147, 120, 10.1016/j.jeconom.2008.09.005 Dhaene, 2006, Risk measures and comonotonicity: a review, Stochastic Models, 22, 573, 10.1080/15326340600878016 Eling, 2012, Fitting insurance claims to skewed distributions: are the skew-normal and skew-student good models?, Insurance: Mathematics and Economics, 51, 239, 10.1016/j.insmatheco.2012.04.001 Fan, 2003, Semiparametric estimation of value-at-risk, Econometrics Journal, 6, 261, 10.1111/1368-423X.t01-1-00109 Guillén, 2011, Modelling losses and locating the tail with the pareto positive stable distribution, Insurance: Mathematicsand Economics, 49, 454, 10.1016/j.insmatheco.2011.07.004 Harrell, 1982, A new distribution-free quantile estimator, Biometrika, 69, 635, 10.1093/biomet/69.3.635 Hill, 1975, A simple general approach to inference about tail of a distribution, Annals of Statistics, 3, 1163, 10.1214/aos/1176343247 Jones, 2007, Risk measures, distortion parameters, and their empirical estimation, Insurance: Mathematics and Economics, 41, 279, 10.1016/j.insmatheco.2006.11.001 Jorion, 2007 Kim, 2010, Bias correction for estimated distortion risk measure using the bootstrap, Insurance: Mathematics and Economics, 47, 198, 10.1016/j.insmatheco.2010.05.001 Krätschmer, 2011, Sensitivity of risk measures with respect to the normal approximation of total claim distributions, Insurance: Mathematics and Economics, 49, 335, 10.1016/j.insmatheco.2011.05.004 Kupiec, 1995, Techniques for verifying the accuracy of risk measurement models, Journal of Derivatives, 3, 73, 10.3905/jod.1995.407942 Lopez, 2012, A generalization of the Kaplan–Meier estimator for analyzing bivariate mortality under right-censoring and left-truncation with applications in model-checking for survival copula models, Insurance: Mathematics and Economics, 10.1016/j.insmatheco.2012.07.009 McNeil, 2005 Peng, 2012, Jackknife empirical likelihood method for some risk measures and related quantities, Insurance: Mathematics and Economics, 51, 142, 10.1016/j.insmatheco.2012.03.008 Reiss, 1981, Nonparametric estimation of smooth distribution functions, Scandinavian Journal of Statistics, 8, 116 Reiss, 1997 Ruppert, 1994, Bias reduction in kernel density estimation by smoothed empirical transformation, Annals of Statistics, 22, 185, 10.1214/aos/1176325365 Sarda, 1993, Smoothing parameter selection for smooth distribution functions, Journal of Statistical Planning and Inference, 35, 65, 10.1016/0378-3758(93)90068-H Sheather, 1990, Kernel quantile estimators, Journal of the American Statistical Association, 85, 410, 10.1080/01621459.1990.10476214 Silverman, 1986 Swanepoel, 2005, A new kernel distribution function estimator based on a nonparametric transformation of the data, Scandinavian Journal of Statistics, 32, 551, 10.1111/j.1467-9469.2005.00472.x Terrell, 1990, The maximal smoothing principle in density estimation, Journal of the American Statistical Association, 85, 270, 10.1080/01621459.1990.10476223 Wand, 1991, Transformations in density estimation, Journal of the American Statistical Association, 86, 343, 10.1080/01621459.1991.10475041