Predicting extreme value at risk: Nonparametric quantile regression with refinements from extreme value theory
Tài liệu tham khảo
Balkema, 1974, Residual life time at great age, The Annals of Probability, 2, 792, 10.1214/aop/1176996548
Cai, 2002, Regression quantiles for time series, Econometric Theory, 18, 169, 10.1017/S0266466602181096
Cai, 2008, Nonparametric estimation of conditional var and expected shortfall, Journal of Econometrics, 147, 120, 10.1016/j.jeconom.2008.09.005
Chen, 2005, Nonparametric inference of value-at-risk for dependent financial returns, Journal of Financial Econometrics, 3, 227, 10.1093/jjfinec/nbi012
Chernozhukov, 2009, Improving point and interval estimates of monotone functions by rearrangement, Biometrika, 96, 559, 10.1093/biomet/asp030
Chernozhukov, 2001, Conditional value-at-risk: aspects of modelling and estimation, Empirical Economics, 26, 271, 10.1007/s001810000062
Dette, 2006, A simple nonparametric estimator of a strictly monotone regression function, Bernoulli, 12, 469, 10.3150/bj/1151525131
Drees, 2003, Extreme quantile estimation for dependent data, with applications to finance, Bernoulli, 9, 617, 10.3150/bj/1066223272
El-Arouia, 2002, On the use of the peaks over thresholds method for estimating out-of-sample quantiles, Computational Statistics and Data Analysis, 39, 453, 10.1016/S0167-9473(01)00087-1
Embrechts, 1997
Engle, 2004, Caviar: conditional autoregressive value at risk by regression quantiles, Journal of Business & Economic Statistics, 22, 367, 10.1198/073500104000000370
Fan, 1996, vol. 66
Koenker, 1978, Regression quantiles, Econometrica, 46, 33, 10.2307/1913643
Koenker, 1996, Conditional quantile estimation and inference for arch models, Econometric Theory, 12, 793, 10.1017/S0266466600007167
Kuester, 2006, Value-at-risk prediction: a comparison of alternative strategies, Journal of Financial Econometrics, 4, 53, 10.1093/jjfinec/nbj002
Kupiec, 1995, Techniques for verifying the accuracy of risk measurement models, Journal of Derivatives, 73, 10.3905/jod.1995.407942
Li, 2007
MacDonald, 2011, A flexible extreme value mixture model, Computational Statistics and Data Analysis, 55, 2137, 10.1016/j.csda.2011.01.005
Manganelli, S., Engle, R.F., 2001. Value at risk models in finance. In: ECB Working Paper Series Working Paper No. 75.
McNeil, 2000, Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach, Journal of Empirical Finance, 7, 271, 10.1016/S0927-5398(00)00012-8
McNeil, 2005
Nieto, M.R., Ruiz, E., 2008. Measuring financial risk: comparison of alternative procedures to measure var and es. In: Universidad Carlos III de Madrid Working Paper No. 08-73.
Pickands, 1975, Statistical inference using extreme order statistics, The Annals of Statistics, 3, 119, 10.1214/aos/1176343003
Smith, 1987, Estimating the tails of probability distributions, The Annals of Statistics, 15, 1174, 10.1214/aos/1176350499
Taylor, 2008, Using exponentially weighted quantile regression to estimate value at risk and expected shortfall, Journal of Financial Econometrics, 6, 382, 10.1093/jjfinec/nbn007
Wu, 2007, Kernel conditional quantile estimation for stationary processes with application to value at risk, Journal of Financial Econometrics, 1
Yu, 1997, A comparison of local constant and local linear regression quantile estimators, Computational Statistics and Data Analysis, 25, 159, 10.1016/S0167-9473(97)00006-6
Yu, 1998, Local linear quantile regression, Journal of the American Statistical Association, 93, 228, 10.1080/01621459.1998.10474104