High quantiles estimation with Quasi-PORT and DPOT: An application to value-at-risk for financial variables

The North American Journal of Economics and Finance - Tập 26 - Trang 487-496 - 2013
Paulo Araújo Santos1, Isabel Fraga Alves2, Shawkat Hammoudeh3
1School of Management and Technology of Santarém and Center of Statistics and Applications, University of Lisbon. Complexo Andaluz, Apartado 295, 2001-904 Santarém, Portugal
2Faculty of Sciences, University of Lisbon, and Center of Statistics and Applications, University of Lisbon. Bloco C6, Piso 4, gab.6.4.8, Campo Grande, 1749-016 Lisboa, Portugal
3Lebow College of Business, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, United States

Tài liệu tham khảo

Araújo Santos, 2012, Forecasting value-at-risk with a duration based POT method, Mathematics and Computers in Simulation. Araújo Santos, 2012, A new class of independence tests for interval forecasts evaluation, Computational Statistics and Data Analysis, 56, 3366, 10.1016/j.csda.2010.10.002 Araújo Santos, 2006, Peaks over random threshold methodology for tail index and high quantile estimation, RevStat Statistical Journal, 4, 227 Balkema, 1974, Residual life time at great age, Annals of Probabilities, 2, 792, 10.1214/aop/1176996548 Beirlant, 1999, Tail index estimation and exponential regression model, Extremes, 2, 177, 10.1023/A:1009975020370 Bollerslev, 1986, Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 31, 307, 10.1016/0304-4076(86)90063-1 Caeiro, 2002, A class of asymptotically unbiased semi parametric estimators of the index, Test, 11, 345, 10.1007/BF02595711 Caeiro, 2005, Direct reduction of bias of the classical Hill estimator, Review of Statistics, 3, 111 Chen, Y. -H., & Tu, A. H. Estimating hedged portfolio value-at-risk using the conditional copula: An illustration of model risk. International Review of Economics and Finance. (2013), http://dx.doi.org/10.1016/j.iref.2013.01.006. Christoffersen, 1998, Evaluating intervals forecasts, International Economic Review, 39, 841, 10.2307/2527341 Danielsson, 2000, Value at risk and extreme returns, Annales d⿿Economie et de Statistique, ENSAE, 60, 239, 10.2307/20076262 de Haan, 1989, Extremal behavior of solutions to a stochastic difference equation with application to ARCH processes, Stochastic Processes and Their Applications, 32, 213, 10.1016/0304-4149(89)90076-8 Diebold, F. X., Schuermann, T., & Stroughair, J. D. (1998). Pitfalls and Opportunities in the use of extreme value theory in risk management. Working Paper, 98-10, Wharton School, University of Pennsylvania. Ding, 1993, A long memory property of stock market return and a new model, Journal of Empirical Finance, 1, 83, 10.1016/0927-5398(93)90006-D Embrechts, 1997 Fraga Alves, 2003, A new class of semi parametric estimators of the second order parameter, Portugaliae Mathematica, 60, 193 Feuerverger, 1999, Estimating a tail exponent by modeling departure from a Pareto distribution, Annals of Statistics, 27, 760, 10.1214/aos/1018031215 Gomes, 2012, A computational study of a quasi-PORT methodology for VaR based on second-order reduced-bias estimation, Journal of Statistical Computation and Simulation, 82, 587, 10.1080/00949655.2010.547196 Gomes, 2008, Tail Index estimation for heavy-tailed models: Accommodation of bias in weighted log-excesses, Journal of Royal Statistical Society, B70, 31 Gomes, 2007, A sturdy reduced bias extreme quantile (VaR) estimator, Journal American Statistical Association, 102, 280, 10.1198/016214506000000799 Gomes, 2007, Improving second order reduced-bias tail index estimator, Review of Statistics, 5, 177 Gomes, 2002, ⿿Asymptotically unbiased⿿ estimators of the tail index based on the external estimation of the second order parameter, Extremes, 5, 5, 10.1023/A:1020925908039 Gomes, 2001, Generalizations of the Hill estimator asymptotic versus finite sample behaviour, Journal of Statistical Planning and Inference, 93, 161, 10.1016/S0378-3758(00)00201-9 Gomes, 2000, Alternatives to a semi parametric estimator of parameters of rare events ⿿ the Jackknife methodology, Extremes, 3, 207, 10.1023/A:1011470010228 Hammoudeh, 2013, Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks, The North American Journal of Economics and Finance, 25 Hill, 1975, A Simple general approach to inference about the tail of a distribution, Annals of Statistics, 3, 1163, 10.1214/aos/1176343247 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, 3, 73, 10.3905/jod.1995.407942 Longin, 2001, From VaR to stress testing: The extreme value approach, Journal of Banking and Finance, 24, 1097, 10.1016/S0378-4266(99)00077-1 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 Pickands, 1975, Statistical inference using extreme value order statistics, Annals of Statistics, 3, 119, 10.1214/aos/1176343003 Peng, 1998, Asymptotically unbiased estimator for the extreme-value index, Statistics and Probability Letters, 38, 107, 10.1016/S0167-7152(97)00160-0 R Development Core Team, 2012 Resnick, 1996 Ribatet, 2009 Riskmetrics, 1996 Smith, 1987, Estimating tails of probability distributions, Annals of Statistics, 15, 1174, 10.1214/aos/1176350499 Tsay, 2010, 10.1002/9780470644560 Weissman, 1978, Estimation of parameters and large quantiles based on the k largest observations, Journal American Statistical Association, 73, 812 Wermers, 2006, Performance evaluation with portfolio holdings information, The North American Journal of Economics and Finance, 17, 207, 10.1016/j.najef.2006.01.001 Wuertz, 2008