Goodness-of-fit test for tail copulas modeled by elliptical copulas

Statistics and Probability Letters

Volumn 79, Issue 8, 2009, Pages 1097-1104

  Li, Deyuan ^a   Peng, Liang ^b  

^a FUDAN UNIVERSITY   (China)

^b GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 61749089701     PISSN: 01677152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.spl.2008.12.019     Document Type: Article

References (21)

1. Berkes I., and Horvath L. Limit results for the empirical process of squared residuals in GARCH models. Stochastic Processes and their Applications 105 (2003) 271-298
2. Bolance C., Giullen M., and Nielsen J.P. Kernel density estimation of actuarial loss functions. Insurance: Mathematics and Economics 32 (2003) 19-36
3. Chan N.H., Chen J., Chen X., Fan Y., and Peng L. Statistical inference for multivariate residual copula of GARCH models. Statistica Sinica 19 1 (2009) 53-70
4. Chen X., and Fan Y. Pseudo-likelihood ratio tests for semiparametric multivariate copula model selection. The Canadian Journal of Statistics 33 2 (2005) 389-414
5. Chen X., and Fan Y. Estimation and model selection of semiparametric copula-based multivariate dynamic models under copula misspecification. Journal of Econometrics 135 (2006) 125-154
6. Dupuis D., and Jones B.L. Multivariate extreme value theory and its usefulness in understanding risk. North American Actuarial Journal 10 (2006) 1-27
7. Frees E.W., and Valdez E.A. Understanding relationships using copulas. North American Actuarial Journal 2 (1998) 1-25
8. Frees E.W., and Wang P. Copula credibility for aggregate loss models. Insurance: Mathematics and Economics 38 (2006) 360-373
9. Hashorva E. Extremes of asymptotically spherical and elliptical random vectors. Insurance: Mathematics and Economics 36 (2005) 285-302
10. Higham N. Computing the nearest correlation matrix - a problem from finance. IMA Journal of Numerical Analysis 22 3 (2002) 329-343
11. Klugman S.A., and Parsa R. Fitting bivariate loss distributions with copulas. Insurance: Mathematics and Economics 24 (1999) 139-148
12. Klüppelber C., Kuhn G., and Peng L. Estimating the tail dependence function of an elliptical distribution. Bernoulli 13 1 (2007) 229-251
13. Klüppelberg C., Kuhn G., and Peng L. Semi-parametric models for the multivariate tail dependence function-the asymptotically dependent case. Scandinavian Journal of Statistics 35 (2008) 701-718
14. Lane M.N. Pricing risk transfer transactions. ASTIN Buletin 30 2 (2000) 259-293
15. Matthys G., Delafosse E., Guillou A., and Beirlant J. Estimating catastrophic quantile levels for heavy-tailed distributions. Insurance: Mathematics and Economics 34 (2004) 517-537
16. McNeil A.J., Frey R., and Embrechts P. Quantitative Risk Management: Concepts, Techniques and Tools (2005), Princeton University Press
17. Peng, L., (2009). Estimating the probability of a rare event via elliptical copulas, North American Actuarial Journal (in press)
18. Schmidt R., and Stadtmüller U. Nonparametric estimation of tail dependence. Scandinavian Journal of Statistics 33 (2006) 307-335
19. Valdez E.A., and Chernih A. Wang's capital allocation formula for elliptically contoured distributions. Insurance: Mathematics and Economics 33 (2003) 517-532
20. Vandewalle B., and Beirlant J. On univariate extreme value statistics and the estimation of reinsurance premiums. Insurance: Mathematics and Economics 38 (2006) 441-459
21. Vernic R. Multivariate skew-normal distributions with applications in insurance. Insurance: Mathematics and Economics 38.2 (2006) 413-426