Modelling total tail dependence along diagonals

Insurance: Mathematics and Economics

Volumn 42, Issue 1, 2008, Pages 73-80

  Zhang, Ming Heng ^a  

^a SHANGHAI UNIVERSITY OF FINANCE AND ECONOMICS   (China)

Author keywords

Copula; Dependence structure; Model mixture; Quantitative risk; Total tail dependence

Indexed keywords

EID: 38649096932     PISSN: 01676687     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.insmatheco.2007.01.002     Document Type: Article

References (24)

1. Alink S., Löwe M., and Wüthrich M.V. Diversification of aggregate dependent risks. Insurance: Mathematics and Economics 35 (2004) 77-95
2. Bouyé, E., Durrleman, V., Nikeghbali, A., Riboulet, G., Roncalli, T., 2002. Copulas for finance-a reading guide and some applications. Groupe de recherche opérationelle, Crédit Lyonnais. Working Paper
3. Charpentier, A., 2003. Tail distribution and dependence measures. In: Proceedings ASTIN, Berlin
4. Coles S.G., Heffernan J.E., and Tawn J.A. Dependence measures for extreme value analyses. Extremes 2 (1999) 339-365
5. Dropsy V., and Fatemeh N.I. Macroeconomic policies, exchange rate regimes and national stock markets. International Review of Economics & Finance 3 (1994) 195-220
6. Embrechts P., McNeil A., and Straumann D. Correlation and dependence in risk management: Properties and pitfalls. In: Dempster M.A.H. (Ed). Value at Risk and Beyond (1999), Cambridge University Press, Cambridge 176-223
7. Embrechts P., Hoeing A., and Juri A. Using copulae to bound the value-at-risk for functions of dependent risk. Finance Stochastic 7 (2003) 145-167
8. Frahm G., Junker M., and Schmidt R. Estimating the tail-dependence coefficient: Properties and pitfalls. Insurance: Mathematics and Economics 37 (2005) 80-100
9. Heffernan J.E. A directory of coefficients of tail dependence. Extremes 3 (2000) 279-290
10. Joe H. Multivariate Models and Dependence Concepts (1997), Chapman & Hall, London
11. Jogdeo K. Concepts of dependence. In: Kotz S., et al. (Ed). Encyclopedia of Statistical Sciences vol. 1 (1982), Wiley, New York 324-334
12. Li, D.X., 1999. Value at risk based on the volatility, skewness and kurtosis. Working Paper, Riskmetrics Group
13. Lo A.W., and MacKinlay A.C. A Non-Random Walk Down Wall Street (1999), Princeton University Press, Princeton, NJ
14. Longin F., and Solnik B. Extreme correlation of international equity markets. The Journal of Finance 56 (2001) 649-676
15. McLanchlan G.J., and Krishnan T. The EM Algorithm and Extensions (1997), Wiley, New York
16. McNeil A.J., Frey R., and Embrechts P. Quantitative Risk Management - Concept, Techniques and Tools (2005), Princeton University Press, Princeton, NJ
17. Mikusiński M., Sherwood H., and Taylor H.D. Probabilistic interpretations of copulas and their convex sum. In: Dall'Aglio G., et al. (Ed). Advances in Probability Distributions with Given Marginals (1991), Kluwer Academic Publishers, Dortrecht, The Netherlands 95-112
18. Nelsen R.B. An Introduction to Copulas. Lecture Notes in Statistics (1999), Springer, New York
19. Rodriguez, J.C., 2006. Measuring financial contagion: A copula approach. Journal of Empirical Finance, doi:10.1016/j.jempfin.2006.07.002
20. Schweizer B. Thirty years of copulas. In: Dall'Aglio G., et al. (Ed). Advances in Probability Distributions with Given Marginals (1991), Kluwer Academic Publishers, Dordrecht, The Netherlands 13-50
21. Sibuya M. Bivariate extreme statistics. Annals of the Institute of Statistical Mathematics 11 (1960) 195-210
22. Sklar A. Random variables, joint distribution functions and copulas. Kybermetrica 9 (1973) 449-460
23. Zhang M.H., and Cheng Q.S. Determine the number of components in a mixture model by the extended KS test. Pattern Recognition Letters 25 (2004) 211-216
24. Zhang M.H., and Cheng Q.S. An approach to VaR for capital markets with Gaussian mixture. Applied Mathematics and Computation 18 (2005) 1079-1085