H. Akaike, A new look at the statistical model identification, IEEE Transactions on Automatic Control, vol.19, issue.6, pp.716-723, 1974.
DOI : 10.1109/TAC.1974.1100705

J. Berntsen, T. O. Espelid, and A. Genz, An adaptive algorithm for the approximate calculation of multiple integrals, ACM Transactions on Mathematical Software, vol.17, issue.4, pp.437-451, 1991.
DOI : 10.1145/210232.210233

J. Berntsen, T. O. Espelid, and A. Genz, Algorithm 698; DCUHRE: an adaptive multidemensional integration routine for a vector of integrals, ACM Transactions on Mathematical Software, vol.17, issue.4, pp.452-456, 1991.
DOI : 10.1145/210232.210234

B. H. Boyer, M. S. Gibson, and M. Loretan, Pitfalls in tests for changes in correlations. Federal Reserve Board, IFS Discussion Paper No597R, 1999.

W. Breymann, A. Dias, and P. Embrechts, Dependence structures for multivariate high-frequency data in finance, Quantitative Finance, vol.3, issue.1, pp.1-14, 2003.
DOI : 10.1080/713666155

C. Caillault and D. Guégan, Empirical estimation of tail dependence using copulas. application to asian markets. Working Paper No 05-2003, 2003.
URL : https://hal.archives-ouvertes.fr/halshs-00180865

C. Caillault and D. Guégan, Forecasting var and expected shortfall using dynamical systems: A risk management stategy. Working Paper No 07-2004, 2004.

S. Cambanis, S. Huang, and G. Simons, On the theory of elliptically contoured distributions, Journal of Multivariate Analysis, vol.11, issue.3, pp.368-385, 1981.
DOI : 10.1016/0047-259X(81)90082-8

S. Coles, J. Heffernan, and J. Tawn, Dependence measures for extreme value analysis, Extremes, vol.2, issue.4, pp.339-365, 1999.
DOI : 10.1023/A:1009963131610

P. Deheuvels, La fonction de dépendance empirique et ses propriétés -un test non paramétrique d'indépendance. Académie Royale de Belgique -Bulletin de la classe des sciences -5? Série, pp.274-292, 1979.

B. Efron and R. J. Tibshirani, An Introduction to the Bootstrap, 1993.
DOI : 10.1007/978-1-4899-4541-9

P. Embrechts, A. Mcneil, and D. Straumann, Correlation: Pitfalls and alternatives, a short, non-technical article, RISK Magazine, pp.69-71, 1999.

P. Embrechts, A. Mcneil, and D. Strausmann, Correlation and Dependence in Risk Management: Properties and Pitfalls, Risk Management: Value at Risk and Beyond, pp.176-223, 2002.
DOI : 10.1017/CBO9780511615337.008

H. Fang, K. Fang, and S. Kotz, The Meta-elliptical Distributions with Given Marginals, Journal of Multivariate Analysis, vol.82, issue.1, pp.1-16, 2002.
DOI : 10.1006/jmva.2001.2017

E. W. Frees and E. A. Valdez, Understanding Relationships Using Copulas, North American Actuarial Journal, vol.82, issue.5, pp.1-25, 1998.
DOI : 10.1080/10920277.1998.10595667

C. Genest, K. Ghoudi, and L. Rivest, A semiparametric estimation procedure of dependence parameters in multivariate families of distributions, Biometrika, vol.82, issue.3, pp.543-552, 1995.
DOI : 10.1093/biomet/82.3.543

C. Genest and R. Mackay, Copules archim??diennes et families de lois bidimensionnelles dont les marges sont donn??es, Canadian Journal of Statistics, vol.21, issue.2, pp.145-159, 1986.
DOI : 10.2307/3314660

C. Genest and R. Mackay, The Joy of Copulas: Bivariate Distributions with Uniform Marginals, The American Statistician, vol.44, issue.4, pp.280-283, 1986.
DOI : 10.2307/3314660

P. Georges, A. Lamy, E. Nicolas, G. Quibel, and T. Roncalli, Multivariate survival modelling: a unified approach with copulas. Working Paper, 2001.

J. Heffernan, A directory of coefficients of tail dependence, Extremes, vol.3, issue.3, pp.279-290, 2000.
DOI : 10.1023/A:1011459127975

H. Joe, Multivariate Models and Dependence Concepts, 1997.

T. Ledford and J. Tawn, Statistics for near independence in multivariate extreme values, Biometrika, vol.83, issue.1, pp.169-187, 1996.
DOI : 10.1093/biomet/83.1.169

T. Ledford and J. Tawn, Concomitant tail behaviour for extremes, Advances in Applied Probability, vol.22, issue.01, pp.197-215, 1998.
DOI : 10.2307/3318479

F. Lindskog, A. Mcneil, and H. Schmoch, A note on kendall's tau for elliptical distributions, ETH preprint, 2001.

Y. Malevergne and D. Sornette, How to account for extreme comovements between stocks and the markets? Working paper, 2001.

Y. Malevergne and D. Sornette, Testing the gaussian copula hypothesis for financial assets dependences, Quantitative Finance, vol.4, issue.3, pp.231-250, 2003.
URL : https://hal.archives-ouvertes.fr/hal-00520539

D. Oakes, Multivariate survival distributions, Journal of Nonparametric Statistics, vol.39, issue.3-4, pp.343-354, 1994.
DOI : 10.2307/2341080

A. J. Patton, Modelling time-varying exchange rate dependence using the conditionnal copula, 2001.

J. H. Shih and T. A. Louis, Inferences on the Association Parameter in Copula Models for Bivariate Survival Data, Biometrics, vol.51, issue.4, pp.1384-1399, 1995.
DOI : 10.2307/2533269

A. Sklar, Fonctions de répartitionrépartition`répartitionà n dimensions et leurs marges, pp.229-231, 1959.