Copulas: a Review and Recent Developments (2007)

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Embrechts, P., Lindskog, F., McNeil, A. (2003a). Modelling Dependence with Copulasand Applications to Risk Management. In Handbook of Hevy Tailed distributionsin Finance, (Rachev, S.T. (Ed.)). Elsvier: Amsterdam, 329-384.Embrechts, P., HÄoing, A., Juri, A. (2003b). Using copulae to bound the Value-at-Risk for functions of dependent risks. Finance & Stochastics 7, 145-167.Embrechts, P., Puccetti, G. (2006). Bounds for functions of multivariate risks.Journal of Multivariate Analysis 97, 526-547.Engle, E. (2002). Dynamic conditional correlation: A Simple class of multivariateGARCH models. Journal of Business and Economic Statistics 20, 339-350.Feller, W. (1968). An Introduction to Probability Theory and Its Applications. VolumeI, 3rd edition. John Wiley & Sons: New York.Fermanian, J-D. (2005). Goodness of ¯t tests for copulas. Journal of MultivariateAnalysis 95, 119-152.Fermanian, J-D., Radulovich, D., Wegkamp, M. (2004). Weak convergence of empiricalcopula process. Bernoulli 10, 847-860.Fermanian J-D., Scaillet, O. (2003). Nonparametric estimation of copulas for timeseries. Journal of Risk 5, 25-54.Fermanian, J-D., Scaillet, O. (2005). Some statistical pitfalls in copula modellingfor ¯nancial applications. In Capital Formation, Governance and Banking (E.Klein, ed.), Nova Science Publishers, 59-74.Fermanian, J-D., Wegkamp, M. (2004). Time dependent copulas. Working paper.Available at http://www.crest.fr/pageperso/lfa/fermanian/fermanian.htmFisher, R.A., Tippet, L.H.C. (1928). Limiting Forms of the Frequency Distributionof the Largest or Smallest Member of a Sample. Proceedings of the CambridgePhilosophical Society 24, 180-190.Frank, M., Nelsen, R., Schweizer, B. (1987). Best possible bounds for the distributionof sum - a problem of Kolmogorov. Probability Theory and Related Fields74, 199-211.Fredricks, G.A., Nelsen, R.B. (1997). Copulas constructed from diagonal sections. InDistributions with Given Marginals and Moment Problems, (Benes, V., Stepan,J. (Eds.)), Kluwer Academic Publishers: Dordrecht, 129-136.Fredricks, G.A., Nelsen, R.B. (2002). The Bertino family of copulas. In Distributionswith Given Marginals and Statistical Modelling, (Cuadras, C.M., Fortiana, J.,Rodrguez Lallena, J.A. (Eds.)), Kluwer Academic Publishers: Dordrecht, 81-91.40
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Page 3 and 4: can be employed in probability theo
Page 5 and 6: y Genest et al. (1993) and Shi and
Page 7 and 8: Table 1: Distribution of (C 1 jC 2
Page 9 and 10: It should be mentioned here that gr
Page 11 and 12: Nelsen et al. (2003) have used Bert
Page 13 and 14: 2.4 Time dependent copulasIn practi
Page 15 and 16: De¯nition (conditional pseudo-copu
Page 17 and 18: (i) Ã 1 (x 1 ;::: ;x n )=x 1 + :::
Page 19 and 20: (1999)) even in the cases where the
Page 21 and 22: Let R u = P nj=1 IfU j · ug and R
Page 23: usually wish to aggregate two-dimen
Page 26 and 27: 3.3 Copula representation via a loc
Page 28 and 29: such thatC(u; v) =© ru;v¡© ¡1 (
Page 30 and 31: Fisher-Tippett Theorem (version for
Page 32 and 33: et al. (2000). To measure contagion
Page 34 and 35: and the non-exchangeable copula (AL
Page 36 and 37: 0 2 4 6 8 10 120 1 2 3 4 5 60 2 4 6
Page 38 and 39: Bouye, E., Durrleman, V. Nikeghbali
Page 42 and 43: Hsing, T, KlÄuppelberg, C., Kuhn,
Page 44 and 45: Nelsen, R., Quesada-Molina, J., Rod

Copulas: a Review and Recent Developments (2007)

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