Is a Normal Copula the Right Copula?

References

• Amengual, D., and Sentana, E. (2015), “Is a Normal Copula the Right Copula?,” CEMFI Working Paper No. 1504, CEMFI.
   Google Scholar
• Amengual, D., Sentana, E. and Tian, Z. (2018), “Gaussian Rank Correlation and Regression,” Mimeo, CEMFI.
   Google Scholar
• Andrews, D. W. K. (2001), “Testing When a Parameter is on the Boundary of the Maintained Hypothesis,” Econometrica, 69, 683–734.
   Web of Science ®Google Scholar
• Asness, C. S., Moskowitz, T. J., and Pedersen, L. H. (2013), “Value and Momentum Everywhere,” Journal of Finance, 68, 929–985.
   Web of Science ®Google Scholar
• Azzalini, A., and Capitanio, A. (2003), “Distributions Generated by Perturbation of Symmetry with Emphasis on a Multivariate Skew t-distribution,” Journal of the Royal Statistical Society, Series B, 65, 367–389.
   Google Scholar
• Barndorff-Nielsen, O. (1977), “Exponentially Decreasing Distributions for the Logarithm of Particle Size,” Proceedings of the Royal Society, 353, 401–419.
   Web of Science ®Google Scholar
• Berg, D., and Quessy, J.-F. (2009), “Local Power Analyses of Goodness-of-Fit Tests for Copulas,” Scandinavian Journal of Statistics, 36, 389–412.
   Web of Science ®Google Scholar
• Blæsild, P. (1981), “The Two-dimensional Hyperbolic Distribution and Related Distributions, with an Application to Johannsen’s Bean Data,” Biometrika, 68, 251–263.
   Web of Science ®Google Scholar
• Calzolari, G., Fiorentini, G., and Sentana, E. (2004), “Constrained Indirect Estimation,” Review of Economic Studies, 71, 945–973.
   Web of Science ®Google Scholar
• Chen, X., and Fan, Y. (2005), “Pseudo-Likelihood Ratio Tests for Semiparametric Multivariate Copula Model Selection,” Canadian Journal of Statistics, 33, 389–414.
   Web of Science ®Google Scholar
• ——— (2006a), “Estimation of Copula-Based Semiparametric Time Series Models,” Journal of Econometrics, 130, 307–335.
   Web of Science ®Google Scholar
• ——— (2006b), “Estimation and Model Selection of Semiparametric Copula-Based Multivariate Dynamic Models Under Copula Misspecification,” Journal of Econometrics, 135, 125–154.
   Web of Science ®Google Scholar
• Donnelly, C., and Embrechts, P. (2010), “The Devil is in the Tails: Actuarial Mathematics and the Subprime Mortgage Crisis,” ASTIN Bulletin, 40, 1–33.
   Web of Science ®Google Scholar
• Engle, R. F. (1982), “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of United Kingdom Inflation,” Econometrica, 50, 987–1007.
   Web of Science ®Google Scholar
• Fan, Y., and Patton, A. J. (2014), “Copulas in Econometrics,” Annual Review of Economics, 6, 179–200.
   Web of Science ®Google Scholar
• Fermanian, J.-D. (2005), “Goodness-of-Fit Tests for Copulas,” Journal of Multivariate Analysis, 95, 119–152.
   Web of Science ®Google Scholar
• Fiorentini, G., and Sentana, E. (2007), “On the Efficiency and Consistency of Likelihood Estimation in Multivariate Conditionally Heteroskedastic Dynamic Regression Models,” CEMFI Working Paper 0713, CEMFI.
   Google Scholar
• Fiorentini, G., Sentana, E., and Calzolari, G. (2003), “Maximum Likelihood Estimation and Inference in Multivariate Conditionally Heteroskedastic Dynamic Regression Models with Student t Innovations,” Journal of Business and Economic Statistics, 21, 532–546.
   Web of Science ®Google Scholar
• Genest, C., Rémillard, B., and Beaudoin, D. (2009), “Goodness-of-Fit Tests for Copulas: A Review and A Power Study,” Insurance Mathematics and Economics, 44, 199–213.
   Web of Science ®Google Scholar
• Godfrey, L. G. (1988), Misspecification Tests in Econometrics: The Lagrange Multiplier Principle and Other Approaches (Econometric Society Monographs), Cambridge: Cambridge University Press.
   Google Scholar
• Gouriéroux, C., Holly, A., and Monfort, A. (1980), “Kuhn–Tucker, Likelihood Ratio and Wald Tests for Nonlinear Models with Inequality Constraints on the Parameters,” Discussion Paper 770, Harvard Institute of Economic Research.
   Google Scholar
• Horowitz, J., and Savin, N. E. (2000), “Empirically Relevant Critical Values for Hypothesis Tests: A Bootstrap Approach,” Journal of Econometrics, 95, 375–389.
   Web of Science ®Google Scholar
• Joe, H. (2005), “Asymptotic Efficiency of the Two-stage Estimation Method for Copula-based Models,” Journal of Multivariate Analysis, 94, 401–419.
   Web of Science ®Google Scholar
• Kotz, S., and Nadarajah, S. (2004), Multivariate t Distributions and Their Applications, Cambridge: Cambridge University Press.
   Google Scholar
• Lee, L. F., and Chesher, A. (1986), “Specification Testing when Score Test Statistics are Identically Xero,” Journal of Econometrics, 31, 121–149.
   Web of Science ®Google Scholar
• MacKenzie, D., and Spears, T. (2012), “The Formula that Killed Wall Street? The Gaussian Copula and the Material Cultures of Modelling,” Mimeo, School of Social & Political Science, University of Edinburgh.
   Google Scholar
• Malevergne, Y., and Sornette, D. (2003), “Testing the Gaussian Copula Hypothesis for Financial Assets Dependencies,” Quantitative Finance, 3, 231–250.
   Web of Science ®Google Scholar
• Mencía, J., and Sentana, E. (2009), “Multivariate Location-Scale Mixture of Normals and Mean-Variance-Skewness Portfolio Allocation,” Journal of Econometrics, 153, 105–121.
   Web of Science ®Google Scholar
• Mencía, J., and Sentana, E. (2012), “Distributional Tests in Multivariate Dynamic Models with Normal and Student t Innovations,” Review of Economics and Statistics, 94, 133–152.
   Web of Science ®Google Scholar
• Newey, W. K. (1985), “Maximum Likelihood Specification Testing and Conditional Moment Tests,” Econometrica, 53, 1047–1070.
   Web of Science ®Google Scholar
• Newey, W. K., and McFadden, D. L. (1994), “Large Sample Estimation and Hypothesis Testing,” in Handbook of Econometrics (Vol. IV), eds. R. F. Engle, and D. L. McFadden, Amsterdam: Elsevier, pp. 2111–2245.
   Google Scholar
• Newey, W. K., and West, K. D. (1987), “A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix,” Econometrica, 55, 703–708.
   Web of Science ®Google Scholar
• Panchenko, V. (2005), “Goodness-of-fit Test for Copulas,” Physica A, 355, 176–182.
   Web of Science ®Google Scholar
• Patton, A. J. (2006), “Modelling Asymmetric Exchange Rate Dependence,” International Economic Review, 47, 527–556.
   Web of Science ®Google Scholar
• ——— (2012), “A Review of Copula Models for Economic Time Series,” Journal of Multivariate Analysis, 110, 4–18.
   Web of Science ®Google Scholar
• Rémillard, B. (2017), “Goodness-of-Fit Tests for Copulas of Multivariate Time Series,” Econometrics, 5, 13.
   Web of Science ®Google Scholar
• Salmon, F. (2009, February 23), “Recipe for Disaster: The Formula that Killed Wall Street,” Wired, Available at http://www.wired.com/print/techbiz/it/magazine/17-03/wp_quant
   Google Scholar
• Scaillet, O. (2007), “Kernel Based Goodness-of-Fit Tests for Copulas with Fixed Smoothing Parameters,” Journal of Multivariate Analysis, 98, 533–543.
   Web of Science ®Google Scholar
• Tauchen, G. (1985), “Diagnostic Testing and Evaluation of Maximum Likelihood Models,” Journal of Econometrics, 30, 415–443.
   Web of Science ®Google Scholar