Generalized Diagonal Band Copulas with Two-Sided Generating Densities

Published Online:https://doi.org/10.1287/deca.1090.0162

References

  • Abbas A. E. Maximum entropy utility. Oper. Res. (2006) 54(2):277–290LinkGoogle Scholar
  • Abbas A. E. Multiattribute utility copulas. Oper. Res. (2009) 57(6):1367–1383LinkGoogle Scholar
  • Abbas A. E., Howard R. A. Attribute dominance utility. Decision Anal. (2005) 2(4):185–206LinkGoogle Scholar
  • Bedford T., Meeuwissen A. M. H. Minimally informative distributions with given rank correlations for use in uncertainty analysis. J. Statist. Comput. Simulation (1997) 57(1–4):143–175CrossrefGoogle Scholar
  • Blomquist N. On a measure of dependence between two random variables. Ann. Math. Statist. (1950) 21:593–600CrossrefGoogle Scholar
  • Bojarski J. A new class of band copulas—Distributions with uniform marginals. (2001) . Technical report, Institute of Mathematics, Technical University of Zielona Góra, Zielona Góra, PolandGoogle Scholar
  • Cherubini U., Luciano E., Vecchiato W.Copula Methods in Finance (2004) (John Wiley & Sons, New York) CrossrefGoogle Scholar
  • Clemen R. T., Reilly T. Correlations and copulas for decision and risk analysis. Management Sci. (1999) 45(2):208–224LinkGoogle Scholar
  • Clemen R. T., Reilly T.Making Hard Decisions with Decision Tools (2001) (Duxbury, Pacific Grove, CA) Google Scholar
  • Cooke R. M., Waij R. Monte Carlo sampling for generalized knowledge dependence, with application to human reliability. Risk Anal. (1986) 6(3):335–343CrossrefGoogle Scholar
  • De Michele C., Salvadori G., Passoni G., Vezzoli R. A multivariate model of sea storms using copulas. Coastal Engrg. (2007) 54(10):734–751CrossrefGoogle Scholar
  • Denuit M., Dhaene J., Goovaerts M., Kaas R.Actuarial Theory for Dependent Risks. Measures, Orders, and Models (2005) (Wiley, Chichester, UK) CrossrefGoogle Scholar
  • Embrechts P. Copulas: A personal view. J. Risk Insurance (2009) 76(3):639–650CrossrefGoogle Scholar
  • Embrechts P., McNeil A. J., Straumann D., Dempster M. A. H. Correlation and dependence in risk management: Properties and pitfalls. Risk Management: Value at Risk and Beyond (2002) (Cambridge University Press, Cambridge, UK) 176–223CrossrefGoogle Scholar
  • Engle R. F. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflations. Econometrica (1982) 50:987–1007CrossrefGoogle Scholar
  • Ferguson T. F. A class of symmetric bivariate uniform distributions. Statist. Papers (1995) 36(1):31–40CrossrefGoogle Scholar
  • Frees E. W., Valdez E. A. Understanding relationships using copulas. North America Actuarial J. (1998) 2:1–25CrossrefGoogle Scholar
  • Frees E. W., Wang P. Credibility using copulas. North American Actuarial J. (2005) 9(2):31–48CrossrefGoogle Scholar
  • Frees E. W., Carriere J., Valdez E. A. Annuity valuation with dependent mortality. J. Risk Insurance (1996) 63(2):229–261CrossrefGoogle Scholar
  • Genest C., Favre A. C. Everything you always wanted to know about copula modeling but were afraid to ask. J. Hydrologic Engrg. (2007) 12:347–368CrossrefGoogle Scholar
  • Genest C., Mackay J. The joy of copulas, bivariate distributions with uniform marginals. Amer. Statistician (1986) 40(4):280–283Google Scholar
  • Härdle W., Kleinow T., Stahl G.Applied Quantitative Finance: Theory and Computational Tools (2002) (Springer-Verlag, Berlin) CrossrefGoogle Scholar
  • He X., Gong P. Measuring the coupled risks: A copula-based CVAR model. J. Computational Appl. Math. (2009) 223(2):1066–1080CrossrefGoogle Scholar
  • Joe H.Multivariate Models and Dependence Concepts (1997) (Chapman and Hall, London) CrossrefGoogle Scholar
  • Kallen M. J., Cooke R. M., Majors M. J., Bonano E. J., Camp A. L., Thompson R. A. Expert aggregation with dependence. Proc. 6th Internat. Conf. Probab. Safety and Management (2002) (Elsevier, Amsterdam) 1287–1294Google Scholar
  • Kendall M. G. A new measure of rank correlation. Biometrika (1938) 30:81–93CrossrefGoogle Scholar
  • Kotz S., van Dorp J. R.Beyond Beta, Other Continuous Families of Distributions with Bounded Support and Applications (2004) (World Scientific, Singapore) CrossrefGoogle Scholar
  • Kruskal W. H. Ordinal measures of association. J. Amer. Statist. Assoc. (1958) 53(284):49–67CrossrefGoogle Scholar
  • Lewandowski D. Generalized diagonal band copulas. Insurance: Math. Econom. (2005) 37:49–67CrossrefGoogle Scholar
  • Lewandowski D. High dimensional dependence copulae: Sensitivity, sampling. (2008) . Doctoral thesis, Delft University of Technology, Delft, The NetherlandsGoogle Scholar
  • McNeil A. J., Frey R., Embrechts P.Quantitative Risk Management: Concepts, Techniques, Tools (2005) (Princeton University Press, Princeton, NJ) Google Scholar
  • Nelsen R. B.An Introduction to Copulas (1999) (Springer, New York) CrossrefGoogle Scholar
  • Norris P. M., Oreopoulos L., Hou A. Y., Tao W.-K., Zeng X. Representation of 3D heterogeneous cloud fields using copulas: Theory for water clouds. Quart. J. Royal Meteorological Soc. (2008) 134:1843–1864CrossrefGoogle Scholar
  • Pearson K. Notes on the history of correlation. Biometrika (1920) 13:24–45CrossrefGoogle Scholar
  • Salmon F. Recipe for disaster: The formula that killed Wall Street. Wired Magazine (2009) February 23). http://www.wired.com/techbiz/it/magazine/17-03/wp_quantGoogle Scholar
  • Schucany W. R., Parr W. C., Boyer J. E. Correlation structure in Farlie-Gumbel-Morgenstern distributions. Biometrika (1978) 65(3):650–653CrossrefGoogle Scholar
  • Sklar A. Fonctions de répartition à n dimensions et leurs marges. (1959) . Technical Report 8, Publications de l'Institut de Statistique de L'Université de Paris, ParisGoogle Scholar
  • Soofi E. S., Retzer J. J. Information indices: Unification and applications. J. Econometrics (2002) 107:17–40CrossrefGoogle Scholar
  • Spearman C. The proof and measurement of association between two things. Amer. J. Psych. (1904) 14:72–101CrossrefGoogle Scholar
  • van Dorp J. R., Duffey M. R. Modeling statistical dependence in risk analysis for project networks. Internat. J. Production Econom. (1999) 58:17–29CrossrefGoogle Scholar
  • van Dorp J. R., Kotz S. Generalizations of two-sided power distributions and their convolution. Comm. Statist.: Theory and Methods (2003) 32(9):1703–1723CrossrefGoogle Scholar
  • Yi W., Bier V. An application of copulas to accident precursor analysis. Management Sci. (1998) 44(12):257–270LinkGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.