Abstract
For a stochastic process {X t } t∈T with identical one-dimensional margins and upper endpoint τ up its tail correlation function (TCF) is defined through \(\chi ^{(X)}(s,t) = \lim _{\tau \to \tau _{\text {up}}} P(X_{s} > \tau \,\mid \, X_{t} > \tau )\). It is a popular bivariate summary measure that has been frequently used in the literature in order to assess tail dependence. In this article, we study its realization problem. We show that the set of all TCFs on T×T coincides with the set of TCFs stemming from a subclass of max-stable processes and can be completely characterized by a system of affine inequalities. Basic closure properties of the set of TCFs and regularity implications of the continuity of χ are derived. If T is finite, the set of TCFs on T×T forms a convex polytope of \(\lvert T \rvert \times \lvert T \rvert \) matrices. Several general results reveal its complex geometric structure. Up to \(\lvert T \rvert = 6\) a reduced system of necessary and sufficient conditions for being a TCF is determined. None of these conditions will become obsolete as \(\lvert T \rvert \geq 3\) grows.
Similar content being viewed by others
References
Adler, R.J.: An introduction to continuity, extrema, and related topics for general Gaussian processes. Institute of Mathematical Statistics Lecture NotesMonograph Series, 12, Institute of Mathematical Statistics, Hayward, CA (1990)
Beirlant, J., Goegebeur, Y., Teugels, J., Segers, J.: Statistics of Extremes Wiley Series in Probability and Statistics. John Wiley & Sons Ltd., Chichester (2004)
Berg, C., Christensen, J.P.R., Ressel, P.: Harmonic Analysis on Semigroups, Graduate Texts in Mathematics, vol. 100. Springer-Verlag, NY (1984)
Blanchet, J., Davison, A.C.: Spatial modeling of extreme snow depth. Ann. Appl. Stat. 5(3), 1699–1725 (2011)
Coles, S., Heffernan, J., Tawn, J.: Dependence measures for extreme value analyses. Extremes 2(4), 339–365 (1999)
Davis, R.A., Mikosch, T.: The extremogram: a correlogram for extreme events. Bernoulli 15(4), 977–1009 (2009)
Deza, M.M., Laurent, M.: Geometry of Cuts and Metrics, Algorithms and Combinatorics Vol 15. Springer-Verlag, Berlin (1997)
Embrechts, P., Hofert M., Wang R.: Bernoulli and tail-dependence compatibility. Annals of Applied Probability (2015). To appear
Emery, X.: On the existence of mosaic and indicator random fields with spherical, circular, and triangular variograms. Math Geosci. 42(8), 969–984 (2010)
Engelke, S., Malinowski, A., Kabluchko, Z., Schlather, M.: Estimation of Hüsler-Reiss distributions and Brown-Resnick processes. J. Royal Stat. Soc. Ser. B (Stat. Methodol.) 77(1), 239–265 (2015)
Fasen, V., Klüppelberg, C., Schlather, M.: High-level dependence in time series models. Extremes 13(1), 1–33 (2010)
Fiebig, U., Strokorb, K., Schlather, M.: The realization problem for tail correlation functions. arXiv:1405.6876 (2014)
Frahm, G., Junker, M., Schmidt, R.: Estimating the tail-dependence coefficient: properties and pitfalls. Insur. Math Econom. 37(1), 80–100 (2005)
Gawrilow, E., Joswig, M.: polymake: a framework for analyzing convex polytopes. In: Polytopescombinatorics and computation (Oberwolfach, 1997), DMV Semaine, vol. 29, pp 43-73, Birkhäuser, Basel (2000)
Geffroy, J.: Contribution à la théorie des valeurs extrêmes. Publ. Inst. Statist. Univ. Paris 7/8, 37–185 (1958)
Grötschel, M., Wakabayashi, Y.: Facets of the clique partitioning polytope. Math Programm. 47(3, Ser. A), 367–387 (1990)
De Haan, L.: A spectral representation for max-stable processes. Ann. Probab. 12(4), 1194–1204 (1984)
Hall, P., Fisher, N.I., Hoffmann, B.: On the nonparametric estimation of covariance functions. Ann. Statist. 22(4), 2115–2134 (1994)
Jiao, Y., Stillinger, F.H., Torquato, S.: Modeling heterogeneous materials via two-point correlation functions: basic principles. Phys Rev E (3) 76(3), 031,110, 13 (2007)
Kabluchko, Z., Schlather, M.: Ergodic properties of max-infinitely divisible processes. Stoch. Process Appl. 120(3), 281–295 (2010)
Lachieze-Rey, R.: The convex class of realisable unit covariances. arXiv:13014402 (2013)
Lachièze-Rey, R.: Realisability conditions for second-order marginals of biphased media. Random Struct. Algorithm. 47(3), 588–604 (2015)
Lachieze-Rey, R., Molchanov, I.: Regularity conditions in the realisability problem with applications to point processes and random closed sets. Ann. Appl. Probab. 25(1), 116–149 (2015)
Markov, K.Z.: On the “triangular” inequality in the theory of two-phase random media. Annu. Univ. Sofia Fac. Math. Inform. 89(1-2), 159–166 (1998) (1995)
Matheron, G.: Suffit-Il Pour Une Covariance D’être De Type Positif? Etud Géostat V, Séminaire CFSG Geostat, Sciences de la Terre Inf Nancy (1988)
Matheron, G.: Une conjecture sur la covariance d’un ensemble aléatoire. Cahiers de Géostatique, Fasc 3, Ecole des Mines de Paris (1993)
McMillan, B.: History of a problem. J. Soc. Ind. Appl. Math. 3(3), 119–128 (1955)
McNeil, F., Embrechts, P., Lindskog, A., Rachev, S.T.: Modelling Dependence with Copulas and Applications to Risk Management. In: Handbook of Heavy Tailed Distributions in Finance. Elsevier/North-Holland, Amserdam (2003)
Molchanov, I.: Theory of Random Sets Probability and Its Applications (New York). Springer-Verlag, London Ltd (2005)
Molchanov, I.: Convex geometry of max-stable distributions. Extremes 11(3), 235–259 (2008)
Molchanov, I., Strokorb, K.: Max-stable random sup-measures with comonotonic tail dependence. arXiv:150703476 (2015)
Tiago de Oliveira, J.: Structure theory of bivariate extremes; extensions. Est. Mat. Estat. Econ. 7, 165–95 (1962)
Patton, A.J.: Modelling asymmetric exchange rate dependence. Int. Econ. Rev. 47(2), 527–556 (2006)
Politis, D.N.: Higher-order accurate, positive semidefinite estimation of large-sample covariance and spectral density matrices. Econ. Theory 27(4), 703–744 (2011)
Quintanilla, J.A.: Necessary and sufficient conditions for the two-point phase probability function of two-phase random media. Proc. R Soc. Lond. Ser. A Math. Phys. Eng. Sci. 464(2095), 1761–1779 (2008)
R Core Team (2013) R.: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, http://www.R-project.org/(2013)
Schlather, M., Tawn, J.: Inequalities for the extremal coefficients of multivariate extreme value distributions. Extremes 5(1), 87–102 (2002)
Schlather, M., Tawn, J.: A dependence measure for multivariate and spatial extreme values: Properties and inference. Biometrika 90, 139–156 (2003)
Shepp, L.: On Positive-Definite Functions Associated with Certain Stochastic Processes. Technical Reprt Technical Report 63-1213-11. Bell Laboratories, Murray Hill (1963)
Shepp, L.: Covariances of Unit Processes. In: Proceedings Working Conference Stochastic Processes, pp 205–218, Santa Barbara, California (1967)
Sibuya, M.: Bivariate extreme statistics. I. Ann. Inst. Stat. Math. Tokyo 11, 195–210 (1960)
Smith, R.: Max-stable processes and spatial extremes. Unpublished Manuscript (1990)
Strokorb, K.: Characterization and construction of max-stable processes. PhD thesis, Georg-August-Universität Göttingen, http://hdl.handle.net/11858/00-1735-0000-0001-BB44-9 (2013)
Strokorb, K., Schlather, M.: An exceptional max-stable process fully parameterized by its extremal coefficients. Bernoulli 21(1), 276–302 (2015)
Strokorb, K., Ballani, F., Schlather, M.: Tail correlation functions of max-stable processes. Extremes 18(2), 241–271 (2015)
Thibaud, E., Opitz, T.: Efficient inference and simulation for elliptical Pareto processes. Biometrika To appear (2015)
Thibaud, E., Aalto, J., Cooley, D.S., Davison, A.C., Heikkinen, J.: Bayesian inference for the Brown-Resnick process, with an application to extreme low temperatures. arXiv:150607836 (2015)
Torquato, S.: Random heterogeneous materials, Interdisciplinary Applied Mathematics, vol 16. Springer-Verlag, New York, microstructure and macroscopic properties (2002)
Wang, Y., Stoev, S.A.: Conditional sampling for spectrally discrete max-stable random fields. Adv. Appl. Probab. 43(2), 461–483 (2011)
Wang, Y., Roy, P., Stoev, S.A.: Ergodic properties of sum- and max-stable stationary random fields via null and positive group actions. Ann. Probab. 41(1), 206–228 (2013)
Yuen, R., Stoev, S.: Upper bounds on value-at-risk for the maximum portfolio loss. Extremes 17(4), 585–614 (2014)
Ziegler, G.M.: Lectures on Polytopes, Graduate Texts in Mathematics, Vol 152. Springer-Verlag, New York (1995)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Fiebig, UR., Strokorb, K. & Schlather, M. The realization problem for tail correlation functions. Extremes 20, 121–168 (2017). https://doi.org/10.1007/s10687-016-0250-8
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10687-016-0250-8
Keywords
- Convex polytope
- Extremal coefficient
- Max-stable process
- Tail correlation matrix
- Tail dependence matrix
- Tawn-Molchanov model