Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-16T15:07:44.417Z Has data issue: false hasContentIssue false

Stochastic orderings of multivariate elliptical distributions

Published online by Cambridge University Press:  23 June 2021

Chuancun Yin*
Affiliation:
Qufu Normal University
*
*Postal address: School of Statistics, Qufu Normal University, Qufu 273165, Shandong, China. Email address: [email protected]

Abstract

For two n-dimensional elliptical random vectors X and Y, we establish an identity for $\mathbb{E}[f({\bf Y})]- \mathbb{E}[f({\bf X})]$, where $f\,{:}\, \mathbb{R}^n \rightarrow \mathbb{R}$ satisfies some regularity conditions. Using this identity we provide a unified method to derive sufficient and necessary conditions for classifying multivariate elliptical random vectors according to several main integral stochastic orders. As a consequence we obtain new inequalities by applying the method to multivariate elliptical distributions. The results generalize the corresponding ones for multivariate normal random vectors in the literature.

Type
Original Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Applied Probability Trust

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abdous, B., Genest, C. and Rémillard, B. (2005). Dependence properties of meta-elliptical distributions. In Statistical Modeling and Analysis for Complex Data Problems, eds. P. Duschene and B. Rémillard, Springer, New York, pp. 115.10.1007/0-387-24555-3_1CrossRefGoogle Scholar
Arlotto, A. and Scarsini, M. (2009). Hessian orders and multinormal distributions. J. Multivar. Anal. 100, 23242330.10.1016/j.jmva.2009.03.009CrossRefGoogle Scholar
Bäuerle, N. (1997). Inequalities for stochastic models via supermodular orderings. Commun. Statist. Stoch. Models 13, 181 (1997).CrossRefGoogle Scholar
Bäuerle, N. abd Bayraktar, E. (2014). A note on applications of stochastic ordering to control problems in insurance and finance. Stochastics, 86, 330340.10.1080/17442508.2013.778861CrossRefGoogle Scholar
Bäuerle, N. and Müller, A. (2006). Stochastic orders and risk measures: Consistency and bounds. Insurance Math. Econom. 38, 132148.CrossRefGoogle Scholar
Block, H. W. and Sampson, A. R. (1988). Conditionally ordered distributions. J. Multivar. Anal. 27, 91104.10.1016/0047-259X(88)90118-2CrossRefGoogle Scholar
Cambanis, S., Huang, S. and Simons, G. (1981). On the theory of elliptically contoured distributions. J. Multivar. Anal. 11, 365385.10.1016/0047-259X(81)90082-8CrossRefGoogle Scholar
Cal, D. and Carcamo, J. (2006). Stochastic orders and majorization of mean order statistics. J. Appl. Prob. 43, 704712.CrossRefGoogle Scholar
Carter, M. (2001). Foundations of Mathematical Economics. MIT Press, Cambridge, MA.Google Scholar
Chernozhukov, V., Chetverikov, D. and Kato, K. (2015). Comparison and anti-concentration bounds for maxima of Gaussian random vectors. Prob. Theory Relat. Fields 162, 4770.10.1007/s00440-014-0565-9CrossRefGoogle Scholar
Christofides, T. C. and Vaggelatou, E. (2004). A connection between supermodular ordering and positive/negative association. J. Multivar. Anal. 88, 138151.10.1016/S0047-259X(03)00064-2CrossRefGoogle Scholar
Das Gupta, S., Eaton, M. L., Olkin, I., Perlman, M. D., Savage, L. J. and Sobel, M. (1972). Inequalities on the probability content of convex regions for elliptically contoured distributions. In: Proc. Sixth Berkeley Symp. Prob. Statist., Vol. 2, University of California Press, Berkeley, CA, pp. 241265.Google Scholar
Davidov, O. and Peddada, S. (2013). The linear stochastic order and directed inference for multivariate ordered distributions. Ann. Statist. 41, 140.10.1214/12-AOS1062CrossRefGoogle ScholarPubMed
Denuit, M. and Müller, A. (2002). Smooth generators of integral stochastic orders. Ann. Appl. Prob. 12, 11741184.10.1214/aoap/1037125858CrossRefGoogle Scholar
Denuit, M., Dhaene, J., Goovaerts, M. and Kaas, R. (2005). Actuarial Theory for Dependent Risks: Measures, Orders and Models. John Wiley, New York.10.1002/0470016450CrossRefGoogle Scholar
Ding, Y. and Zhang, X. (2004). Some stochastic orders of Kotz-type distributions. Statist. Prob. Lett. 69, 389396.CrossRefGoogle Scholar
El Karoui, N. (2009). Concentration of measure and spectra of random matrices: Applications to correlation matrices, elliptical distributions and beyond. Ann. Appl. Prob. 19, 23622405.10.1214/08-AAP548CrossRefGoogle Scholar
Fábián, C. I., Mitra, G. and Roman, D. (2011). Processing second-order stochastic dominance models using cutting-plane representations. Math. Program. 130, 3357.10.1007/s10107-009-0326-1CrossRefGoogle Scholar
Fang, K. T. and Liang, J. J. (1989). Inequalities for the partial sums of elliptical order statistics related to genetic selection. Canad. J. Statist. 17, 439446.CrossRefGoogle Scholar
Fang, K. W., Kotz, S. and Ng, K. W. (1990). Symmetric Multivariate and Related Distributions. Chapman & Hall, London.10.1007/978-1-4899-2937-2CrossRefGoogle Scholar
Fill, J. A. and Kahn, J. (2013). Comparison inequalities and fastest-mixing Markov chains. Ann. Appl. Prob. 23, 17781816.10.1214/12-AAP886CrossRefGoogle Scholar
Goovaerts, M. J. and Dhaene, J. (1999). Supermodular ordering and stochastic annuities. Insurance Math. Econom. 24, 281290.10.1016/S0167-6687(99)00002-5CrossRefGoogle Scholar
Gupta, A. K., Varga, T. and Bodnar, T. (2013). Elliptically Contoured Models in Statistics and Portfolio Theory, 2nd ed. Springer, New York.10.1007/978-1-4614-8154-6CrossRefGoogle Scholar
Hazra, N. K., Kuiti, M. R., Finkelstein, M. and Nanda, A. K. (2017). On stochastic comparisons of maximum order statistics from the location-scale family of distributions. J. Multivar. Anal. 160, 3141.10.1016/j.jmva.2017.06.001CrossRefGoogle Scholar
Houdré, C., Pérez-Abreu, V. and Surgailis, D. (1998). Interpolation, correlation identities, and inequalities for infinitely divisible variables. J. Fourier Anal. Appl. 4, 651668.CrossRefGoogle Scholar
Hu, T. Z. and Zhuang, W. W. (2006). Stochastic orderings between p-spacings of generalized order statistics from two samples. Prob. Eng. Inf. Sci. 20, 465479.CrossRefGoogle Scholar
Joag-Dev, K., Perlman, M. and Pitt, L. (1983). Association of normal random variables and Slepian’s inequality. Ann. Probab. 11, 451455.10.1214/aop/1176993610CrossRefGoogle Scholar
Joe, H. (1990). Multivariate concordance. J. Multivar. Anal. 35, 1230.10.1016/0047-259X(90)90013-8CrossRefGoogle Scholar
Kelker, D. (1970). Distribution theory of spherical distributions and location-scale parameter generalization. Sankhyā 32, 419430.Google Scholar
Landsman, Z. and Tsanakas, A. (2006). Stochastic ordering of bivariate elliptical distributions. Statist. Prob. Lett. 76, 488494.10.1016/j.spl.2005.08.016CrossRefGoogle Scholar
Li, W. V. and Shao, Q. M. (2002). A normal comparison inequality and its applications. Prob. Theory Relat. Fields 122, 494508.10.1007/s004400100176CrossRefGoogle Scholar
López-Díaz, M. C., López-Díaz, M. and Martínez-Fernández, S. (2018). A stochastic order for the analysis of investments affected by the time value of money. Insurance Math. Econom. 83, 7582.CrossRefGoogle Scholar
Marshall, A. and Olkin, I. (2011). Inequalities: Theory of Majorization and its Applications, 2nd ed. Springer, New York, (2011).10.1007/978-0-387-68276-1CrossRefGoogle Scholar
McNeil, A. J., Frey, R. and Embrechts, P. (2015). Quantitative Risk Management: Concepts, Techniques and Tools. Princeton University Press.Google Scholar
Meester, L. E. and Shanthikumar, J. G. (1993). Regularity of stochastic processes. Prob. Eng. Inf. Sci. 7, 343360.10.1017/S0269964800002965CrossRefGoogle Scholar
Mosler, K. C. (1982). Entscheidungsregeln bei Risiko: Multivariate stochastische Dominanz. Lecture Notes in Economics and Mathematical Systems, Vol. 204, Springer, Berlin..Google Scholar
Müller, A. (1997a). Stop-loss order for portfolios of dependent risks. Insurance Math. Econom. 21, 219223.10.1016/S0167-6687(97)00032-2CrossRefGoogle Scholar
Müller, A. (1997b). Stochastic orders generated by integrals: A unified study. Adv. Appl. Prob. 29, 414428.CrossRefGoogle Scholar
Müller, A. (2001). Stochastic ordering of multivariate normal distributions. Ann. Inst. Statist. Math. 53, 567575.10.1023/A:1014629416504CrossRefGoogle Scholar
Müller, A and Scarsini, M. (2000). Some remarks on the supermodular order. J. Multivar. Anal. 73, 107119.10.1006/jmva.1999.1867CrossRefGoogle Scholar
Müller, A and Scarsini, M. (2006). Stochastic order relations and lattices of probability measures. SIAM J. Optim. 16, 10241043.CrossRefGoogle Scholar
Müller, A. and Stoyan, D. (2002). Comparison Methods for Stochastic Models and Risks. John Wiley, Chichester.Google Scholar
Pan, X., Qiu, G. and Hu, T. (2016). Stochastic orderings for elliptical random vectors. J. Multivar. Anal. 148, 8388.10.1016/j.jmva.2016.02.016CrossRefGoogle Scholar
Rüschendorf, L. (1980). Inequalities for the expectation of $\Delta$-monotone functions. Z. Wahrscheinlichkeitsth. 54, 341349.CrossRefGoogle Scholar
Scarsini, M. (1998). Multivariate convex orderings, dependence, and stochastic equality. J. Appl. Prob. 35, 93103.10.1017/S0021900200014704CrossRefGoogle Scholar
Sha, X. Y. Xu, Z. S. and Yin, C. C. (2019). Elliptical distribution-based weight-determining method for ordered weighted averaging operators. Internat. J. Intel. Syst. 34, 858877.CrossRefGoogle Scholar
Shaked, M. and Shanthikumar, J. G. (1990). Parametric stochastic convexity and concavity of stochastic processes. Ann. Inst. Statist. Math. 42, 509531.10.1007/BF00049305CrossRefGoogle Scholar
Shaked, M. and Shanthikumar, J. G. (1997). Supermodular stochastic orders and positive dependence of random vectors. J. Multivar. Anal. 61, 86101.CrossRefGoogle Scholar
Shaked, M. and Shanthikumar, J. G. (2007). Stochastic Orders. Springer, New York.CrossRefGoogle Scholar
Tong, Y. L. (1980). Probability Inequalities in Multivariate Distributions. Academic Press, New York.Google Scholar
Topkis, D. M. (1988). Supermodularity and Complementarity. Princeton University Press.Google Scholar
Whitt, W. (1986). Stochastic comparisons for non-Markov processes. Math. Operat. Res. 11, 608618.10.1287/moor.11.4.608CrossRefGoogle Scholar
Yan, L. (2009). Comparison inequalities for one-sided normal probabilities. J. Theor. Prob. 22, 827836.10.1007/s10959-009-0248-0CrossRefGoogle Scholar
Yin, C. C. (2020). A unified treatment of characteristic functions of symmetric multivariate and related distributions. Working paper.Google Scholar
Yin, C. C., Wang, Y. and Sha, X. Y. (2020). A new class of symmetric distributions including the elliptically symmetric logistic. Submitted.Google Scholar