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Modeling and Generating Dependent Risk Processes for IRM and DFA

Published online by Cambridge University Press:  17 April 2015

Dietmar Pfeifer
Affiliation:
Institut für Mathematik, Fakultät für Naturwissenschaften und Mathematik, Carl von Ossietzky Universität, D-26111 Oldenburg, Germany, E-mail: [email protected], Web: www.mathematik.uni-oldenburg.de/personen/pfeifer/pfeifer.html, and AON Jauch&Hübener, Heidenkampsweg 58, D-20059 Hamburg, Germany, Web: www.aon.com/de/ge/
Johana Nešlehová
Affiliation:
RiskLab, ETH-Zentrum, CH-8092 Zürich, Switzerland, E-mail: [email protected], Web: www.risklab.ch/
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Abstract

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Modern Integrated Risk Management (IRM) and Dynamic Financial Analysis (DFA) rely in great part on an appropriate modeling of the stochastic behavior of the various risky assets and processes that influence the performance of the company under consideration. A major challenge here is a more substantial and realistic description and modeling of the various complex dependence structures between such risks showing up on all scales. In this presentation, we propose some approaches towards modeling and generating (simulating) dependent risk processes in the framework of collective risk theory, in particular w.r.t. dependent claim number processes of Poisson type (homogeneous and non-homogeneous), and compound Poisson processes.

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Articles
Copyright
Copyright © ASTIN Bulletin 2004

References

Billingsley, P. (1986) Probability and Measure. Wiley, N.Y.Google Scholar
Blum, P., Dias, A. and Embrechts, P. (2002) The ART of dependence modelling: the latest advances in correlation analysis. In: Lane, M. (ed.): Alternative Risk Strategies, Risk Books, London.Google Scholar
Cambanis, S., Simons, G. and Stout, W. (1976) Inequalities for e k(X, Y) when the marginals are fixed. Zeitschrift für Wahrscheinlichkeitstheorie u. verw. Gebiete 36, 285294.CrossRefGoogle Scholar
Campbell, J.T. (1934) The Poisson correlation function. Proc. Edinb. Math. Soc., II. Ser. 4, 1826.CrossRefGoogle Scholar
Cox, D.R. and Lewis, P.A.W. (1972) Multivariate point processes. Proc. 6th Berkeley Sympos. Math. Statist. Probab., 3, 401448, University of California, 1970.Google Scholar
Daley, D.J. and Vere-Jones, D. (1988) An Introduction to the Theory of Point Processes. Springer, N.Y. Google Scholar
Embrechts, P., Straumann, D. and McNeil, A.J. (2000) Correlation: pitfalls and alternatives. In: Embrechts, P. (ed.): Extremes and Integrated Risk Management. Risk Books, London. Google Scholar
Embrechts, P., McNeil, A.J. and Straumann, D. (2002) Correlation and dependence in risk management: properties and pitfalls. In: Dempster, M.A.H. (ed.): Risk Management: Value at Risk and Beyond. Cambridge Univ. Press, Cambridge.Google Scholar
Gass, S.I. (1969) Linear Programming: Methods and Applications. McGraw-Hill Book Company and Kogakusha Company, Ltd., Tokyo, 3rd ed.Google Scholar
Griffiths, R.C., Milne, R.K. and Wood, R. (1979) Aspects of correlation in bivariate Poisson distributions and processes. Australian Journal of Statistics 21(3), 238255.CrossRefGoogle Scholar
Hoeffding, W. Maßstabinvariante Korrelationstheorie. Schriften des Mathematischen Seminars und des Instituts für Angewandte Mathematik 5, 181233, Universität Berlin.Google Scholar
Hoffman, A.J. (1963) On simple linear programming problems. In: Klee (ed.): Convexity, vol. 7, 317327, Providence, R.I., Proc. Symp. Pure Math. CrossRefGoogle Scholar
Joe, H. (1997) Multivariate Models and Dependence Concepts. Chapman & Hall, London.Google Scholar
Johnson, N.L., Kotz, S. and Balakrishnan, N. (1997) Discrete Multivariate Distributions. Wiley, N.Y.Google Scholar
Junker, M. and May, A. (2002) Measurement of aggregate risk with copulas. Caesar preprint 021, Center of Advanced European Studies and Research, Bonn, Germany. Google Scholar
Kingman, J.F.C. (1993) Poisson Processes. Clarendon Press, Oxford.Google Scholar
Kocherlakota, S. and Kocherlakota, K. (1992) Bivariate Discrete Distributions. Dekker, M., N.Y. Google Scholar
Lakshminarayana, J., Pandit, S.N.N. and Rao, K.S. (1999) On a bivariate Poisson distribution. Communications in Statistics – Theory and Methods 28(2), 267276.CrossRefGoogle Scholar
Lee, M.-L.T. (1996) Properties and applications of the Sarmanov family of bivariate distributions. Communications in Statistics – Theory and Methods 25(6), 12071222.Google Scholar
Mari, D.D. and Kotz, S. (2001) Correlation and Dependence. Imp. College Press, London. Google Scholar
Müller, A. and Bäuerle, N. (1998) Modelling and comparing dependencies in multivariate risk portfolios. ASTIN Bulletin 28(1), 5976.Google Scholar
Nelsen, R.B. (1987) Discrete bivariate distributions with given marginals and correlation. Communications in Statistics – Simulation 16(1), 199208.CrossRefGoogle Scholar
Nelsen, R.B. (1999) An Introduction to Copulas. Lecture Notes in Statistics 139, Springer, N.Y.Google Scholar
Neslehova, J. (2004) Dependence of Non-Continuous Random Variables. Ph.D. Thesis, University of Oldenburg.Google Scholar
Reiss, R.-D. (1993) A Course on Point Processes. Springer, N.Y. Google Scholar
Rodrigues, J., Cid, J.E.R. and Achcar, J.A. (2002) Bayesian analysis for the superposition of two dependent nonhomogeneous Poisson processes. Communications in Statistics – Theory and Methods 31(9), 14671478.CrossRefGoogle Scholar
Rolski, T., Schmidli, H., Schmidt, V. and Teugels, J. (1998) Stochastic Processes for Insurance and Finance. Wiley, N.Y. Google Scholar
Rachev, S.T. and Rüschendorf, L. (1998) Mass Transportation Problems. Volume I: Theory. Springer, N.Y. Google Scholar
Rachev, S.T. and Rüschendorf, L. (1998) Mass Transportation Problems. Volume II: Applications. Springer, N.Y. Google Scholar
Teicher, H. (1954) On the multivariate Poisson distribution. Skandinavisk Aktuarietidskrift 37, 19.Google Scholar