Volume 5, Issue 1-1, February 2016, Page: 1-13
Identification of Company-Specific Stress Scenarios in Non-Life Insurance
Wiltrud Weidner, Institute for Risk and Insurance, Leibniz University Hanover, Hanover, Germany
J.-Matthias Graf von der Schulenburg, Institute for Risk and Insurance, Leibniz University Hanover, Hanover, Germany
Received: Apr. 18, 2015;       Accepted: Apr. 23, 2015;       Published: Jun. 10, 2015
DOI: 10.11648/j.acm.s.2016050101.11      View  3866      Downloads  108
This paper provides an effective approach, known as dynamic financial analysis, to the systematic development of stress scenarios for the risk profile of non-life insurers, which can be used in risk analysis for the regulatory and rating assessment. The determination of company-specific stress scenarios is demonstrated, the resulting critical scenarios are described. Non-linear dependencies have a significant impact on the scenarios, some of which have not previously been adequately considered are introduced. The recent global financial crisis illustrates that the analysis of extreme events, which can affect both sides of the balance sheet, is essential in an asset-liability management context.
Non-Life Insurance, Solvency II, Risk Management, Dynamic Financial Analysis, Stress Testing, Copulas
To cite this article
Wiltrud Weidner, J.-Matthias Graf von der Schulenburg, Identification of Company-Specific Stress Scenarios in Non-Life Insurance, Applied and Computational Mathematics. Special Issue: Computational Methods in Monetary and Financial Economics. Vol. 5, No. 1-1, 2016, pp. 1-13. doi: 10.11648/j.acm.s.2016050101.11
J. Berkowitz, “A coherent framework for stress testing”, Journal of Risk, vol. 2, no. 2, 2000, pp. 1-11.
BaFin, Rundschreiben 1/2004 (VA) – Durchführung von Stresstests, Bonn: Bundesanstalt für Finanzdienstleistungsaufsicht, February 2004.
FSA, Stress and scenario testing (CP 08/24), London: Financial Services Authority, 2008.
BCBS, Amendment to the capital accord to incorporate market risk, Basel: Basel Committee on Banking Supervision, November 2005.
G. Bonti, M. Kalkbrener, C. Lotz, and G. Stahl, “Credit risk concentrations under stress”, Journal of Credit Risk, vol. 2, no. 3, 2006, pp. 115-136.
ECB, Financial stability report, Frankfurt a. M.: European Central Bank, June 2006.
H.-J. Zwiesler, “Asset-Liability-Management – die Versicherung auf dem Weg von der Planungsrechnung zum Risikomanagement”, in: K. Spremann (ed.), Versicherungen im Umbruch, Berlin: Springer, 2005, pp. 117-131.
P. M. Achleitner, J. Biebel, and D. Wichels, “Does WTC matter for the investment policy of p/c insurance companies?”, The Geneva Papers on Risk and Insurance, vol. 27, no. 2, 2002, pp. 275-282.
CAS, DFA Handbook, Arlington: Casualty Actuarial Society, June 1999.
S. P. Lowe, and J. N. Stanard, “An integrated dynamic financial analysis and decision support system for a property catastrophe reinsurer”, ASTIN Bulletin, vol. 27, no. 2, 1997, pp. 339-371.
R. Kaufmann, A. Gadmer, and R. Klett, “Introduction to dynamic financial analysis”, ASTIN Bulletin, vol. 31, no. 1, 2001, 213-249.
P. Blum, M. Dacorogna, P. Embrechts, T. Neghaiwi, and H. Niggli, “Using DFA for modeling the impact of foreign exchange risks on reinsurance decisions”, Casualty Actuarial Society Forum, 2001, pp. 49-93.
S. P. D’Arcy, and R. Gorvett, “The use of dynamic financial analysis to determine whether an optimal growth rate exists for a property-liability insurer”, Journal of Risk and Insurance, vol. 71, no. 4, 2004, pp. 583-615.
M. Eling, T. Parnitzke, T., and H. Schmeiser, “Management strategies and dynamic financial analysis”, Variance, vol. 2, no. 1, 2008, pp. 52-70.
A. Sklar, “Fonctions de répartition à n dimensions et leurs marges”, Publ. Inst. Statist. Univ. Paris, vol. 8, 1959, pp. 229-231.
S. Wang, “Aggregation of correlated risk portfolios: models and algorithms”, Proceedings of the Casualty Actuarial Society, vol. 85, no. 163, 1998, pp. 848-939.
E. W. Frees, and E. A. Valdez, “Understanding relationships using copulas”, North American Actuarial Journal, vol. 2, no. 1, 1998, pp. 1-25.
P. Embrechts, F. Lindskog, and A. McNeil, “Modelling dependence with copulas and applications to risk management”, in: S.T. Rachev (ed.), Handbook of Heavy Tailed Distributions in Finance, Amsterdam: Elsevier, 2001, pp. 329-384.
Y. Malevergne, and D. Sornette, “Testing the Gaussian copula hypothesis for financial assets dependencies”, Quantitative Finance, vol. 3, no. 4, 2003, pp. 231-250.
E. Kole, K. Koedijk, and M. Verbeek, “Selecting copulas for risk management”, Journal of Banking & Finance, vol. 31, no. 8, 2007, pp. 2405-2423.
A. Dias, and P. Embrechts, “Testing for structural changes in exchange rates' dependence beyond linear correlation”, The European Journal of Finance, vol. 15, no. 7-8, 2009, pp. 619-637.
N. Whelan, “Sampling from Archimedean copulas”, Quantitative Finance, vol. 4, no. 3, 2004, pp. 339-352.
M. Hofert, “Sampling Archimedean copulas”, Computational Statistics & Data Analysis, vol. 52, no. 12, 2008, pp. 5163-5174.
A. McNeil, “Sampling nested Archimedean copulas”, Journal of Statistical Computation and Simulation, vol. 78, no. 6, 2008, pp. 567-581.
M. Eling, and D. Toplek, “Modeling and management of nonlinear dependencies – copulas in dynamic financial analysis”, Journal of Risk and Insurance, vol. 76, no. 3, 2009, pp. 651-681.
D. Diers, “Management strategies in multi-year enterprise risk management”, The Geneva Papers on Risk and Insurance, vol. 36, 2011, pp. 107-125.
J. Han, and M. Kamber, Data Mining: Concepts and Techniques, San Francisco: Morgan Kaufmann, 2006.
D. Wishart, “An algorithm for Hierarchical classifications”, Biometrics, vol. 25, no. 1, 1969, pp. 165-170.
R. M. Cormack, “A review of classification”, Journal of the Royal Statistical Society, vol. 134, no. 3, 1971, pp. 321-367.
M. R. Anderberg, Cluster Analysis or Applications, New York: Academic Press, 1973.
D. Scheibler, and W. Schneider, “Monte Carlo tests of the accuracy of cluster analysis algorithm: a comparison of hierarchical and nonhierarchical methods”, Multivariate Behavioral Research, vol. 20, no. 3, 1985, pp. 283-304.
J. H. Ward, “Hierarchical grouping to optimize an objective function”, Journal of the American Statistical Association, vol. 58, no. 301, 1963, pp. 236-244.
G. N. Lance, and W. T. Williams, “A general theory of classificatory sorting strategies”, Computer Journal, vol. 9, no. 4, 1967, pp. 373-380.
P. Mangiameli, S. K. Chen, and D. West, “A comparison of SOM neural network and hierarchical clustering methods”, European Journal of Operational Research, vol. 93, no. 2, 1996, pp. 402-417.
P. Embrechts, A. McNeil, and D. Straumann, “Correlation and dependence in risk management: properties and pitfalls”, in: M. A. H. Dempster (ed.), Risk Management: Value at Risk and Beyond, Cambridge: Cambridge University Press, 2002, pp. 176-223.
C. Hering, M. Hofert, J.-F. Mai, and M. Scherer, “Constructing hierarchical Archimedean copulas with Lévy subordinators”, Journal of Multivariate Analysis, vol. 101, no. 6, 2010, pp. 1428-1433.
R. B. Nelsen, An Introduction to Copulas, New York: Springer, 2006.
G. Fusai, and A. Roncoroni, Implementing Models in Quantitative Finance: Methods and Cases, Berlin Heidelberg: Springer, 2008.
C. Hering, M. Hofert, “Goodness-of-fit tests for Archimedean copulas in high dimensions”, in: K. Glau, M. Scherer, and R. Zagst (ed.), Innovations in Quantitative Risk Management, Springer, 2013, pp. 357-373.
O. Horn, and H.-J. Zwiesler, “Die Problematik der Anwendung von Managementregeln im Risikomanagement”, in D. Zietsch (ed.), Beiträge zu aktuellen Themen des Versicherungsmarktes, Karlsruhe: Verlag Versicherungswirtschaft, 2008, pp. 79-125.
W.-R. Heilmann, Fundamentals of Risk Theory, Karlsruhe: Verlag Versicherungswirtschaft, 1988.
P. Artzner, F. Delbaen, J.-M. Eber, and D. Heath, “Coherent measures of risk”, Mathematical Finance, vol. 9, 1999, pp. 203-228.
P. Albrecht, Grundprinzipien der Finanz- und Versicherungsmathematik, Stuttgart: Schäffer-Poeschel Verlag, 2007.
W. F. Sharpe, “Mutual fund performance”, Journal of Business, vol. 39, no. 1, 1966, pp. 119-138.
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