Graph
2014
Abstract
risk in a large claims insurance market with bipartite
Key takeaways
AI
AI
- The paper assesses systemic risk in insurance markets using a bipartite graph structure.
- Heavy-tailed claims are modeled with Pareto distributions, impacting risk measures like Value-at-Risk.
- Uninsured losses depend on network connectivity and agent diversification preferences.
- The model reveals a conflict between individual agent interests and societal insurance needs when claims have infinite mean.
- Regular variation techniques are applied to understand extremal dependence between losses and their distribution across agents.
References (46)
- T. Adrian and M.K. Brunnermeier. CoVaR. Working Paper 17454, National Bureau of Economic Research, October 2011.
- H. Amini and A. Minca. Inhomogeneous Financial Networks and Con- tagious Links. Available at SSRN: http://ssrn.com/abstract=2518840 or http://dx.doi.org/10.2139/ssrn.2518840, 2014.
- B. Bollobás, C. Borgs, J. Chayes, and O. Riordan. Directed scale-free graphs. In Proceed- ings of the Fourteenth Annual ACM-SIAM Symposium on Discrete Algorithms (Baltimore, 2003), pages 132-139. ACM, New York, 2003.
- A.D. Bain. Insurance Spirals and the London Market. The Geneva Papers on Risk and Insurance -Issues and Practice, 24(2):228-242, 1999.
- A.D. Barbour, L. Holst, and S. Janson. Poisson Approximation. Oxford University Press, Oxford, 1992.
- B. Basrak. The Sample Autocorrelation Function of Non-Linear Time Series. PhD thesis, Rijksuniversteit Groningen, NL, 2000.
- B. Basrak, R.A. Davis, and T. Mikosch. Regular variation of GARCH processes. Stochastic Processes and their Applications, 99(1):95-115, 2002.
- R. Biard. Asymptotic multivariate finite-time ruin probabilities with heavy-tailed claim amounts: impact of dependence and optimal reserve allocation. Bulletin Francais d'Actuariat, 13(26), 2013.
- N.H. Bingham, C.M. Goldie, and J.L. Teugels. Regular Variation. Cambridge University Press Cambridge ; New York, 1987.
- J. Blanchet and Y. Shi. Stochastic Risk Networks: Modeling, Analysis and Efficient Monte Carlo. 2012.
- M. Boss, H. Elsinger, M. Summer, and S.Thurner. The network topology of the interbank market. Quantitative Finance, 4(6):677-684, 2004.
- A. Braverman and A. Minca. Networks of Common Asset Holdings: Aggregation and Measures of Vulnerability. Available at SSRN 2379669, 2014.
- Y. Bregman and C. Klüppelberg. Ruin estimation in multivariate models with Clayton dependence structure. Scand. Act. J., 2005(6):462-480, 2005.
- L. Breiman. On some limit theorems similar to the arc-sine law. Theory Probab. Appl., 10:323-331, 1965.
- C. T. Brownlees and R. Engle. Volatility, correlation and tails for systemic risk measure- ment., 2010. Working Paper Series, Department of Finance, NYU.
- M. K. Brunnermeier and P. Cheridito. Measuring and Allocating Systemic Risk. Available at SSRN: http://ssrn.com/abstract=2372472 or http://dx.doi.org/10.2139/ssrn.2372472, 2014.
- F. Caccioli, M. Shrestha, C. Moore, and J.D. Farmer. Stability analysis of financial conta- gion due to overlapping portfolios. SFI Working Paper: 2012-10-018, 2012.
- C. Chen, G. Iyengar, and C.C. Moallemi. An Axiomatic Approach to Systemic Risk. Management Science, 59(6):1373-1388, 2013.
- Munich Reinsurance Company. Annual report 2014. http://www.munichre.com/ site/corporate/get/documents_E-1770937763/mr/assetpool.shared/Documents/ 0_Corporate%20Website/_Financial%20Reports/2015/Annual%20Report%202014/ 302-08574_en.pdf.
- R. Cont, A. Moussa, and E.B. Santos. Network structure and systemic risk in banking systems. In J-P. Fouque and J.A. Langsam, editors, Handbook on Systemic Risk. Cambridge University Press, Cambridge, 2013.
- E.W. Cope, G. Mignola, G. Antonini, and R. Ugoccioni. Challenges and pitfalls in mea- suring operational risk from loss data. Journal of Operational Risk, 4(4):3-27, 2009.
- C.G. de Vries, G. Samorodnitsky, B.N. Jorgensen, S. Mandira, and J. Danielsson. Subad- ditivity re-examined: the case for Value-at-Risk. FMG Discussion Papers dp549, Financial Markets Group, November 2005.
- I. Eder and C. Klüppelberg. The first passage event for sums of dependent Lévy processes with applications to insurance risk. Ann. Appl. Probab., 19(6):2047-2079, 2009.
- I. Eder and C. Klüppelberg. Pareto Lévy measures and multivariate regular variation. Advances in Applied Probability, 44(1):117-138, 2012.
- L. Eisenberg and T. Noe. Systemic risks in financial systems. Management Science, 47:2236- 249, 2001.
- P. Embrechts, D.D. Lambrigger, and M.V. Wüthrich. Multivariate extremes and the ag- gregation of dependent risks: examples and counter-examples. Extremes, 12:107-127, 2009.
- P. Embrechts, J. Nešlehová, and M.V. Wüthrich. Additivity properties for Value-at-Risk under Archimedean dependence and heavy-tailedness. Insurance: Mathematics and Eco- nomics, 44(2):164-169, 2009.
- P. Gai and S. Kapadia. Contagion in financial networks. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Science, 466(2120):2401-2423, 2010.
- A.G. Haldane and R.M. May. Systemic risk in banking ecosystems. Nature, 469(7330):351- 355, 2011.
- H. Hoffmann, T. Meyer-Brandis, and G. Svindland. Risk-Consistent Conditional Systemic Risk Measures. 2014. preprint.
- H. Hult and F. Lindskog. Heavy-tailed insurance portfolios: buffer capital and ruin proba- bilities. Technical Report No. 1441, 2006.
- International Association of Insurance Supervisors (IAIS). Insurance and Financial Stabil- ity, 2011.
- R. Ibragimov. Portfolio diversification and value at risk under thick-tailedness. Quantitative Finance, 9(5):565-580, 2009.
- O. Kley and C. Klüppelberg. Bounds for randomly shared risk of heavy-tailed loss factors. arxiv:1503.03726[q-fin.RM], 2015.
- O. Kley, C. Klüppelberg, and G. Reinert. Conditional risk measures in a large claims market with bipartite graph structure. Preprint Technische Universität München, submitted, 2015.
- E Kromer, L. Overbeck, and K.A. Zilch. Systemic Risk Measures on General Probability Spaces. 2014.
- Y. Lin, J. Yu, and M.O. Peterson. Reinsurance Networks and Their Impact on Reinsurance Decisions: Theory and Empirical Evidence. Journal of Risk and Insurance, 2014.
- G. Mainik and L. Rüschendorf. On optimal portfolio diversification with respect to extreme risks. Finance and Stochastics, 14(4):593-623, 2010.
- G. Rasch. On general laws and the meaning of measurement in psychology. In Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, IV, pages 321-333. Berkeley, 1961.
- S.I. Resnick. Extreme Values, Regular Variation, and Point Processes. Springer, New York, 1987.
- S.I. Resnick. Heavy-Tail Phenomena. Springer, New York, 2007.
- H. Rootzén and C. Klüppelberg. A single number can't hedge against economic catastro- phes. AMBIO: A Journal of the Human Environment, 28(6), 1999.
- G. Samorodnitsky, S. Resnick, D. Towsley, R. Davis, A. Willis, and P. Wan. Nonstan- dard regular variation of in-degree and out-degree in the preferential attachment model. arXiv:1405.4882v1 [math.PR], 2014.
- S. von Dahlen and G. von Peter. Natural catastrohpes and global reinsurance -exploring the linkages. BIS Quarterly Review, 2012.
- C. Zhou. Dependence structure of risk factors and diversification effects. Insurance: Math- ematics and Economics, 46(3):531-540, 2010.
- J.-P. Zigrand. Systems and Systemic Risk in Finance and Economics, 2014. SRC Special Paper No 1.