Skip to main content
Log in

Bounds for Functions of Dependent Risks

  • Original Paper
  • Published:
Finance and Stochastics Aims and scope Submit manuscript

Abstract

The problem of finding the best-possible lower bound on the distribution of a non-decreasing function of n dependent risks is solved when n=2 and a lower bound on the copula of the portfolio is provided. The problem gets much more complicated in arbitrary dimensions. When no information on the structure of dependence of the random vector is available, we provide a bound on the distribution function of the sum of risks which we prove to be better than the one generally used in the literature.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Denuit M., Genest C., Marceau É. (1999) Stochastic bounds on sums of dependent risks. Insur Math Econ 25, 85–104

    Article  MathSciNet  MATH  Google Scholar 

  2. Dhaene J., Denuit M., Goovaerts M.J., Kaas R., Vyncke D. (2002) The concept of comonotonicity in actuarial science and finance: theory. Insur Math Econ 31, 3–33

    Article  MathSciNet  MATH  Google Scholar 

  3. Embrechts P., McNeil A.J., Straumann D. (2002). Correlation and dependence in risk management: properties and pitfalls. In: Dempster M. (eds). Risk management: value at risk and beyond. Cambridge University Press, Cambridge, pp. 176–223

    Google Scholar 

  4. Embrechts P., Höing A., Juri A. (2003) Using copulae to bound the Value-at-Risk for functions of dependent risks. Finance Stoch 7, 145–167

    Article  MathSciNet  MATH  Google Scholar 

  5. Frank M.J., Nelsen R.B., Schweizer B. (1987) Best-possible bounds for the distribution of a sum – a problem of Kolmogorov. Probab Theory Related Fields 74, 199–211

    Article  MathSciNet  MATH  Google Scholar 

  6. Makarov G.D. (1981) Estimates for the distribution function of the sum of two random variables with given marginal distributions. Theory Probab Appl 26, 803–806

    Article  Google Scholar 

  7. Moscadelli, M. The modelling of operational risk: experience with the analysis of the data collected by the Basel Committee. Temi di discussione N. 517 Banca d’Italia, URL: http://www.bancaditalia.it/ricerca/consultazioni/temidi/td04/td517/td_517/tema_517.pdf (2004)

  8. Nelsen R.B. (1999) An introduction to copulas. Springer, Berlin Heidelberg New York

    MATH  Google Scholar 

  9. Rachev S.T., Rüschendorf L. (1998) Mass transportation problems, vol. I–II. Springer, Berlin Heidelberg New York

    MATH  Google Scholar 

  10. Rüschendorf L. (1982) Random variables with maximum sums. Adv Appl Probab 14, 623–632

    Article  MATH  Google Scholar 

  11. Sklar A. (1973) Random variables, joint distribution functions, and copulas. Kybernetika 9, 449–460

    MathSciNet  MATH  Google Scholar 

  12. Williamson R.C., Downs T. (1990) Probabilistic arithmetic. I. Numerical methods for calculating convolutions and dependence bounds. Int J Approx Reason 4, 89–158

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Giovanni Puccetti.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Embrechts, P., Puccetti, G. Bounds for Functions of Dependent Risks. Finance Stoch 10, 341–352 (2006). https://doi.org/10.1007/s00780-006-0005-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00780-006-0005-5

Keywords

Mathematics Subject Classifications (2000)

JEL Classifications

Navigation