Allocation of Economic Capital in Banking: A Simulation Approach

  • H.-P. Burghof
  • J. Müller


The approach describes the difficulties implied through consistently equating a bank’s allocation of economic capital with an allocation of decision rights in the form of value-at-risk limits. These days, risk measurement through value-at-risk methods is widespread. Using these methods strategically in order to optimize the return to risk ratio actively on an overall bank level is hardly developed. Thereto we model a bank’s central planner coping with correlations’ uncertainty and learning about the limit addressees’ skills. In order to face the underlying mixed integer non linear program the model provides the central planner with a heuristic optimization approach. According to the given information and the assumed rationality of the central planner, resulting limit allocations are optimal in a portfolio theoretical sense. The numerical model generates a data set providing evidence concerning this allocation method’s superiority compared to others.


Portfolio Optimization Business Unit Economic Capital Short Position Heuristic Optimization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Althöfer, I. and Koschnick, K.-U. (1991). On the convergence of threshold accepting. Applied Mathematics and Optimization 24(1), 183–195. CrossRefzbMATHMathSciNetGoogle Scholar
  2. 2.
    Burghof, H.-P. and Müller, J. (2009). Allocation of Economic Capital in Banking: A Simulation Approach. In: Handbook of Value at Risk (ed. Gregoriou, G. N.). McGraw-Hill, New York. Google Scholar
  3. 3.
    Burghof, H.-P. and Sinha, T. (2005). Capital allocation with value-at-risk—the case of informed traders and herding. Journal of Risk 7(4), 47–73. Google Scholar
  4. 4.
    Gilli, M., Kellezi, E. and Hysi, H. (2006). A data-driven optimization heuristic for downside risk minimization, Journal of Risk 8(3), 1–19. Google Scholar
  5. 5.
    Gilli, M. and Schumann, E. (2010). Optimal enough? Working paper. Cited 18 July 2011.
  6. 6.
    Gilli, M. and Winker, P. (2008). A review of heuristic optimization methods in econometrics. Swiss Finance Institute, Research Paper Series No. 12. Cited 18 July 2011.
  7. 7.
    Maringer, D. (2005). Portfolio Management with Heuristic Optimization (eds. Amman, H. and Rustem, B.). Springer, The Netherlands. Google Scholar
  8. 8.
    Rockafellar, R. T. and Uryasev, S. (2000). Optimization of conditional value-at-risk. Journal of Risk 2(3), 21–41. Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Lehrstuhl für Bankwirtschaft und FinanzdienstleistungenUniversität HohenheimStuttgartGermany

Personalised recommendations