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Optimal Versus Alternative Economic Capital Allocation in Banking

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High Performance Computing in Science and Engineering ‘13

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Abstract

Burghof and Müller (High Performance Computing in Science and Engineering ’11. Springer, Heidelberg, 2012) already describes a basic model of economic capital allocation in banking. Furthermore, Burghof and Müller (High Performance Computing in Science and Engineering ’12. Springer, Heidelberg, 2013) addresses the model’s heuristic solving algorithm in the form of threshold accepting by focusing on the algorithm’s parameterization. The current report finally focusses on emphasizing the superiority of the optimal method of economic capital allocation. Thereto, the report restricts itself to an introductory model case providing optimal conditions in the form of an informed central management of the model bank.

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Notes

  1. 1.

    See Burghof and Müller [2, 3] for information on the optimal allocation method. Burghof and Müller [3] also provides a quick introduction to the expected return and the uniform method.

  2. 2.

    See e.g. Knuth [6, pp. 409–426] for further information on binary search algorithms.

  3. 3.

    See Gilli and Winker [5] for an overview concerning categories of heuristic optimization algorithms. See also Maringer [7, pp. 38–76] for a slightly different alternative introduction to heuristic optimization.

  4. 4.

    See e.g. Gilli and Winker [5].

  5. 5.

    Differences compared to the data from previous annual reports result from the different development stages of the research.

  6. 6.

    See Burghof and Müller [1, pp. 205–210] for a previous version of the modeling of a Bayesian learning bank management.

  7. 7.

    See Burghof and Sinha [4] for an investigation of herding in context with VAR-limit-systems without the consideration of optimization.

References

  1. H.-P. Burghof, J. Müller, Allocation of economic capital in banking: a simulation approach, in The VaR Modeling Handbook, ed. by G.N. Gregoriou (McGraw-Hill, New York u. a., 2009)

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  2. H.-P. Burghof, J. Müller, Allocation of economic capital in banking: a simulation approach, in High Performance Computing in Science and Engineering ’11, ed. by W.E. Nagel, D.B. Kröner, M. Resch (Springer, Heidelberg u. a., 2012)

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  3. H.-P. Burghof, J. Müller, Parameterization of threshold accepting: the case of economic capital allocation, in High Performance Computing in Science and Engineering ’12, ed. by W.E. Nagel, D.B. Kröner, M. Resch (Springer, Heidelberg u. a., 2013)

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  4. H.-P. Burghof, T. Sinha, Capital allocation with value-at-risk – the case of informed traders and herding. J. Risk 7(4), 47–73 (2005)

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  5. M. Gilli, P. Winker, Heuristic optimization methods in econometrics, in Hand-Book of Computational Econometrics, ed. by D.A. Belsley, E.J. Kontoghiorghes (Wiley, Chichester, 2009)

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  6. D. Knuth, The Art of Computer Programming 3 (Addison-Wesley Longman, Amsterdam, 1997)

    MATH  Google Scholar 

  7. D. Maringer, Portfolio Management with Heuristic Optimization, ed. by H. Amman, B. Rustem (Springer, Dordrecht, 2005)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Lehrstuhl für Bankwirtschaft und Finanzdienstleistungen, Universität Hohenheim, 70599, Stuttgart, Germany

    H.-P. Burghof & J. Müller

Authors
  1. H.-P. Burghof
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  2. J. Müller
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Corresponding author

Correspondence to J. Müller .

Editor information

Editors and Affiliations

  1. Zentrum für Informationsdienste und Hochleistungsrechnen (ZIH), Technische Universität Dresden, Dresden, Germany

    Wolfgang E. Nagel

  2. Abteilung für Angewandte Mathematik, Universität Freiburg, Freiburg, Germany

    Dietmar H. Kröner

  3. Höchstleistungsrechenzentrum Stuttgart (HLRS), Universität Stuttgart, Stuttgart, Germany

    Michael M. Resch

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Burghof, HP., Müller, J. (2013). Optimal Versus Alternative Economic Capital Allocation in Banking. In: Nagel, W., Kröner, D., Resch, M. (eds) High Performance Computing in Science and Engineering ‘13. Springer, Cham. https://doi.org/10.1007/978-3-319-02165-2_41

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