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Risk Measures in Simulation-Based Business Valuation: Classification of Risk Measures in Risk Axiom Systems and Application in Valuation Practice

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  • Dietmar Ernst

    (International School of Finance (ISF), Nuertingen-Geislingen University, Sigmaringer Straße 25, 72622 Nürtingen, Germany)

Abstract

Simulation-based company valuations are based on an analysis of the risks in the company to be valued. This means that risk analysis is decisively important in a simulation-based business valuation. The link between risk measures, risk conception and risk axiom systems has not yet been sufficiently elaborated for simulation-based business valuations. The aim of this study was to determine which understanding of risk underlies simulation-based business valuations and how this can be implemented via suitable risk measures in simulation-based business valuations. The contribution of this study is providing guidance for the methodologically correct selection of appropriate risk measures. This will help with avoiding valuation errors. To this end, the findings were combined from risk axiom systems with the valuation equations of simulation-based business valuations. Only position-invariant risk measures are suitable for simulation-based business valuations.

Suggested Citation

  • Dietmar Ernst, 2023. "Risk Measures in Simulation-Based Business Valuation: Classification of Risk Measures in Risk Axiom Systems and Application in Valuation Practice," Risks, MDPI, vol. 11(1), pages 1-14, January.
  • Handle: RePEc:gam:jrisks:v:11:y:2023:i:1:p:13-:d:1027451
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    References listed on IDEAS

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    1. Pascal Bruhn & Dietmar Ernst, 2022. "Assessing the Risk Characteristics of the Cryptocurrency Market: A GARCH-EVT-Copula Approach," JRFM, MDPI, vol. 15(8), pages 1-28, August.
    2. Acerbi, Carlo, 2002. "Spectral measures of risk: A coherent representation of subjective risk aversion," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1505-1518, July.
    3. Christian S. Pedersen & Stephen E. Satchell, 1998. "An Extended Family of Financial-Risk Measures," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 23(2), pages 89-117, December.
    4. Uwe Wehrspohn & Dietmar Ernst, 2022. "When Do I Take Which Distribution?," SpringerBriefs in Business, Springer, number 978-3-031-07330-4, July.
    5. Ingo Hoffmann & Christoph J. Börner, 2020. "Tail models and the statistical limit of accuracy in risk assessment," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 21(3), pages 201-216, July.
    6. Dietmar Ernst, 2022. "Simulation-Based Business Valuation: Methodical Implementation in the Valuation Practice," JRFM, MDPI, vol. 15(5), pages 1-17, April.
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