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Marginal Decomposition of Risk Measures

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  • Venter, Gary G.
  • Major, John A.
  • Kreps, Rodney E.

Abstract

The marginal approach to risk and return analysis compares the marginal return from a business decision to the marginal risk imposed. Allocation distributes the total company risk to business units and compares the profit/risk ratio of the units. These approaches coincide when the allocation actually assigns the marginal risk to each business unit, i.e., when the marginal impacts add up to the total risk measure. This is possible for one class of risk measures (scalable measures) under the assumption of homogeneous growth and by a subclass (transformed probability measures) otherwise. For homogeneous growth, the allocation of scalable measures can be accomplished by the directional derivative. The first well known additive marginal allocations were the Myers-Read method from Myers and Read (2001) and co-Tail Value at Risk, discussed in Tasche (2000). Now we see that there are many others, which allows the choice of risk measure to be based on economic meaning rather than the availability of an allocation method. We prefer the term “decomposition†to “allocation†here because of the use of the method of co-measures, which quantifies the component composition of a risk measure rather than allocating it proportionally to something. Risk adjusted profitability calculations that do not rely on capital allocation still may involve decomposition of risk measures. Such a case is discussed. Calculation issues for directional derivatives are also explored.

Suggested Citation

  • Venter, Gary G. & Major, John A. & Kreps, Rodney E., 2006. "Marginal Decomposition of Risk Measures," ASTIN Bulletin, Cambridge University Press, vol. 36(2), pages 375-413, November.
  • Handle: RePEc:cup:astinb:v:36:y:2006:i:02:p:375-413_01
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    Cited by:

    1. Battulga Gankhuu, 2024. "Derivatives of Risk Measures," Papers 2404.09646, arXiv.org.
    2. Stephen J. Mildenhall, 2017. "Actuarial Geometry," Risks, MDPI, vol. 5(2), pages 1-44, June.

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