Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-23T14:19:21.232Z Has data issue: false hasContentIssue false

Marginal Decomposition of Risk Measures

Published online by Cambridge University Press:  17 April 2015

Gary G. Venter
Affiliation:
John A. Major
Affiliation:
Rodney E. Kreps
Affiliation:
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

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.

Type
Articles
Copyright
Copyright © ASTIN Bulletin 2006

References

Acerbi, C. (2002) Spectral measures of risk: A coherent representation of subjective risk aversion, Journal of Banking & Finance, 26.Google Scholar
Artzner, P., Delbaen, F., Eber, J.-M. and Heath, D. (1999) Coherent measures of risk, Mathematical Finance, 9(3), 203228.CrossRefGoogle Scholar
Ballotta, L. (2004) Alternative framework for the fair valuation of life insurance contracts: a Lévy process based model, AFIR Colloquium.CrossRefGoogle Scholar
Kalkbrener, M. (2005) An Axiomatic Approach to Capital Allocation, Mathematical Finance, July.CrossRefGoogle Scholar
Kreps, R. (2005) Riskiness Leverage Models, Proceedings of the Casualty Actuarial Society.Google Scholar
Kusuoka, S. (2001) On law invariant coherent risk measures, in: Advances in Mathematical Economics, 3, 8395, Springer: Tokyo.CrossRefGoogle Scholar
Mango, D.F. (2003) Capital Consumption: An Alternative Methodology for Pricing Reinsurance, Casualty Actuarial Society Forum, Winter, 351378.Google Scholar
Merton, R. and Perold, A. (1993) Theory of Risk Capital in Financial Firms, Journal of Applied Corporate Finance, Fall, 1632.CrossRefGoogle Scholar
Major, J.A. (2004) Gradients of Risk Measures: Theory and Application to Catastrophe Risk Management and Reinsurance Pricing, Casualty Actuarial Society Forum, Winter.Google Scholar
Møller, T. (2003) Stochastic orders in dynamic reinsurance markets, ASTIN Colloquium Papers.CrossRefGoogle Scholar
Myers, S. and Read, J. (2001) Capital Allocation for Insurance Companies, Journal of Risk and Insurance, 68(4).CrossRefGoogle Scholar
Mildenhall, S. (2004) A Note on the Myers and Read Capital Allocation Formula, North American Actuarial Journal, 8(2).CrossRefGoogle Scholar
Phillips, R., Cummins, J.D. and Allen, F. (1998) Financial Pricing of Insurance in the Multiple-Line Insurance Company, The Journal of Risk and Insurance, 65(4), 597636.CrossRefGoogle Scholar
Ruhm, D. (2003) Distribution-Based Pricing Formulas Are Not Arbitrage-Free, Proceedings of the Casualty Actuarial Society.Google Scholar
Ruhm, D. and Mango, D. (2003) A Risk Charge Calculation Based on Conditional Probability, Bowles, Thomas P. Jr. Symposium, Georgia State University.Google Scholar
Sherris, M. (2004) Solvency, Capital Allocation and Fair Rate of Return in Insurance, UNSW working paper.Google Scholar
Tasche, D. (2000) Risk contributions and performance measurement, Report of the Lehrstuhl fur mathematische Statistik, T.U. Munchen.Google Scholar
Tasche, D. (2002) Expected shortfall and beyond, Journal of Banking and Finance, 26, 15191533.CrossRefGoogle Scholar
Uryasev, S. (1995a) Derivatives of Probability Functions and Integrals over Sets Given by Inequalities, Journal of Computational and Applied Mathematics, 56, 197223.CrossRefGoogle Scholar
Uryasev, S. (1995b) Derivatives of Probability Functions and Some Applications, Annals of Operations Research, 56, 287311.CrossRefGoogle Scholar
Uryasev, S. (1999) Derivatives of Probability and Integral Functions: General Theory and Examples, in Encyclopedia of Optimization, Floudas, C.A. and Pardalos, P.M., eds., Kluwer Academic Publishers.Google Scholar
Venter, G. (1991) Premium Calculation Implications of Reinsurance without Arbitrage, ASTIN Bulletin, 21(2).CrossRefGoogle Scholar
Venter, G. (2004) Capital Allocation Survey With Commentary, North American Actuarial Journal, 8(2).CrossRefGoogle Scholar
Venter, G., Barnett, J. and Owen, M. (2004) Market Value of Risk Transfer: Catastrophe Reinsurance Case, AFIR Colloquium.Google Scholar