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Compatibility between pricing rules and risk measures: The CCVaR

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Author Info
Alejandro Balbás ()
Raquel Balbás ()
Abstract

This paper has considered a risk measure ρ and a (maybe incomplete and/or imperfect) arbitrage-free market with pricing rule π. They are said to be compatible if there are no reachable strategies y such that π (y) remains bounded and ρ(y) is close to - ∞. We show that the lack of compatibility leads to meaningless situations in financial or actuarial applications. The presence of compatibility is characterized by properties connecting the Stochastic Discount Factor of π and the sub-gradient of ρ . Consequently, several examples pointing out that the lack of compatibility may occur in very important pricing models are yielded. For instance the CVaR and the DPT are not compatible with the Black and Scholes model or the CAPM. We prove that for a given incompatible couple (π,ρ) we can construct a minimal risk measure ρπ compatible with π and such that ρπ ≥ ρ . This result is particularized for the CVaR and the CAPM and the Black and Scholes model. Therefore we construct the Compatible Conditional Value at Risk (CCVaR). It seems that the CCVaR preserves the good properties of the CVaR and overcomes its shortcomings.

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Paper provided by Universidad Carlos III, Departamento de Economía de la Empresa in its series Business Economics Working Papers with number wb090201.

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Date of creation: Jan 2009
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Handle: RePEc:cte:wbrepe:wb090201

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Related research
Keywords: Risk Measure; Pricing Rule; Compatibility; Compatible Conditional Value at Risk;

Find related papers by JEL classification:
G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies
G23 - Financial Economics - - Financial Institutions and Services - - - Pension Funds; Other Private Financial Institutions

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  1. Ogryczak, Wlodzimierz & Ruszczynski, Andrzej, 1999. "From stochastic dominance to mean-risk models: Semideviations as risk measures," European Journal of Operational Research, Elsevier, vol. 116(1), pages 33-50, July. [Downloadable!] (restricted)
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  2. Balbás, Alejandro & Balbás, Beatriz & Heras, Antonio, 2009. "Optimal reinsurance with general risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 44(3), pages 374-384, June. [Downloadable!] (restricted)
  3. R. Rockafellar & Stan Uryasev & Michael Zabarankin, 2006. "Generalized deviations in risk analysis," Finance and Stochastics, Springer, vol. 10(1), pages 51-74, 01. [Downloadable!] (restricted)
  4. Goovaerts, Marc J. & Kaas, Rob & Dhaene, Jan & Tang, Qihe, 2004. "Some new classes of consistent risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 34(3), pages 505-516, June. [Downloadable!] (restricted)
  5. Alexander Schied, 2007. "Optimal investments for risk- and ambiguity-averse preferences: a duality approach," Finance and Stochastics, Springer, vol. 11(1), pages 107-129, January. [Downloadable!] (restricted)
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  6. Barbarin, Jerome & Devolder, Pierre, 2005. "Risk measure and fair valuation of an investment guarantee in life insurance," Insurance: Mathematics and Economics, Elsevier, vol. 37(2), pages 297-323, October. [Downloadable!] (restricted)
  7. Alexander, S. & Coleman, T.F. & Li, Y., 2006. "Minimizing CVaR and VaR for a portfolio of derivatives," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 583-605, February. [Downloadable!] (restricted)
  8. Andrzej Ruszczynski & Alexander Shapiro, 2004. "Optimization of Convex Risk Functions," Risk and Insurance 0404001, EconWPA, revised 08 Oct 2005. [Downloadable!]
  9. Hans Föllmer & Alexander Schied, 2002. "Convex measures of risk and trading constraints," Finance and Stochastics, Springer, vol. 6(4), pages 429-447. [Downloadable!] (restricted)
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