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Coherent Pricing

Author

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  • Balbás, Alejandro
  • Balbás, Beatriz
  • Balbás, Raquel

Abstract

Recent literature proved the existence of an unbounded market price of risk (MPR) or maximum generalized Sharpe ratio (GSR) if one combines the most important Brownian-motion-linked arbitrage free pricing models with a coherent and expectation bounded risk measure. Furthermore, explicit sequences of portfolios with a theoretical (risk, return) diverging to (􀀀1;+1) were constructed and their performance tested. The empirical evidence revealed that the divergence to (􀀀1;+1) is only theoretical (not real), but the MPR is much larger than the GSR of the most important international stock indices. The natural question is how to modify the available pricing models so as to prevent the caveat above. The theoretical MPR cannot equal inf nity but must be large enough (consistent with the empirical findings) and this will be the focus of this paper. It will be shown that every arbitrage free pricing model can be improved in such a manner that the new stochastic discount factor (SDF) satisfie the two requirements above, and the newMPR becomes bounded but large enough. This is important for several reasons; Firstly, if the existent models predict unrealistic price evolutions then these mistakes may imply important capital losses to practitioners and theoretical errors to researchers. Secondly, the lack of an unbounded MPR is much more coherent and consistent with equilibrium. Finally, the major discrepancies between the initial pricing model and the modifie one will affect the tails of their SDF, which seems to justify several empirical caveats of previous literature. For instance, it has been pointed out that it is not easy to explain the real quotes of many deeply OTM options with the existing pricing models.

Suggested Citation

  • Balbás, Alejandro & Balbás, Beatriz & Balbás, Raquel, 2016. "Coherent Pricing," INDEM - Working Paper Business Economic Series 22932, Instituto para el Desarrollo Empresarial (INDEM).
  • Handle: RePEc:cte:idrepe:22932
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    References listed on IDEAS

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    1. Robert J. Aumann & Roberto Serrano, 2008. "An Economic Index of Riskiness," Journal of Political Economy, University of Chicago Press, vol. 116(5), pages 810-836, October.
    2. 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.
    3. David B. Brown & Melvyn Sim, 2009. "Satisficing Measures for Analysis of Risky Positions," Management Science, INFORMS, vol. 55(1), pages 71-84, January.
    4. Basak, Suleyman & Shapiro, Alexander, 2001. "Value-at-Risk-Based Risk Management: Optimal Policies and Asset Prices," Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 371-405.
    5. Zhao, Pan & Xiao, Qingxian, 2016. "Portfolio selection problem with liquidity constraints under non-extensive statistical mechanics," Chaos, Solitons & Fractals, Elsevier, vol. 82(C), pages 5-10.
    6. Hans Föllmer & Alexander Schied, 2002. "Convex measures of risk and trading constraints," Finance and Stochastics, Springer, vol. 6(4), pages 429-447.
    7. R. Rockafellar & Stan Uryasev & Michael Zabarankin, 2006. "Generalized deviations in risk analysis," Finance and Stochastics, Springer, vol. 10(1), pages 51-74, January.
    8. Goovaerts, Marc J. & Laeven, Roger J.A., 2008. "Actuarial risk measures for financial derivative pricing," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 540-547, April.
    9. Dupačová, Jitka & Kopa, Miloš, 2014. "Robustness of optimal portfolios under risk and stochastic dominance constraints," European Journal of Operational Research, Elsevier, vol. 234(2), pages 434-441.
    10. Balbás, Alejandro & Balbás, Beatriz & Balbás, Raquel, 2016. "Good deals and benchmarks in robust portfolio selection," European Journal of Operational Research, Elsevier, vol. 250(2), pages 666-678.
    11. Oleg Bondarenko, 2014. "Why Are Put Options So Expensive?," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 4(03), pages 1-50.
    12. Schachermayer, W., 1992. "A Hilbert space proof of the fundamental theorem of asset pricing in finite discrete time," Insurance: Mathematics and Economics, Elsevier, vol. 11(4), pages 249-257, December.
    13. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    14. Hirbod Assa, 2015. "Trade-off Between Robust Risk Measurement and Market Principles," Journal of Optimization Theory and Applications, Springer, vol. 166(1), pages 306-320, July.
    15. Patrick Cheridito & Tianhui Li, 2009. "Risk Measures On Orlicz Hearts," Mathematical Finance, Wiley Blackwell, vol. 19(2), pages 189-214, April.
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    More about this item

    Keywords

    Risk measure;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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