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Esscher transforms and consumption-based models

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  • Badescu, Alex
  • Elliott, Robert J.
  • Siu, Tak Kuen

Abstract

The Esscher transform is an important tool in actuarial science. Since the pioneering work of Gerber and Shiu (1994), the use of the Esscher transform for option valuation has also been investigated extensively. However, the relationships between the asset pricing model based on the Esscher transform and some fundamental equilibrium-based asset pricing models, such as consumption-based models, have so far not been well-explored. In this paper, we attempt to bridge the gap between consumption-based models and asset pricing models based on Esscher-type transformations in a discrete-time setting. Based on certain assumptions for the distributions of asset returns, changes in aggregate consumptions and returns on the market portfolio, we construct pricing measures that are consistent with those arising from Esscher-type transformations. Explicit relationships between the market price of risk, and the risk preference parameters are derived for some particular cases.

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Bibliographic Info

Article provided by Elsevier in its journal Insurance: Mathematics and Economics.

Volume (Year): 45 (2009)
Issue (Month): 3 (December)
Pages: 337-347

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Handle: RePEc:eee:insuma:v:45:y:2009:i:3:p:337-347

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Web page: http://www.elsevier.com/locate/inca/505554

Related research

Keywords: Esscher transform Esscher-Girsanov transform Consumption-based model Stochastic discount factor Exponential affine form Euler equation Radon-Nikodym derivative Utility function;

References

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  1. Badescu, Alexandru M. & Kulperger, Reg J., 2008. "GARCH option pricing: A semiparametric approach," Insurance: Mathematics and Economics, Elsevier, vol. 43(1), pages 69-84, August.
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  21. Robert J. Elliott & Tak Kuen Siu & Leunglung Chan, 2006. "Option Pricing For Garch Models With Markov Switching," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 9(06), pages 825-841.
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Citations

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Cited by:
  1. M. Martin Boyer & Lars Peter Stentoft, 2012. "If we can simulate it, we can insure it: An application to longevity risk management," CIRANO Working Papers 2012s-08, CIRANO.
  2. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall futures at the CME," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4286-4298.
  3. Labuschagne, Coenraad C.A. & Offwood, Theresa M., 2010. "A note on the connection between the Esscher-Girsanov transform and the Wang transform," Insurance: Mathematics and Economics, Elsevier, vol. 47(3), pages 385-390, December.
  4. Alexandru Badescu & Robert J. Elliott & Juan-Pablo Ortega, 2012. "Quadratic hedging schemes for non-Gaussian GARCH models," Papers 1209.5976, arXiv.org, revised Dec 2013.
  5. Chen, Hua & Cox, Samuel H. & Wang, Shaun S., 2010. "Is the Home Equity Conversion Mortgage in the United States sustainable? Evidence from pricing mortgage insurance premiums and non-recourse provisions using the conditional Esscher transform," Insurance: Mathematics and Economics, Elsevier, vol. 46(2), pages 371-384, April.
  6. Brenda López Cabrera & Martin Odening & Matthias Ritter, 2013. "Pricing Rainfall Derivatives at the CME," SFB 649 Discussion Papers SFB649DP2013-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  7. Liew, Chuin Ching & Siu, Tak Kuen, 2010. "A hidden Markov regime-switching model for option valuation," Insurance: Mathematics and Economics, Elsevier, vol. 47(3), pages 374-384, December.
  8. Marri, Fouad & Furman, Edward, 2012. "Pricing compound Poisson processes with the Farlie–Gumbel–Morgenstern dependence structure," Insurance: Mathematics and Economics, Elsevier, vol. 51(1), pages 151-157.

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