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Efficient hedging for a complete jump-diffusion model


  • Kirch, Michael
  • Krutchenko, R. N.
  • Melnikov, Aleksandr V.


This paper is devoted to the problem of hedging contingent claims in the framework of a complete two-factor jump-diffusion model. In this context, it is well understood that every contingent claim can be hedged perfectly if one invests the unique arbitrage-free price. Based on the results of H. Föllmer and P. Leukert [4][ 5] in a general semimartingale setting, we determine the unique hedging strategies which minimize a suitably defined shortfall risk under a given cost constraint. We derive explicit formulas for this so-called efficient or quantile hedging strategy for a European call option. We then compare the performance of the optimal strategy for different degrees of the investor's risk-aversion.

Suggested Citation

  • Kirch, Michael & Krutchenko, R. N. & Melnikov, Aleksandr V., 2002. "Efficient hedging for a complete jump-diffusion model," SFB 373 Discussion Papers 2002,27, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  • Handle: RePEc:zbw:sfb373:200227

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    References listed on IDEAS

    1. Conor Dolan & Han Maas, 1998. "Fitting multivariage normal finite mixtures subject to structural equation modeling," Psychometrika, Springer;The Psychometric Society, vol. 63(3), pages 227-253, September.
    2. Asim Ansari & Kamel Jedidi & Sharan Jagpal, 2000. "A Hierarchical Bayesian Methodology for Treating Heterogeneity in Structural Equation Models," Marketing Science, INFORMS, vol. 19(4), pages 328-347, August.
    3. Yiu-Fai Yung, 1997. "Finite mixtures in confirmatory factor-analysis models," Psychometrika, Springer;The Psychometric Society, vol. 62(3), pages 297-330, September.
    4. Kamel Jedidi & Harsharanjeet S. Jagpal & Wayne S. DeSarbo, 1997. "Finite-Mixture Structural Equation Models for Response-Based Segmentation and Unobserved Heterogeneity," Marketing Science, INFORMS, pages 39-59.
    5. Venkatram Ramaswamy & Wayne S. Desarbo & David J. Reibstein & William T. Robinson, 1993. "An Empirical Pooling Approach for Estimating Marketing Mix Elasticities with PIMS Data," Marketing Science, INFORMS, vol. 12(1), pages 103-124.
    6. Gerhard Arminger & Petra Stein & Jörg Wittenberg, 1999. "Mixtures of conditional mean- and covariance-structure models," Psychometrika, Springer;The Psychometric Society, vol. 64(4), pages 475-494, December.
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    More about this item


    Efficient hedging; Quantile Hedging; jump-diffusion; martingale Measure;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty


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