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Hedging with small uncertainty aversion


  • Sebastian Herrmann

    () (University of Michigan)

  • Johannes Muhle-Karbe

    () (University of Michigan)

  • Frank Thomas Seifried

    () (Universität Trier)


Abstract We study the pricing and hedging of derivative securities with uncertainty about the volatility of the underlying asset. Rather than taking all models from a prespecified class equally seriously, we penalise less plausible ones based on their “distance” to a reference local volatility model. In the limit for small uncertainty aversion, this leads to explicit formulas for prices and hedging strategies in terms of the security’s cash gamma.

Suggested Citation

  • Sebastian Herrmann & Johannes Muhle-Karbe & Frank Thomas Seifried, 2017. "Hedging with small uncertainty aversion," Finance and Stochastics, Springer, vol. 21(1), pages 1-64, January.
  • Handle: RePEc:spr:finsto:v:21:y:2017:i:1:d:10.1007_s00780-016-0309-z DOI: 10.1007/s00780-016-0309-z

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    References listed on IDEAS

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    Cited by:

    1. Sebastian Herrmann & Johannes Muhle-Karbe, 2017. "Model Uncertainty, Recalibration, and the Emergence of Delta-Vega Hedging," Papers 1704.04524,
    2. repec:spr:finsto:v:21:y:2017:i:4:d:10.1007_s00780-017-0342-6 is not listed on IDEAS

    More about this item


    Volatility uncertainty; Ambiguity aversion; Option pricing and hedging; Asymptotics;

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games


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