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Quantile Hedging in a semi-static market with model uncertainty

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  • Erhan Bayraktar

    (University of Michigan)

  • Gu Wang

    (Worcester Polytechnic Institute)

Abstract

With model uncertainty characterized by a convex, possibly non-dominated set of probability measures, the agent minimizes the cost of hedging a path dependent contingent claim with given expected success ratio, in a discrete-time, semi-static market of stocks and options. Based on duality results which link quantile hedging to a randomized composite hypothesis test, an arbitrage-free discretization of the market is proposed as an approximation. The discretized market has a dominating measure, which guarantees the existence of the optimal hedging strategy and helps numerical calculation of the quantile hedging price. As the discretization becomes finer, the approximate quantile hedging price converges and the hedging strategy is asymptotically optimal in the original market.

Suggested Citation

  • Erhan Bayraktar & Gu Wang, 2018. "Quantile Hedging in a semi-static market with model uncertainty," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 87(2), pages 197-227, April.
  • Handle: RePEc:spr:mathme:v:87:y:2018:i:2:d:10.1007_s00186-017-0616-y
    DOI: 10.1007/s00186-017-0616-y
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    Cited by:

    1. Jan Obloj & Johannes Wiesel, 2018. "A unified Framework for Robust Modelling of Financial Markets in discrete time," Papers 1808.06430, arXiv.org, revised Dec 2019.

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