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A Forward Equation for Barrier Options under the Brunick&Shreve Markovian Projection

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  • Ben Hambly
  • Matthieu Mariapragassam
  • Christoph Reisinger

Abstract

We derive a forward equation for arbitrage-free barrier option prices, in terms of Markovian projections of the stochastic volatility process, in continuous semi-martingale models. This provides a Dupire-type formula for the coefficient derived by Brunick and Shreve for their mimicking diffusion and can be interpreted as the canonical extension of local volatility for barrier options. Alternatively, a forward partial-integro differential equation (PIDE) is introduced which provides up-and-out call prices, under a Brunick-Shreve model, for the complete set of strikes, barriers and maturities in one solution step. Similar to the vanilla forward PDE, the above-named forward PIDE can serve as a building block for an efficient calibration routine including barrier option quotes. We provide a discretisation scheme for the PIDE as well as a numerical validation.

Suggested Citation

  • Ben Hambly & Matthieu Mariapragassam & Christoph Reisinger, 2014. "A Forward Equation for Barrier Options under the Brunick&Shreve Markovian Projection," Papers 1411.3618, arXiv.org, revised Sep 2016.
    • Handle: RePEc:arx:papers:1411.3618
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    References listed on IDEAS

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    1. Peter Carr & John Crosby, 2010. "A class of Levy process models with almost exact calibration to both barrier and vanilla FX options," Quantitative Finance, Taylor & Francis Journals, vol. 10(10), pages 1115-1136.
    2. René Carmona & Sergey Nadtochiy, 2009. "Local volatility dynamic models," Finance and Stochastics, Springer, vol. 13(1), pages 1-48, January.
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    Cited by:

    1. Andrei Cozma & Christoph Reisinger, 2017. "Strong convergence rates for Euler approximations to a class of stochastic path-dependent volatility models," Papers 1706.07375, arXiv.org, revised Oct 2018.
    2. Köpfer, Benedikt & Rüschendorf, Ludger, 2023. "Markov projection of semimartingales — Application to comparison results," Stochastic Processes and their Applications, Elsevier, vol. 162(C), pages 361-386.
    3. Alan Bain & Matthieu Mariapragassam & Christoph Reisinger, 2019. "Calibration of Local-Stochastic and Path-Dependent Volatility Models to Vanilla and No-Touch Options," Papers 1911.00877, arXiv.org.
    4. Martin Tegner & Stephen Roberts, 2021. "A Bayesian take on option pricing with Gaussian processes," Papers 2112.03718, arXiv.org.
    5. Martin Tegn'er & Stephen Roberts, 2019. "A Probabilistic Approach to Nonparametric Local Volatility," Papers 1901.06021, arXiv.org, revised Jan 2019.
    6. Qiao, Huijie & Wu, Jiang-Lun, 2016. "Characterizing the path-independence of the Girsanov transformation for non-Lipschitz SDEs with jumps," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 326-333.

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