Pathwise large deviations for the rough Bergomi model

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  • Antoine Jacquier, Imperial Coll London, Imperial College London, Dept Math
  • ,
  • Mikko S. Pakkanen
  • Henry Stone, Imperial Coll London, Imperial College London, Dept Math

Introduced recently in mathematical finance by Bayer et al. (2016), the rough Bergomi model has proved particularly efficient to calibrate option markets. We investigate some of its probabilistic properties, in particular proving a pathwise large deviations principle for a small-noise version of the model. The exponential function (continuous but superlinear) as well as the drift appearing in the volatility process fall beyond the scope of existing results, and a dedicated analysis is needed.

Original languageEnglish
JournalJournal of Applied Probability
Pages (from-to)1078-1092
Number of pages15
Publication statusPublished - 2018

    Research areas

  • Rough volatility, large deviations, small-time asymptotics, Gaussian measure, reproducing kernel Hilbert space, IMPLIED VOLATILITY, STOCHASTIC VOLATILITY, ASYMPTOTICS, DIFFUSION, PRINCIPLE, JUMPS

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