Pathwise large deviations for the Rough Bergomi model

Abstract

We study the small-time behaviour of the rough Bergomi model, introduced by Bayer, Friz and Gatheral (2016), and prove a large deviations principle for a rescaled version of the normalised log stock price process, which then allows us to characterise the small-time behaviour of the implied volatility.

arXiv comment12 Pages

References in corpus (6)

• Hybrid scheme for Brownian semistationary processes
• Asymptotics for rough stochastic volatility models
• Large Deviations and Importance Sampling for Systems of Slow-Fast Motion
• Brownian moving averages have conditional full support
• Fact or friction: Jumps at ultra high frequency
• Importance sampling for slow-fast diffusions based on moderate deviations

Cited by in corpus (6)

• Precise asymptotics: robust stochastic volatility models
• Large and moderate deviations for stochastic Volterra systems
• Hierarchical adaptive sparse grids and quasi Monte Carlo for option pricing under the rough Bergomi model
• On smile properties of volatility derivatives and exotic products: understanding the VIX skew
• Asymptotic behaviour of randomised fractional volatility models
• On spatially irregular ordinary differential equations and a pathwise volatility modelling framework