Pathwise large deviations for the rough Bergomi model

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Title: Pathwise large deviations for the rough Bergomi model
Authors: Jacquier, A
Pakkanen, MS
Stone, H
Item Type: Journal Article
Abstract: 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.
Issue Date: Dec-2018
Date of Acceptance: 8-Aug-2018
URI: http://hdl.handle.net/10044/1/63331
DOI: https://doi.org/10.1017/jpr.2018.72
ISSN: 0021-9002
Publisher: Applied Probability Trust
Start Page: 1078
End Page: 1092
Journal / Book Title: Journal of Applied Probability
Volume: 55
Issue: 4
Copyright Statement: © 2018 Applied Probability Trust. First published in Jacquier, A., Pakkanen, M., & Stone, H. (2018). Pathwise large deviations for the rough Bergomi model. Journal of Applied Probability, 55(4), 1078-1092. doi:10.1017/jpr.2018.72 .
Keywords: Science & Technology
Physical Sciences
Statistics & Probability
Mathematics
Rough volatility
large deviations
small-time asymptotics
Gaussian measure
reproducing kernel Hilbert space
IMPLIED VOLATILITY
STOCHASTIC VOLATILITY
ASYMPTOTICS
DIFFUSION
PRINCIPLE
JUMPS
math.PR
math.PR
q-fin.PR
60F10, 60G22
math.PR
math.PR
q-fin.PR
60F10, 60G22
0102 Applied Mathematics
0104 Statistics
Statistics & Probability
Publication Status: Published
Online Publication Date: 2019-01-16
Appears in Collections:Financial Mathematics
Mathematics
Faculty of Natural Sciences



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