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@article{McCrickerd:2018:10.1080/14697688.2018.1459812,
author = {McCrickerd, R and Pakkanen, MS},
doi = {10.1080/14697688.2018.1459812},
journal = {Quantitative Finance},
pages = {1877--1886},
title = {Turbocharging Monte Carlo pricing for the rough Bergomi model},
url = {http://dx.doi.org/10.1080/14697688.2018.1459812},
volume = {18},
year = {2018}
}

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TY  - JOUR
AB  - The rough Bergomi model, introduced by Bayer, Friz and Gatheral [Quant.Finance 16(6), 887-904, 2016], is one of the recent rough volatility modelsthat are consistent with the stylised fact of implied volatility surfaces beingessentially time-invariant, and are able to capture the term structure of skewobserved in equity markets. In the absence of analytical European optionpricing methods for the model, we focus on reducing the runtime-adjustedvariance of Monte Carlo implied volatilities, thereby contributing to themodel's calibration by simulation. We employ a novel composition of variancereduction methods, immediately applicable to any conditionally log-normalstochastic volatility model. Assuming one targets implied volatility estimateswith a given degree of confidence, thus calibration RMSE, the results wedemonstrate equate to significant runtime reductions - roughly 20 times onaverage, across different correlation regimes.
AU  - McCrickerd,R
AU  - Pakkanen,MS
DO  - 10.1080/14697688.2018.1459812
EP  - 1886
PY  - 2018///
SN  - 1469-7688
SP  - 1877
TI  - Turbocharging Monte Carlo pricing for the rough Bergomi model
T2  - Quantitative Finance
UR  - http://dx.doi.org/10.1080/14697688.2018.1459812
UR  - http://arxiv.org/abs/1708.02563v3
UR  - http://hdl.handle.net/10044/1/58622
VL  - 18
ER  -

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