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Markovian Approximation for rBergomi Model by Bryan Dilamore is a document available to read on EtoBox.

This document presents a Markovian approximation of the rough Bergomi model for Monte Carlo option pricing. The rough Bergomi model generates realistic volatility skews but is non-Markovian, posing challenges for calibration and simulation. The authors establish an affine structure for the rough Bergomi model by approximating its Volterra kernel with a combination of Ornstein-Uhlenbeck processes. This yields an approximated Bergomi model that is Markovian and can be efficiently simulated using a hybrid sche

Author
Bryan Dilamore
Language
EN