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High order discretization schemes for stochastic volatility models

Author

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  • Benjamin Jourdain

    (CERMICS - Centre d'Enseignement et de Recherche en Mathématiques, Informatique et Calcul Scientifique - Inria - Institut National de Recherche en Informatique et en Automatique - ENPC - École des Ponts ParisTech, MATHRISK - Mathematical Risk handling - Inria Paris-Rocquencourt - Inria - Institut National de Recherche en Informatique et en Automatique - UPEM - Université Paris-Est Marne-la-Vallée - ENPC - École des Ponts ParisTech)

  • Mohamed Sbai

    (CERMICS - Centre d'Enseignement et de Recherche en Mathématiques, Informatique et Calcul Scientifique - Inria - Institut National de Recherche en Informatique et en Automatique - ENPC - École des Ponts ParisTech)

Abstract

In usual stochastic volatility models, the process driving the volatility of the asset price evolves according to an autonomous one-dimensional stochastic differential equation. We assume that the coefficients of this equation are smooth. Using Itô's formula, we get rid, in the asset price dynamics, of the stochastic integral with respect to the Brownian motion driving this SDE. Taking advantage of this structure, we propose - a scheme, based on the Milstein discretization of this SDE, with order one of weak trajectorial convergence for the asset price, - a scheme, based on the Ninomiya-Victoir discretization of this SDE, with order two of weak convergence for the asset price. We also propose a specific scheme with improved convergence properties when the volatility of the asset price is driven by an Orstein-Uhlenbeck process. We confirm the theoretical rates of convergence by numerical experiments and show that our schemes are well adapted to the multilevel Monte Carlo method introduced by Giles [2008a, 2008b].

Suggested Citation

  • Benjamin Jourdain & Mohamed Sbai, 2013. "High order discretization schemes for stochastic volatility models," Post-Print hal-00409861, HAL.
  • Handle: RePEc:hal:journl:hal-00409861
    DOI: 10.21314/JCF.2013.262
    Note: View the original document on HAL open archive server: https://hal.science/hal-00409861v4
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    References listed on IDEAS

    as
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    Cited by:

    1. Dan Pirjol & Lingjiong Zhu, 2017. "Asymptotics for the Euler-Discretized Hull-White Stochastic Volatility Model," Papers 1707.00899, arXiv.org.
    2. Dan Pirjol & Lingjiong Zhu, 2018. "Asymptotics for the Euler-Discretized Hull-White Stochastic Volatility Model," Methodology and Computing in Applied Probability, Springer, vol. 20(1), pages 289-331, March.

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