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International Journal of Theoretical and Applied FinanceVolume 21, Issue 8, 1 December 2018, Article number 1850052

Decomposition formula for jump diffusion models(Article)(Open Access)

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  • aFacultat de Matemàtiques, Universitat de Barcelona, Gran Via 585, Barcelona, 08007, Spain
  • bFaculty of Applied Sciences, University of West Bohemia, NTIS-New Technologies for the Information Society, Univerzitní 8, Plzeň, 30614, Czech Republic
  • cVidaCaixa S.A., Investment Risk Management Department, C/Juan Gris 2-8, Barcelona, 08014, Spain

Abstract

In this paper, we derive a generic decomposition of the option pricing formula for models with finite activity jumps in the underlying asset price process (SVJ models). This is an extension of the well-known result by Alòs [(2012) A decomposition formula for option prices in the Heston model and applications to option pricing approximation, Finance and Stochastics 16 (3), 403-422, doi:https://doi.org/10.1007/s00780-012-0177-0] for Heston [(1993) A closed-form solution for options with stochastic volatility with applications to bond and currency options, The Review of Financial Studies 6 (2), 327-343, doi:https://doi.org/10.1093/rfs/6.2.327] SV model. Moreover, explicit approximation formulas for option prices are introduced for a popular class of SVJ models-models utilizing a variance process postulated by Heston [(1993) A closed-form solution for options with stochastic volatility with applications to bond and currency options, The Review of Financial Studies 6 (2), 327-343, doi:https://doi.org/10.1093/rfs/6.2.327]. In particular, we inspect in detail the approximation formula for the Bates [(1996), Jumps and stochastic volatility: Exchange rate processes implicit in Deutsche mark options, The Review of Financial Studies 9 (1), 69-107, doi:https://doi.org/10.1093/rfs/9.1.69] model with log-normal jump sizes and we provide a numerical comparison with the industry standard-Fourier transform pricing methodology. For this model, we also reformulate the approximation formula in terms of implied volatilities. The main advantages of the introduced pricing approximations are twofold. Firstly, we are able to significantly improve computation efficiency (while preserving reasonable approximation errors) and secondly, the formula can provide an intuition on the volatility smile behavior under a specific SVJ model. © 2018 World Scientific Publishing Company.

Author keywords

implied volatilityjump diffusion modelsOption pricingstochastic volatility models

Funding details

Funding sponsor Funding number Acronym
Grantová Agentura České RepublikyMEC MTM 2016-76420-PGA ČR
  • 1

    This work was partially supported by the GACR Grant GA18-16680S Rough models of fractional stochastic volatility. Computational resources were provided by the CESNET LM2015042 and the CERIT Scientific Cloud LM2015085, provided under the programme “Projects of Large Research, Development, and Innovations Infrastructures”. The work of Josep Vives is partially supported by Spanish grant MEC MTM 2016-76420-P.

  • ISSN: 02190249
  • Source Type: Journal
  • Original language: English
  • DOI: 10.1142/S0219024918500528
  • Document Type: Article
  • Publisher: World Scientific Publishing Co. Pte Ltd

  Vives, J.; Facultat de Matemàtiques, Universitat de Barcelona, Gran Via 585, Barcelona, Spain;
© Copyright 2019 Elsevier B.V., All rights reserved.

Cited by 1 document

Merino, R. , Pospíšil, J.A.N. , Sobotka, T.
Decomposition formula for rough volterra stochastic volatility models
(2021) International Journal of Theoretical and Applied Finance
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