Splitting and matrix exponential approach for jump-diffusion models with Inverse Normal Gaussian, Hyperbolic and Meixner jumps

Andrey Itkin ()

Algorithmic Finance, 2014, vol. 3, issue 3-4, 233-250

Abstract: This paper is a further extension of the method proposed in Itkin (2014) as applied to another set of jump-diffusion models: Inverse Normal Gaussian, Hyperbolic and Meixner. To solve the corresponding PIDEs we accomplish few steps. First, a second-order operator splitting on financial processes (diffusion and jumps) is applied to these PIDEs. To solve the diffusion equation we use standard finite-difference methods. For the jump part, we transform the jump integral into a pseudo-differential operator and construct its second order approximation on a grid which supersets the grid used for the diffusion part. The proposed schemes are unconditionally stable in time and preserve positivity of the solution which is computed either via a matrix exponential, or via its Páde approximation. Various numerical experiments are provided to justify these results.

Keywords: Jump-diffusion; PIDE; splitting; matrix exponential; unconditionally stable schemes (search for similar items in EconPapers)
JEL-codes: C00 (search for similar items in EconPapers)
Date: 2014
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Working Paper: Splitting and Matrix Exponential approach for jump-diffusion models with Inverse Normal Gaussian, Hyperbolic and Meixner jumps (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:ris:iosalg:0033

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