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Computing Deltas without Derivatives

Baños, David Ruiz; Meyer-Brandis, Thilo; Proske, Frank Norbert; Duedahl, Sindre
Journal article; AcceptedVersion; Peer reviewed
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DeltasAcceptedRevised.pdf (661.6Kb)
Year
2017
Permanent link
http://urn.nb.no/URN:NBN:no-57932

CRIStin
1399704

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  • Matematisk institutt [2422]
  • CRIStin høstingsarkiv [15189]
Original version
Finance and Stochastics. 2017, 21 (2), 509-549, DOI: http://dx.doi.org/10.1007/s00780-016-0321-3
Abstract
A well-known application of Malliavin calculus in mathematical finance is the probabilistic representation of option price sensitivities, the so-called Greeks, as expectation functionals that do not involve the derivative of the payoff function. This allows numerically tractable computation of the Greeks even for discontinuous payoff functions. However, while the payoff function is allowed to be irregular, the coefficients of the underlying diffusion are required to be smooth in the existing literature, which for example already excludes simple regime-switching diffusion models. The aim of this article is to generalise this application of Malliavin calculus to Itô diffusions with irregular drift coefficients, where we focus here on the computation of the delta, which is the option price sensitivity with respect to the initial value of the underlying. To this end, we first show existence, Malliavin differentiability and (Sobolev) differentiability in the initial condition for strong solutions of Itô diffusions with drift coefficients that can be decomposed into the sum of a bounded, but merely measurable, and a Lipschitz part. Furthermore, we give explicit expressions for the corresponding Malliavin and Sobolev derivatives in terms of the local time of the diffusion, respectively. We then turn to the main objective of this article and analyse the existence and probabilistic representation of the corresponding deltas for European and path-dependent options. We conclude with a small simulation study of several regime-switching examples.

The final version of this research has been published by Finance and Stochastics. © Springer Verlag.
 
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