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Pricing and hedging of financial derivatives using a posteriori error estimates and adaptive methods for stochastic differential equations

Önskog, Thomas, 1979- (author)
Umeå universitet,Institutionen för matematik och matematisk statistik
Nyström, Kaj, 1969- (author)
Uppsala universitet,Umeå universitet,Institutionen för matematik och matematisk statistik,Analys och tillämpad matematik
 (creator_code:org_t)
Elsevier, 2010
2010
English.
In: Journal of Computational and Applied Mathematics. - : Elsevier. - 0377-0427 .- 1879-1778. ; 235, s. 563-592
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • The efficient and accurate calculation of sensitivities of the price of financial derivatives with respect to perturbations of the parameters in the underlying model, the so-called `Greeks', remains a great practical challenge in the derivative industry. This is true regardless of whether methods for partial differential equations or stochastic differential equations (Monte Carlo techniques) are being used. The computation of the `Greeks' is essential to risk management and to the hedging of financial derivatives and typically requires substantially more computing time as compared to simply pricing the derivatives. Any numerical algorithm (Monte Carlo algorithm) for stochastic differential equations produces a time-discretization error and a statistical error in the process of pricing financial derivatives and calculating the associated `Greeks'. In this article we show how a posteriori error estimates and adaptive methods for stochastic differential equations can be used to control both these errors in the context of pricing and hedging of financial derivatives. In particular, we derive expansions, with leading order terms which are computable in a posteriori form, of the time-discretization errors for the price and the associated `Greeks'. These expansions allow the user to simultaneously first control the time-discretization errors in an adaptive fashion, when calculating the price, sensitivities and hedging parameters with respect to a large number of parameters, and then subsequently to ensure that the total errors are, with prescribed probability, within tolerance.

Subject headings

NATURVETENSKAP  -- Matematik (hsv//swe)
NATURAL SCIENCES  -- Mathematics (hsv//eng)
NATURVETENSKAP  -- Matematik -- Matematisk analys (hsv//swe)
NATURAL SCIENCES  -- Mathematics -- Mathematical Analysis (hsv//eng)

Keyword

Sensitivity analysis
Parabolic partial differential equations
Stochastic differential equations
Euler scheme
A posteriori error estimate
Adaptive algorithms
hedging
Financial derivatives
MATHEMATICS
MATEMATIK
Mathematics
matematik

Publication and Content Type

ref (subject category)
art (subject category)

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