Department of Economics and Business Economics

American Option Pricing using GARCH models and the Normal Inverse Gaussian distribution

Research output: Working paperResearch

  • Lars Peter Stentoft, Denmark
  • School of Economics and Management
In this paper we propose a feasible way to price American options in a model with time varying
volatility and conditional skewness and leptokurtosis using GARCH processes and the Normal Inverse
Gaussian distribution. We show how the risk neutral dynamics can be obtained in this model, we
interpret the effect of the riskneutralization, and we derive approximation procedures which allow for a
computationally efficient implementation of the model. When the model is estimated on financial returns
data the results indicate that compared to the Gaussian case the extension is important. A study of the
model properties shows that there are important option pricing differences compared to the Gaussian
case as well as to the symmetric special case. A large scale empirical examination shows that our model
outperforms the Gaussian case for pricing options on three large US stocks as well as a major index. In
particular, improvements are found when considering the smile in implied standard deviations.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages47
Publication statusPublished - 2008

    Research areas

  • GARCH models, Normal Inverse Gaussian distribution, American Options, Least Squares Monte Carlo method

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ID: 12330622