Journal of Computational Finance

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Neural networks for option pricing and hedging: a literature review

Johannes Ruf and Weiguan Wang

  • Comprehensive literature review on the use of artificial neural networks for option pricing and hedging.
  • Comparison in terms of input features, output variables, benchmark models, performance measures, data partition methods and underlying assets.
  • Discussion of related work (calibration, solving PDEs, etc) and regularization techniques.

Neural networks have been used as a nonparametric method for option pricing and hedging since the early 1990s, with far more than a hundred papers having been published on the topic. This paper provides a comprehensive review of the field, comparing articles in terms of input features, output variables, benchmark models, performance measures, data partition methods and underlying assets. Further, related work and regularization techniques are discussed.

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