English, Article, Journal or magazine article edition: Option Pricing with Modular Neural Networks Nikola Gradojevic; Ramazan Gencay; Dragan Kukolj

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Bookmark: http://trove.nla.gov.au/version/25495
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Option Pricing with Modular Neural Networks
Author
  • Nikola Gradojevic
  • Ramazan Gencay
  • Dragan Kukolj
Physical Description
  • preprint
Notes
  • This paper investigates a non-parametric modular neural network (MNN) model to price the S&​P-500 European call options. The modules are based on time to maturity and moneyness of the options. The option price function of interest is homogenous of degree one with respect to the underlying index price and the strike price. When compared to an array of parametric and non-parametric models, the MNN method consistently exerts superior out-of-sample pricing performance. We conclude that modularity improves the generalization properties of standard feedforward neural network option pricing models (with and without the homogeneity hint)
  • Option Pricing; Modular Neural Networks; Non-parametric Methods
  • RePEc:rim:rimwps:wp32_09
Language
  • English
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