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Régularisation du prix des options : Stacking

Author

Listed:
  • Olivier Bardou
  • Yoshua Bengio

Abstract

The non-parametric modelization of the stock options and other derivatives generated an increased interest over the past years. The goal of this paper is to predict the market price of an option from the same information as needed by the Black-Scholes formula. This is a continuation of more recent papers based on the modelization of these prices by the use of neural networks with a structure inspired by our economic knowledge of option pricing. Our contribution, with this paper, is the successful use of the stacking algorithm to improve the generalization of these models. This algorithm combines two training levels for the models, the second being used to improve the out-of-sample deficits of the first one. The obtained results are very interesting, and span the call options of the S&P 500 between 1987 and 1993. La modélisation non-paramétrique du prix des options et autres produits dérivés a connu un intérêt croissant au cours des dernières années. Ce rapport se situe dans la perspective de prédire le prix de l'option au marché à partir des mêmes informations utilisées dans la formule de Black-Scholes. Il se situe dans la continuation de travaux récents sur la modélisation de ces prix par des réseaux de neurones avec une structure inspirée des connaissances économiques sur la valorisation d'options. La contribution de la recherche présentée ici est l'utilisation avec succès de l'algorithme de Stacking pour améliorer la généralisation de ces modèles. Cet algorithme combine deux niveaux d'entraînement des modèles, le deuxième cherchant à combler les déficits hors-échantillon du premier. Les résultats obtenus sont très intéressants et portent sur des options d'achat du S&P 500 entre 1987 et 1993.

Suggested Citation

  • Olivier Bardou & Yoshua Bengio, 2002. "Régularisation du prix des options : Stacking," CIRANO Working Papers 2002s-44, CIRANO.
  • Handle: RePEc:cir:cirwor:2002s-44
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    File URL: https://cirano.qc.ca/files/publications/2002s-44.pdf
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    References listed on IDEAS

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    1. Hutchinson, James M & Lo, Andrew W & Poggio, Tomaso, 1994. "A Nonparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks," Journal of Finance, American Finance Association, vol. 49(3), pages 851-889, July.
    2. Garcia, Rene & Gencay, Ramazan, 2000. "Pricing and hedging derivative securities with neural networks and a homogeneity hint," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 93-115.
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