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The Importance of the Loss Function in Option Valuation

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  • Peter Christoffersen
  • Kris Jacobs

Abstract

Which loss function should be used when estimating and evaluating option valuation models? Many different functions have been suggested, but no standard has emerged. We emphasize that consistency in the choice of loss functions is crucial. First, for any given model, the loss function used in parameter estimation and model evaluation should be the same, otherwise suboptimal parameter estimates may be obtained. Second, when comparing models, the estimation loss function should be identical across models, otherwise inappropriate comparisons will be made. We illustrate the importance of these issues in an application of the so-called Practitioner Black-Scholes model to S&P 500 index options. Quelle devrait être la fonction de perte utilisée pour l'estimation et l'évaluation des modèles de valorisation des options? Plusieurs fonctions ont été suggérées, mais aucune norme ne s'est imposée. Dans ce travail, nous ne proposons pas une fonction en particulier, mais nous soutenons que la cohérence dans le choix des fonctions est cruciale. Premièrement, pour n'importe quel modèle donné, la fonction de perte utilisée dans l'estimation des paramètres et dans l'évaluation du modèle devrait être la même, sinon on obtient des estimations de paramètres sous-optimaux. Deuxièmement, lors de la comparaison des modèles, la fonction de perte utilisée pour l'estimation devrait être la même pour chaque modèle, autrement les comparaisons sont injustes. Nous illustrons l'importance de ces questions dans une application du modèle appelé Black-Scholes du praticien (PBS) aux options de l'indice S&P500.

Suggested Citation

  • Peter Christoffersen & Kris Jacobs, 2003. "The Importance of the Loss Function in Option Valuation," CIRANO Working Papers 2003s-52, CIRANO.
  • Handle: RePEc:cir:cirwor:2003s-52
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    More about this item

    Keywords

    implied volatility functions; valuation errors; out-of-sample forecasting; parameter stability; fonctions de volatilité implicite; évaluation des erreurs; prévision hors échantillon; stabilité des paramètres;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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