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Nonparametric estimation of American options' exercise boundaries and call prices

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  • Broadie, Mark
  • Detemple, Jerome
  • Ghysels, Eric
  • Torres, Olivier

Abstract

Unlike European-type derivative securities, there are no simple analytic valuation formulas for American options, even when the underlying asset price has constant volatility. The early exercise feature considerably complicates the valuation of American contracts. The strategy taken in this paper is to rely on nonparametric statistical methods using market data to estimate the call prices and the exercise boundaries. The paper focuses on the daily market option prices and exercise data on the S&P100 contract. A comparison is made with parametric constant volatility model-based prices and exercise boundaries. We find large discrepancies between the parametric and nonparametric call prices and exercise boundaries. Contrairement à ce qu'il est possible d'obtenir dans un contexte d'évaluation de titres dérivés de type européen, il n'existe pas de formule analytique simple pour évaluer les options américaines, même si la volatilité de l'actif sous-jacent est supposée constante. La possibilité d'exercice prématuré qu'offre ce type de contrat complique considérablement son évaluation. La démarche adoptée dans cette étude consiste à dériver les prix d'option et les frontières d'exercice à partir de données financières, utilisées dans un cadre d'analyse statistique non-paramétrique. Plus particulièrement, l'étude utilise les observations quotidiennes du prix du contrat sur l'indice S&P100 ainsi que les observations sur l'exercice de ce contrat. Les résultats sont comparés à ceux obtenus à l'aide de techniques paramétriques dans un modèle où la volatilité est supposée constante. La conclusion est qu'il existe des différences stratégiques entre les prédictions des deux modèles, aussi bien en ce qui concerne le prix de l'option que la politique d'exercice qui lui est associée.
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  • Broadie, Mark & Detemple, Jerome & Ghysels, Eric & Torres, Olivier, 2000. "Nonparametric estimation of American options' exercise boundaries and call prices," Journal of Economic Dynamics and Control, Elsevier, vol. 24(11-12), pages 1829-1857, October.
  • Handle: RePEc:eee:dyncon:v:24:y:2000:i:11-12:p:1829-1857
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    Cited by:

    1. Shively, Thomas S. & Walker, Stephen G. & Damien, Paul, 2011. "Nonparametric function estimation subject to monotonicity, convexity and other shape constraints," Journal of Econometrics, Elsevier, vol. 161(2), pages 166-181, April.
    2. Yu, Xisheng & Xie, Xiaoke, 2015. "Pricing American options: RNMs-constrained entropic least-squares approach," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 155-173.
    3. Jun Lu & Hiroshi Ohta, 2003. "A data and digital-contracts driven method for pricing complex derivatives," Quantitative Finance, Taylor & Francis Journals, vol. 3(3), pages 212-219.
    4. Gagliardini, Patrick & Ronchetti, Diego, 2013. "Semi-parametric estimation of American option prices," Journal of Econometrics, Elsevier, vol. 173(1), pages 57-82.
    5. 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.
    6. Broadie, Mark & Detemple, Jerome & Ghysels, Eric & Torres, Olivier, 2000. "American options with stochastic dividends and volatility: A nonparametric investigation," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 53-92.
    7. Li, Gang & Zhang, Chu, 2016. "On the relationship between conditional jump intensity and diffusive volatility," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 196-213.
    8. GHYSELS, Eric & PATILEA, Valentin & RENAULT, Eric & TORRES, Olivier, 1997. "Nonparametric methods and option pricing," CORE Discussion Papers 1997075, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Ait-Sahalia, Yacine & Lo, Andrew W., 2000. "Nonparametric risk management and implied risk aversion," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 9-51.
    10. Tze Leung Lai & Samuel Po-Shing Wong, 2007. "Combining domain knowledge and statistical models in time series analysis," Papers math/0702814, arXiv.org.
    11. René Garcia & Eric Ghysels & Éric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO.
    12. Li, Gang & Zhang, Chu, 2013. "Diagnosing affine models of options pricing: Evidence from VIX," Journal of Financial Economics, Elsevier, vol. 107(1), pages 199-219.
    13. Teresa Corzo Santamaría & Javier Gómez Biscarri, 2005. "Nonparametric estimation of convergence of interest rates: Effects on bond pricing," Spanish Economic Review, Springer;Spanish Economic Association, vol. 7(3), pages 167-190, September.
    14. repec:pal:jorsoc:v:54:y:2003:i:9:d:10.1057_palgrave.jors.2601597 is not listed on IDEAS
    15. Matthias Fengler & Wolfgang Härdle & Enno Mammen, 2005. "A Dynamic Semiparametric Factor Model for Implied Volatility String Dynamics," SFB 649 Discussion Papers SFB649DP2005-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D52 - Microeconomics - - General Equilibrium and Disequilibrium - - - Incomplete Markets
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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