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Calibrating Option Pricing Models with Heuristics

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  • Manfred Gilli
  • Enrico Schumann

Abstract

Calibrating option pricing models to market prices often leads to optimisation problems to which standard methods (like such based on gradients) cannot be applied. We investigate two models: Heston’s stochastic volatility model, and Bates’s model which also includes jumps. We discuss how to price options under these models, and how to calibrate the parameters of the models with heuristic techniques.

Suggested Citation

  • Manfred Gilli & Enrico Schumann, 2010. "Calibrating Option Pricing Models with Heuristics," Working Papers 030, COMISEF.
    • Handle: RePEc:com:wpaper:030
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    References listed on IDEAS

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    1. Bakshi, Gurdip & Cao, Charles & Chen, Zhiwu, 1997. "Empirical Performance of Alternative Option Pricing Models," Journal of Finance, American Finance Association, vol. 52(5), pages 2003-2049, December.
    2. Das, Sanjiv Ranjan & Sundaram, Rangarajan K., 1999. "Of Smiles and Smirks: A Term Structure Perspective," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(2), pages 211-239, June.
    3. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    4. Kilin, Fiodar, 2006. "Accelerating the calibration of stochastic volatility models," MPRA Paper 2975, University Library of Munich, Germany, revised 22 Apr 2007.
    5. Manfred Gilli & Enrico Schumann, 2009. "Optimal enough?," Working Papers 010, COMISEF.
    6. Bates, David S, 1996. "Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options," The Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 69-107.
    7. Kilin, Fiodar, 2007. "Accelerating the calibration of stochastic volatility models," CPQF Working Paper Series 6, Frankfurt School of Finance and Management, Centre for Practical Quantitative Finance (CPQF).
    8. Winker, Peter & Gilli, Manfred, 2004. "Applications of optimization heuristics to estimation and modelling problems," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 211-223, September.
    9. Bakshi, Gurdip & Madan, Dilip, 2000. "Spanning and derivative-security valuation," Journal of Financial Economics, Elsevier, vol. 55(2), pages 205-238, February.
    10. Gilli, Manfred & Schumann, Enrico, 2010. "Optimization in financial engineering - an essay on 'good' solutions and misplaced exactitude," Journal of Financial Transformation, Capco Institute, vol. 28, pages 117-122.
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    Citations

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    Cited by:

    1. Cui, Yiran & del Baño Rollin, Sebastian & Germano, Guido, 2017. "Full and fast calibration of the Heston stochastic volatility model," European Journal of Operational Research, Elsevier, vol. 263(2), pages 625-638.
    2. Shuaiqiang Liu & Anastasia Borovykh & Lech A. Grzelak & Cornelis W. Oosterlee, 2019. "A neural network-based framework for financial model calibration," Papers 1904.10523, arXiv.org.
    3. Yeap, Claudia & Kwok, Simon S. & Choy, S. T. Boris, 2016. "A Flexible Generalised Hyperbolic Option Pricing Model and its Special Cases," Working Papers 2016-14, University of Sydney, School of Economics.
    4. Eudald Romo & Luis Ortiz-Gracia, 2021. "SWIFT calibration of the Heston model," Papers 2103.01570, arXiv.org.
    5. Silvia Centanni, 2011. "Computing option values by pricing kernel with a stochatic volatility model," Working Papers 05/2011, University of Verona, Department of Economics.
    6. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.
    7. Zaineb Mezdoud & Carsten Hartmann & Mohamed Riad Remita & Omar Kebiri, 2021. "$\alpha$-Hypergeometric Uncertain Volatility Models and their Connection to 2BSDEs," Papers 2108.06965, arXiv.org.
    8. Stefan Haring & Ronald Hochreiter, 2015. "Efficient and robust calibration of the Heston option pricing model for American options using an improved Cuckoo Search Algorithm," Papers 1507.08937, arXiv.org.
    9. Eudald Romo & Luis Ortiz-Gracia, 2021. "SWIFT Calibration of the Heston Model," Mathematics, MDPI, vol. 9(5), pages 1-20, March.
    10. Hilmar Gudmundsson & David Vyncke, 2021. "A Generalized Weighted Monte Carlo Calibration Method for Derivative Pricing," Mathematics, MDPI, vol. 9(7), pages 1-22, March.

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