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Estimating the Parameters of Stochastic Volatility Models Using Option Price Data

Author

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  • A. S. Hurn
  • K. A. Lindsay
  • A. J. McClelland

Abstract

This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.

Suggested Citation

  • A. S. Hurn & K. A. Lindsay & A. J. McClelland, 2015. "Estimating the Parameters of Stochastic Volatility Models Using Option Price Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 579-594, October.
    • Handle: RePEc:taf:jnlbes:v:33:y:2015:i:4:p:579-594
    DOI: 10.1080/07350015.2014.981634
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    2. Dammak, Wael & Hamad, Salah Ben & de Peretti, Christian & Eleuch, Hichem, 2023. "Pricing of European currency options considering the dynamic information costs," Global Finance Journal, Elsevier, vol. 58(C).
    3. Aretz, Kevin & Eser Arisoy, Y., 2023. "The Pricing of Skewness Over Different Return Horizons," Journal of Banking & Finance, Elsevier, vol. 148(C).
    4. Brignone, Riccardo & Gonzato, Luca & Lütkebohmert, Eva, 2023. "Efficient Quasi-Bayesian Estimation of Affine Option Pricing Models Using Risk-Neutral Cumulants," Journal of Banking & Finance, Elsevier, vol. 148(C).
    5. Steven Heston & Kris Jacobs & Hyung Joo Kim, 2023. "The Pricing Kernel in Options," Finance and Economics Discussion Series 2023-053, Board of Governors of the Federal Reserve System (U.S.).
    6. Yan-Feng Wu & Xiangyu Yang & Jian-Qiang Hu, 2024. "Method of Moments Estimation for Affine Stochastic Volatility Models," Papers 2408.09185, arXiv.org.
    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. Lorenzo Mercuri & Edit Rroji, 2018. "Option pricing in an exponential MixedTS Lévy process," Annals of Operations Research, Springer, vol. 260(1), pages 353-374, January.

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