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Implied volatility in oil markets

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  • Borovkova, Svetlana
  • Permana, Ferry J.

Abstract

Modelling the implied volatility surface as a function of an option's strike price and maturity is a subject of extensive research in financial markets. The implied volatility in commodity markets is much less studied, due to a limited liquidity and the complicated structure of commodity options. A new semi-parametric method is introduced for modelling the implied volatility surface and is applied to the option price data from oil markets. This approach combines the simplicity of a parametric method with the flexibility of a non-parametric approach. The method can successfully deal with a limited amount of option price data. Performance of the method is investigated by applying it to prices of exchange-traded crude oil and gasoline options, and the results are compared with those obtained by a purely parametric approach. Furthermore, the investigation of the relationship between volatilities implied from European and Asian options shows that Asian options in oil markets are significantly more expensive than theoretical arguments imply.

Suggested Citation

  • Borovkova, Svetlana & Permana, Ferry J., 2009. "Implied volatility in oil markets," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2022-2039, April.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:6:p:2022-2039
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    References listed on IDEAS

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    1. Rama Cont & Jose da Fonseca, 2002. "Dynamics of implied volatility surfaces," Quantitative Finance, Taylor & Francis Journals, vol. 2(1), pages 45-60.
    2. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2008. "Volatility forecasting using threshold heteroskedastic models of the intra-day range," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2990-3010, February.
    3. Pascual, Lorenzo & Romo, Juan & Ruiz, Esther, 2006. "Bootstrap prediction for returns and volatilities in GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2293-2312, May.
    4. Creal, Drew D., 2008. "Analysis of filtering and smoothing algorithms for Lévy-driven stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2863-2876, February.
    5. Xekalaki, Evdokia & Degiannakis, Stavros, 2005. "Evaluating volatility forecasts in option pricing in the context of a simulated options market," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 611-629, April.
    6. Omori, Yasuhiro & Watanabe, Toshiaki, 2008. "Block sampler and posterior mode estimation for asymmetric stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2892-2910, February.
    7. Ruiz, Esther & Veiga, Helena, 2008. "Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2846-2862, February.
    8. Amendola, Alessandra & Storti, Giuseppe, 2008. "A GMM procedure for combining volatility forecasts," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3047-3060, February.
    9. Kemna, A. G. Z. & Vorst, A. C. F., 1990. "A pricing method for options based on average asset values," Journal of Banking & Finance, Elsevier, vol. 14(1), pages 113-129, March.
    10. Yu, Jun & Yang, Zhenlin & Zhang, Xibin, 2006. "A class of nonlinear stochastic volatility models and its implications for pricing currency options," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2218-2231, December.
    11. Buhlmann, Peter & McNeil, Alexander J., 2002. "An algorithm for nonparametric GARCH modelling," Computational Statistics & Data Analysis, Elsevier, vol. 40(4), pages 665-683, October.
    12. Raggi, Davide & Bordignon, Silvano, 2006. "Comparing stochastic volatility models through Monte Carlo simulations," Computational Statistics & Data Analysis, Elsevier, vol. 50(7), pages 1678-1699, April.
    13. Gianluca Cassesse & Massimo Guidolin, 2005. "Modelling the MIB30 implied volatility surface. Does market efficiency matter?," Working Papers 2005-008, Federal Reserve Bank of St. Louis.
    14. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    15. Suk Kim, Myung & Wang, Suojin, 2006. "On the applicability of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2210-2217, December.
    16. Bordignon, Silvano & Caporin, Massimiliano & Lisi, Francesco, 2007. "Generalised long-memory GARCH models for intra-daily volatility," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5900-5912, August.
    17. Bernard Dumas & Jeff Fleming & Robert E. Whaley, 1998. "Implied Volatility Functions: Empirical Tests," Journal of Finance, American Finance Association, vol. 53(6), pages 2059-2106, December.
    18. Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
    19. Mancino, M.E. & Sanfelici, S., 2008. "Robustness of Fourier estimator of integrated volatility in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2966-2989, February.
    20. Barone-Adesi, Giovanni & Rasmussen, Henrik & Ravanelli, Claudia, 2005. "An option pricing formula for the GARCH diffusion model," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 287-310, April.
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    1. Śmiech, Sławomir & Papież, Monika & Rubaszek, Michał & Snarska, Małgorzata, 2021. "The role of oil price uncertainty shocks on oil-exporting countries," Energy Economics, Elsevier, vol. 93(C).
    2. Itkin, Andrey, 2015. "To sigmoid-based functional description of the volatility smile," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 264-291.
    3. Zdeněk Drábek & Miloš Kopa & Matúš Maciak & Michal Pešta & Sebastiano Vitali, 2023. "Investment disputes and their explicit role in option market uncertainty and overall risk instability," Computational Management Science, Springer, vol. 20(1), pages 1-25, December.
    4. Chang, C-L. & Hsieh, T-L. & McAleer, M.J., 2016. "How are VIX and Stock Index ETF Related?," Econometric Institute Research Papers EI2016-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Cristian Homescu, 2011. "Implied Volatility Surface: Construction Methodologies and Characteristics," Papers 1107.1834, arXiv.org.
    6. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2016. "Connecting VIX and Stock Index ETF," Tinbergen Institute Discussion Papers 16-010/III, Tinbergen Institute, revised 23 Jan 2017.
    7. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2018. "Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK," JRFM, MDPI, vol. 11(4), pages 1-25, September.
    8. Shang, Han Lin & Kearney, Fearghal, 2022. "Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1025-1049.
    9. Miloš Kopa & Sebastiano Vitali & Tomáš Tichý & Radek Hendrych, 2017. "Implied volatility and state price density estimation: arbitrage analysis," Computational Management Science, Springer, vol. 14(4), pages 559-583, October.
    10. Liu, Zhenhua & Tseng, Hui-Kuan & Wu, Jy S. & Ding, Zhihua, 2020. "Implied volatility relationships between crude oil and the U.S. stock markets: Dynamic correlation and spillover effects," Resources Policy, Elsevier, vol. 66(C).
    11. Sebastiano Vitali & Miloš Kopa & Gabriele Giana, 2023. "Implied volatility smoothing at COVID-19 times," Computational Management Science, Springer, vol. 20(1), pages 1-42, December.

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