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Implied volatility surface construction for commodity futures options traded in China

Author

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  • Xu, Wei
  • Šević, Aleksandar
  • Šević, Željko

Abstract

European futures options are not traded on the Chinese exchanges and that generates difficulties to calibrate fundamental market parameters, such as the implied volatilities. We propose an efficient willow tree method to resolve the problem of calibrating the implied volatility from American-style options. The proposed willow tree construction is independent of the volatility itself so as to minimize the cost of the calibration. We also apply the proposed method to calibrate the implied volatilities of most frequently traded options in the Chinese market, sugar and soybean meal, based on the daily closing prices, and construct the corresponding implied volatility surfaces. The results indicate the seasonality in the volatility of commodity spot prices and futures prices in China. Moreover, based on the implied volatility distortion close to the option maturity observed in our empirical results, we suggest a minimum tick price scheme to avoid the distortion and decrease of hedging costs.

Suggested Citation

  • Xu, Wei & Šević, Aleksandar & Šević, Željko, 2022. "Implied volatility surface construction for commodity futures options traded in China," Research in International Business and Finance, Elsevier, vol. 61(C).
  • Handle: RePEc:eee:riibaf:v:61:y:2022:i:c:s0275531922000642
    DOI: 10.1016/j.ribaf.2022.101676
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    References listed on IDEAS

    as
    1. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    2. Buchen, Peter W. & Kelly, Michael, 1996. "The Maximum Entropy Distribution of an Asset Inferred from Option Prices," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 31(1), pages 143-159, March.
    3. Ioannis Kyriakou & Nikos K. Nomikos & Nikos C. Papapostolou & Panos K. Pouliasis, 2016. "Affine†Structure Models and the Pricing of Energy Commodity Derivatives," European Financial Management, European Financial Management Association, vol. 22(5), pages 853-881, November.
    4. Ling Lu & Wei Xu & Zhehui Qian, 2017. "Efficient willow tree method for European-style and American-style moving average barrier options pricing," Quantitative Finance, Taylor & Francis Journals, vol. 17(6), pages 889-906, June.
    5. Wei Xu & Zhiwu Hong & Chenxiang Qin, 2013. "A new sampling strategy willow tree method with application to path-dependent option pricing," Quantitative Finance, Taylor & Francis Journals, vol. 13(6), pages 861-872, May.
    6. Bosch, David & Smimou, K., 2022. "Traders’ motivation and hedging pressure in commodity futures markets," Research in International Business and Finance, Elsevier, vol. 59(C).
    7. Jim Gatheral & Antoine Jacquier, 2014. "Arbitrage-free SVI volatility surfaces," Quantitative Finance, Taylor & Francis Journals, vol. 14(1), pages 59-71, January.
    8. 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.
    9. José Renato Haas Ornelas & Roberto Baltieri Mauad, 2017. "Volatility risk premia and future commodities returns," BIS Working Papers 619, Bank for International Settlements.
    10. Ornelas, José Renato Haas & Mauad, Roberto Baltieri, 2019. "Volatility risk premia and future commodity returns," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 341-360.
    11. Bugge, Sebastian A. & Guttormsen, Haakon J. & Molnár, Peter & Ringdal, Martin, 2016. "Implied volatility index for the Norwegian equity market," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 133-141.
    12. Jim Gatheral & Antoine Jacquier, 2011. "Convergence of Heston to SVI," Quantitative Finance, Taylor & Francis Journals, vol. 11(8), pages 1129-1132.
    13. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    14. Bai, Yizhou & Xue, Cheng, 2021. "An empirical study on the regulated Chinese agricultural commodity futures market based on skew Ornstein-Uhlenbeck model," Research in International Business and Finance, Elsevier, vol. 57(C).
    15. Bo Zhao & Stewart Hodges, 2013. "Parametric modeling of implied smile functions: a generalized SVI model," Review of Derivatives Research, Springer, vol. 16(1), pages 53-77, April.
    16. Johnny Siu‐Hang Li & Andrew Cheuk‐Yin Ng & Wai‐Sum Chan, 2011. "On the calibration of mortality forward curves," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(10), pages 947-970, October.
    17. Ronald W. Anderson & Jean-Pierre Danthine, 1983. "The Time Pattern of Hedging and the Volatility of Futures Prices," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 50(2), pages 249-266.
    18. Helyette Geman & V. Nguyen, 2005. "Soybeans Inventory and Forward Curve Dynamics," Post-Print halshs-00144292, HAL.
    19. Nelson, Daniel B & Ramaswamy, Krishna, 1990. "Simple Binomial Processes as Diffusion Approximations in Financial Models," The Review of Financial Studies, Society for Financial Studies, vol. 3(3), pages 393-430.
    20. Wang, JinDong & Xu, Wei, 2020. "Risk-Based Capital For Variable Annuity Under Stochastic Interest Rate," ASTIN Bulletin, Cambridge University Press, vol. 50(3), pages 959-999, September.
    21. Poshakwale, Sunil S. & Chandorkar, Pankaj & Agarwal, Vineet, 2019. "Implied volatility and the cross section of stock returns in the UK," Research in International Business and Finance, Elsevier, vol. 48(C), pages 271-286.
    22. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    23. Hélyette Geman & Vu-Nhat Nguyen, 2005. "Soybean Inventory and Forward Curve Dynamics," Management Science, INFORMS, vol. 51(7), pages 1076-1091, July.
    24. 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.
    25. repec:dau:papers:123456789/1937 is not listed on IDEAS
    26. repec:bla:jfinan:v:53:y:1998:i:6:p:2059-2106 is not listed on IDEAS
    27. Thomas F. Coleman & Yuying Li & Arun Verma, 2001. "Reconstructing The Unknown Local Volatility Function," World Scientific Book Chapters, in: Marco Avellaneda (ed.), Quantitative Analysis In Financial Markets Collected Papers of the New York University Mathematical Finance Seminar(Volume II), chapter 7, pages 192-215, World Scientific Publishing Co. Pte. Ltd..
    28. Gaoyue Guo & Antoine Jacquier & Claude Martini & Leo Neufcourt, 2012. "Generalised arbitrage-free SVI volatility surfaces," Papers 1210.7111, arXiv.org, revised May 2016.
    29. Triantafyllou, Athanasios & Dotsis, George, 2017. "Option-implied expectations in commodity markets and monetary policy," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 1-17.
    30. Cox, John C. & Ross, Stephen A. & Rubinstein, Mark, 1979. "Option pricing: A simplified approach," Journal of Financial Economics, Elsevier, vol. 7(3), pages 229-263, September.
    31. Birkelund, Ole Henrik & Haugom, Erik & Molnár, Peter & Opdal, Martin & Westgaard, Sjur, 2015. "A comparison of implied and realized volatility in the Nordic power forward market," Energy Economics, Elsevier, vol. 48(C), pages 288-294.
    32. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
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    More about this item

    Keywords

    Commodity futures option; Implied volatility; SVI model; Willow tree method; American option; Mean-reverting;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

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