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Implied volatility surfaces: uncovering regularities for options on financial futures

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  • Robert Tompkins

Abstract

It is well known that the implied volatilities of options on the same underlying asset differ across strike prices and terms to expiration. However, the reason for this remains unclear. Before the development of theory to explain this phenomenon, it may be helpful to better understand the empirical record of implied volatility surfaces. If regularities are discovered which are stable over time, this may aid the development of theories to explain implied volatility surfaces and provide a means to test alternative models. This paper identifies these regularities and subsequent research will examine the implications of these results. While a number of papers have examined individual option markets and identified smile patterns, it is not clear whether the conclusions found are based upon idiosyncrasies of a particular market or more generally apply to options in other markets. This research fills this gap in the literature by examining sixteen options markets on financial futures (comprising four asset classes) and compares the smile patterns across markets. Furthermore, this analysis considers a longer period of analysis than previously examined in the literature. This allows assessment of the stability of the implied volatility patterns for a variety of subperiods and testing of models outside of sample.

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  • Robert Tompkins, 2001. "Implied volatility surfaces: uncovering regularities for options on financial futures," The European Journal of Finance, Taylor & Francis Journals, vol. 7(3), pages 198-230.
  • Handle: RePEc:taf:eurjfi:v:7:y:2001:i:3:p:198-230
    DOI: 10.1080/13518470110040375
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    Cited by:

    1. Chalamandaris, Georgios & Tsekrekos, Andrianos E., 2010. "Predictable dynamics in implied volatility surfaces from OTC currency options," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1175-1188, June.
    2. Sabrina Ecca & Michele Marchesi & Alessio Setzu, 2008. "Modeling and Simulation of an Artificial Stock Option Market," Computational Economics, Springer;Society for Computational Economics, vol. 32(1), pages 37-53, September.
    3. Haas, Markus & Mittnik, Stefan & Mizrach, Bruce, 2006. "Assessing central bank credibility during the ERM crises: Comparing option and spot market-based forecasts," Journal of Financial Stability, Elsevier, vol. 2(1), pages 28-54, April.
    4. Boes, Mark-Jan & Drost, Feike C. & Werker, Bas J. M., 2007. "The Impact of Overnight Periods on Option Pricing," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(2), pages 517-533, June.
    5. Kotzé, Antonie & Labuschagne, Coenraad C.A. & Nair, Merell L. & Padayachi, Nadine, 2013. "Arbitrage-free implied volatility surfaces for options on single stock futures," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 380-399.
    6. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    7. Tompkins, Robert G. & D'Ecclesia, Rita L., 2006. "Unconditional return disturbances: A non-parametric simulation approach," Journal of Banking & Finance, Elsevier, vol. 30(1), pages 287-314, January.
    8. Ederington, Louis H. & Guan, Wei, 2013. "The cross-sectional relation between conditional heteroskedasticity, the implied volatility smile, and the variance risk premium," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3388-3400.
    9. Patrik Karlsson, 2018. "Finite element based Monte Carlo simulation of options on Lévy driven assets," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-23, March.
    10. Bates, David S., 2008. "The market for crash risk," Journal of Economic Dynamics and Control, Elsevier, vol. 32(7), pages 2291-2321, July.
    11. Bruce Mizrach, 2007. "Recovering Probabilistic Information From Options Prices and the Underlying," Departmental Working Papers 200702, Rutgers University, Department of Economics.
    12. Antonie Kotzé & Rudolf Oosthuizen & Edson Pindza, 2015. "Implied and Local Volatility Surfaces for South African Index and Foreign Exchange Options," JRFM, MDPI, vol. 8(1), pages 1-40, January.
    13. 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.
    14. Mi‐Hsiu Chiang & Hsin‐Yu Chiu & Robin K. Chou, 2021. "Relevance of the disposition effect on the options market: New evidence," Financial Management, Financial Management Association International, vol. 50(1), pages 75-106, March.
    15. Alentorn, Amadeo & Markose, Sheri M, 2006. "Removing Maturity Effects of Implied Risk Neutral Densities and Related Statistics," Economics Discussion Papers 3722, University of Essex, Department of Economics.
    16. 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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