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Implied Volatility Trees And Pricing Performance: Evidence From The S&P 100 Options

Author

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  • CHARILAOS E. LINARAS

    (Technical Division, EKO-ELDA A.B.E.E., Hellenic Petroleum Group S.A., Athens, Greece)

  • GEORGE SKIADOPOULOS

    (Department of Banking and Financial Management, University of Piraeus, Karaoli & Dimitriou 80, 18534 Piraeus, Greece;
    Financial Options Research Centre, Warwick Business School, University of Warwick, UK)

Abstract

This paper examines the pricing performance of various discrete-time option models that accept the variation of implied volatilities with respect to the strike price and the time-to-maturity of the option (implied volatility tree models). To this end, data from the S&P 100 options are employed for the first time. The complex implied volatility trees are compared to the standard Cox–Ross–Rubinstein model and the ad-hoc traders model. Various criteria and interpolation methods are used to evaluate the performance of the models. The results have important implications for the pricing accuracy of the models under scrutiny and their implementation.

Suggested Citation

  • Charilaos E. Linaras & George Skiadopoulos, 2005. "Implied Volatility Trees And Pricing Performance: Evidence From The S&P 100 Options," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(08), pages 1085-1106.
    • Handle: RePEc:wsi:ijtafx:v:08:y:2005:i:08:n:s0219024905003359
    DOI: 10.1142/S0219024905003359
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    Citations

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    Cited by:

    1. Fabozzi, Frank J. & Paletta, Tommaso & Stanescu, Silvia & Tunaru, Radu, 2016. "An improved method for pricing and hedging long dated American options," European Journal of Operational Research, Elsevier, vol. 254(2), pages 656-666.
    2. U Hou Lok & Yuh-Dauh Lyuu, 2022. "A Valid and Efficient Trinomial Tree for General Local-Volatility Models," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 817-832, October.
    3. U Hou Lok & Yuh‐Dauh Lyuu, 2020. "Efficient trinomial trees for local‐volatility models in pricing double‐barrier options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(4), pages 556-574, April.
    4. Elyas Elyasiani & Silvia Muzzioli & Alessio Ruggieri, 2016. "Forecasting and pricing powers of option-implied tree models: Tranquil and volatile market conditions," Department of Economics 0099, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    5. Yossi Shvimer & Avi Herbon, 2020. "Tradability, closeness to market prices, and expected profit: their measurement for a binomial model of options pricing in a heterogeneous market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(3), pages 737-762, July.
    6. Panayiotis Andreou & Chris Charalambous & Spiros Martzoukos, 2014. "Assessing the performance of symmetric and asymmetric implied volatility functions," Review of Quantitative Finance and Accounting, Springer, vol. 42(3), pages 373-397, April.
    7. Moriggia, V. & Muzzioli, S. & Torricelli, C., 2009. "On the no-arbitrage condition in option implied trees," European Journal of Operational Research, Elsevier, vol. 193(1), pages 212-221, February.

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