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Pricing options using implied trees: Evidence from FTSE‐100 options

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  • Kian Guan Lim
  • Da Zhi

Abstract

Previously, few, if any, comparative tests of performance of Jackwerth's ( 1997 ) generalized binomial tree (GBT) and Derman and Kani ( 1994 ) implied volatility tree (IVT) models were done. In this paper, we propose five different weight functions in GBT and test them empirically compared to both the Black‐Scholes model and IVT. We use the daily settlement prices of FTSE‐100 index options from January to November 1999. With both American and European options traded on the FTSE‐100 index, we construct both GBT and IVT from European options and examine their performance in both the hedging of European option and the pricing of its American counterpart. IVT is found to produce least hedging errors and best results for American call options with earlier maturity than the maturity span of the implied trees. GBT appears to produce better results for American ATM put pricing for any maturity, and better in‐sample fit for options with maturity equal to the maturity span of the implied trees. Deltas calculated from IVT are consistently lower (higher) than Black‐Scholes deltas for both European and American calls (puts) in absolute term. The reverse holds true for GBT deltas. These empirical findings about the relative performance of GBT, IVT, and Standard Black‐Scholes models are important to practitioners as they indicate that different methods should be used for different applications, and some cautions should be exercised. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:601–626, 2002

Suggested Citation

  • Kian Guan Lim & Da Zhi, 2002. "Pricing options using implied trees: Evidence from FTSE‐100 options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(7), pages 601-626, July.
    • Handle: RePEc:wly:jfutmk:v:22:y:2002:i:7:p:601-626
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    Cited by:

    1. Xin‐Jiang He & Wenting Chen, 2021. "A semianalytical formula for European options under a hybrid Heston–Cox–Ingersoll–Ross model with regime switching," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 343-352, January.
    2. Tianyang Wang & James S. Dyer, 2010. "Valuing Multifactor Real Options Using an Implied Binomial Tree," Decision Analysis, INFORMS, vol. 7(2), pages 185-195, June.
    3. He, Xin-Jiang & Zhu, Song-Ping, 2016. "An analytical approximation formula for European option pricing under a new stochastic volatility model with regime-switching," Journal of Economic Dynamics and Control, Elsevier, vol. 71(C), pages 77-85.
    4. Nappo, Giovanna & Marchetti, Fabio Massimo & Vagnani, Gianluca, 2023. "Traders’ heterogeneous beliefs about stock volatility and the implied volatility skew in financial options markets," Finance Research Letters, Elsevier, vol. 53(C).
    5. Sha Lin & Xin-Jiang He, 2022. "Analytically Pricing European Options under a New Two-Factor Heston Model with Regime Switching," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1069-1085, March.
    6. Vipul Kumar Singh, 2016. "Pricing and hedging competitiveness of the tree option pricing models: Evidence from India," Journal of Asset Management, Palgrave Macmillan, vol. 17(6), pages 453-475, October.
    7. 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.
    8. 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.
    9. 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".
    10. Bo Jing & Shenghong Li & Yong Ma, 2020. "Pricing VIX options with volatility clustering," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(6), pages 928-944, June.

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