IDEAS home Printed from https://ideas.repec.org/a/wly/jfutmk/v19y1999i7p817-843.html
   My bibliography  Save this article

A flexible binomial option pricing model

Author

Listed:
  • Yisong “Sam” Tian

Abstract

This article develops a flexible binomial model with a “tilt” parameter that alters the shape and span of the binomial tree. A positive tilt parameter shifts the tree upward while a negative tilt parameter does exactly the opposite. This simple extension of the standard binomial model is shown to converge with any value of the tilt parameter. More importantly, the binomial tree can be recalibrated through the tilt parameter in order to position nodes relative to the strike price or barrier of an option. The rate of convergence is improved as a result. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 817–843, 1999

Suggested Citation

  • Yisong “Sam” Tian, 1999. "A flexible binomial option pricing model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(7), pages 817-843, October.
    • Handle: RePEc:wly:jfutmk:v:19:y:1999:i:7:p:817-843
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dong Zou & Pu Gong, 2017. "A Lattice Framework with Smooth Convergence for Pricing Real Estate Derivatives with Stochastic Interest Rate," The Journal of Real Estate Finance and Economics, Springer, vol. 55(2), pages 242-263, August.
    2. Gambaro, Anna Maria & Kyriakou, Ioannis & Fusai, Gianluca, 2020. "General lattice methods for arithmetic Asian options," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1185-1199.
    3. 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.
    4. Luca Vincenzo Ballestra, 2021. "Enhancing finite difference approximations for double barrier options: mesh optimization and repeated Richardson extrapolation," Computational Management Science, Springer, vol. 18(2), pages 239-263, June.
    5. San-Lin Chung & Pai-Ta Shih, 2007. "Generalized Cox-Ross-Rubinstein Binomial Models," Management Science, INFORMS, vol. 53(3), pages 508-520, March.
    6. Jean-Christophe Breton & Youssef El-Khatib & Jun Fan & Nicolas Privault, 2021. "A q-binomial extension of the CRR asset pricing model," Papers 2104.10163, arXiv.org, revised Feb 2023.
    7. Gongqiu Zhang & Lingfei Li, 2019. "Analysis of Markov Chain Approximation for Option Pricing and Hedging: Grid Design and Convergence Behavior," Operations Research, INFORMS, vol. 67(2), pages 407-427, March.
    8. Guillaume Leduc & Merima Nurkanovic Hot, 2020. "Joshi’s Split Tree for Option Pricing," Risks, MDPI, vol. 8(3), pages 1-26, August.
    9. Yuan Hu & W. Brent Lindquist & Svetlozar T. Rachev & Frank J. Fabozzi, 2024. "Option Pricing Using a Skew Random Walk Binary Tree," JRFM, MDPI, vol. 17(4), pages 1-29, March.
    10. Alona Bock & Ralf Korn, 2016. "Improving Convergence of Binomial Schemes and the Edgeworth Expansion," Risks, MDPI, vol. 4(2), pages 1-22, May.
    11. Pier Giuseppe Giribone & Simone Ligato, 2016. "Flexible-forward pricing through Leisen–Reimer trees: Implementation and performance comparison with traditional Markov chains," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 1-21, June.
    12. Yuan Hu & W. Brent Lindquist & Svetlozar T. Rachev & Frank J. Fabozzi, 2023. "Option pricing using a skew random walk pricing tree," Papers 2303.17014, arXiv.org.
    13. Feng Dai & Ling Liang, 2005. "The Advance in Partial Distribution: A New Mathematical Tool for Economic Management," EERI Research Paper Series EERI_RP_2005_04, Economics and Econometrics Research Institute (EERI), Brussels.
    14. Tianyang Wang & James Dyer & Warren Hahn, 2015. "A copula-based approach for generating lattices," Review of Derivatives Research, Springer, vol. 18(3), pages 263-289, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:jfutmk:v:19:y:1999:i:7:p:817-843. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0270-7314/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.