IDEAS home Printed from https://ideas.repec.org/a/wsi/ijfexx/v03y2016i02ns2424786316500109.html
   My bibliography  Save this article

Flexible-forward pricing through Leisen–Reimer trees: Implementation and performance comparison with traditional Markov chains

Author

Listed:
  • Pier Giuseppe Giribone

    (CARIGE Bank Group, 15 Cassa di Risparmio, 16123 Genoa, Italy)

  • Simone Ligato

    (CARIGE Bank Group, 15 Cassa di Risparmio, 16123 Genoa, Italy)

Abstract

This article aims to estimate the fair-value of flexi-forwards, popular financial instruments on currencies, through Leisen–Reimer trees. The first part of paper deals with Markov chains suitable for pricing American options: Cox–Ross–Rubinstein, Jarrow–Rudd, Tian, Leisen–Reimer Trees. The correctness of the implementation in Matlab has been tested by comparing their prices with those obtained through approximated closed-formulas. The second part highlights the better performance of Leisen–Reimer trees in terms of convergence speed and sensitivity. Finally, flexi-forward contracts have been priced by using the numerical methodologies which have outperformed in the previous parts.

Suggested Citation

  • 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.
    • Handle: RePEc:wsi:ijfexx:v:03:y:2016:i:02:n:s2424786316500109
    DOI: 10.1142/S2424786316500109
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S2424786316500109
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S2424786316500109?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bjerksund, Petter & Stensland, Gunnar, 1993. "Closed-form approximation of American options," Scandinavian Journal of Management, Elsevier, vol. 9(Supplemen), pages 87-99.
    2. Leisen, Dietmar P. J., 1998. "Pricing the American put option: A detailed convergence analysis for binomial models," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1419-1444, August.
    3. Roll, Richard, 1977. "An analytic valuation formula for unprotected American call options on stocks with known dividends," Journal of Financial Economics, Elsevier, vol. 5(2), pages 251-258, November.
    4. Wallner, Christian & Wystup, Uwe, 2004. "Efficient computation of option price sensitivities for options of American style," CPQF Working Paper Series 1, Frankfurt School of Finance and Management, Centre for Practical Quantitative Finance (CPQF).
    5. 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.
    6. Yisong Tian, 1993. "A modified lattice approach to option pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 13(5), pages 563-577, August.
    7. Dietmar Leisen & Matthias Reimer, 1996. "Binomial models for option valuation - examining and improving convergence," Applied Mathematical Finance, Taylor & Francis Journals, vol. 3(4), pages 319-346.
    8. Barone-Adesi, Giovanni & Whaley, Robert E, 1987. "Efficient Analytic Approximation of American Option Values," Journal of Finance, American Finance Association, vol. 42(2), pages 301-320, June.
    9. 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.
    10. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Mattia Fabbri & Pier Giuseppe Giribone, 2020. "Design, implementation and validation of advanced lattice techniques for pricing EAKO — European American Knock-Out option," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 6(04), pages 1-26, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qianru Shang & Brian Byrne, 2021. "American option pricing: Optimal Lattice models and multidimensional efficiency tests," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(4), pages 514-535, April.
    2. San-Lin Chung & Pai-Ta Shih, 2007. "Generalized Cox-Ross-Rubinstein Binomial Models," Management Science, INFORMS, vol. 53(3), pages 508-520, March.
    3. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    4. Leisen, Dietmar P. J., 1999. "The random-time binomial model," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1355-1386, September.
    5. Mark Broadie & Jérôme Detemple, 1996. "Recent Advances in Numerical Methods for Pricing Derivative Securities," CIRANO Working Papers 96s-17, CIRANO.
    6. Weihan Li & Jin E. Zhang & Xinfeng Ruan & Pakorn Aschakulporn, 2024. "An empirical study on the early exercise premium of American options: Evidence from OEX and XEO options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(7), pages 1117-1153, July.
    7. Jérôme Detemple, 2014. "Optimal Exercise for Derivative Securities," Annual Review of Financial Economics, Annual Reviews, vol. 6(1), pages 459-487, December.
    8. 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.
    9. In oon Kim & Bong-Gyu Jang & Kyeong Tae Kim, 2013. "A simple iterative method for the valuation of American options," Quantitative Finance, Taylor & Francis Journals, vol. 13(6), pages 885-895, May.
    10. Antonio Cosma & Stefano Galluccio & Paola Pederzoli & O. Scaillet, 2012. "Valuing American Options Using Fast Recursive Projections," Swiss Finance Institute Research Paper Series 12-26, Swiss Finance Institute.
    11. Weiping Li & Su Chen, 2018. "The Early Exercise Premium In American Options By Using Nonparametric Regressions," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(07), pages 1-29, November.
    12. Guillaume Leduc & Merima Nurkanovic Hot, 2020. "Joshi’s Split Tree for Option Pricing," Risks, MDPI, vol. 8(3), pages 1-26, August.
    13. Manuel Moreno & Javier Navas, 2003. "On the Robustness of Least-Squares Monte Carlo (LSM) for Pricing American Derivatives," Review of Derivatives Research, Springer, vol. 6(2), pages 107-128, May.
    14. M. H. Vellekoop & J. W. Nieuwenhuis, 2006. "Efficient Pricing of Derivatives on Assets with Discrete Dividends," Applied Mathematical Finance, Taylor & Francis Journals, vol. 13(3), pages 265-284.
    15. 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.
    16. Josheski Dushko & Apostolov Mico, 2020. "A Review of the Binomial and Trinomial Models for Option Pricing and their Convergence to the Black-Scholes Model Determined Option Prices," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 24(2), pages 53-85, June.
    17. Dietmar P.J. Leisen, 1997. "The Random-Time Binomial Model," Finance 9711005, University Library of Munich, Germany, revised 29 Nov 1998.
    18. Mondher Bellalah, 2009. "Derivatives, Risk Management & Value," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 7175, August.
    19. Shvimer, Yossi & Herbon, Avi, 2020. "Comparative empirical study of binomial call-option pricing methods using S&P 500 index data," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    20. Bartosz Lamasz & Natalia Iwaszczuk, 2020. "Crude Oil Option Market Parameters and Their Impact on the Cost of Hedging by Long Strap Strategy," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 471-480.

    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:wsi:ijfexx:v:03:y:2016:i:02:n:s2424786316500109. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscientific.com/worldscinet/ijfe .

    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.