IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v34y2020ics1544612319303320.html
   My bibliography  Save this article

Exotic options pricing under special Lévy process models: A biased control variate method approach

Author

Listed:
  • Jia, Jiayi
  • Lai, Yongzeng
  • Li, Lin
  • Tan, Vinna

Abstract

Option pricing plays an important role in financial engineering. No explicit formulas can be derived for many exotic options when the underlying asset prices follow more realistic models. The Monte Carlo simulation method is the only feasible approach to obtain numerical values of these options usually. To overcome the slow convergence – the main drawback for the Monte Carlo method, variance reduction and quasi-Monte Carlo methods are proposed. This paper proposes the application of biased control variate method to speed up the evaluation of exotic options prices by simulations under a special type of Lévy processes. We construct very efficient biased control variates for both fixed and floating strike lookback options, as well as barrier options.

Suggested Citation

  • Jia, Jiayi & Lai, Yongzeng & Li, Lin & Tan, Vinna, 2020. "Exotic options pricing under special Lévy process models: A biased control variate method approach," Finance Research Letters, Elsevier, vol. 34(C).
  • Handle: RePEc:eee:finlet:v:34:y:2020:i:c:s1544612319303320
    DOI: 10.1016/j.frl.2019.07.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612319303320
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2019.07.022?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. Nick Webber & Claudia Ribeiro, 2003. "A Monte Carlo Method for the Normal Inverse Gaussian Option Valuation Model using an Inverse Gaussian Bridge," Computing in Economics and Finance 2003 5, Society for Computational Economics.
    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. Lu, Jin-Ray & Yang, Ya-Huei, 2021. "Option valuations and asset demands and supplies," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 49-64.

    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. Weilong Fu & Ali Hirsa, 2019. "A fast method for pricing American options under the variance gamma model," Papers 1903.07519, arXiv.org.
    2. Zhang, Ling & Lai, Yongzeng & Zhang, Shuhua & Li, Lin, 2019. "Efficient control variate methods with applications to exotic options pricing under subordinated Brownian motion models," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 602-621.
    3. Dingeç, Kemal Dinçer & Hörmann, Wolfgang, 2012. "A general control variate method for option pricing under Lévy processes," European Journal of Operational Research, Elsevier, vol. 221(2), pages 368-377.
    4. Kyoung-Kuk Kim & Sojung Kim, 2016. "Simulation of Tempered Stable Lévy Bridges and Its Applications," Operations Research, INFORMS, vol. 64(2), pages 495-509, April.
    5. Zang, Xin & Jiang, Fan & Xia, Chenxi & Yang, Jingping, 2024. "Random distortion risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 116(C), pages 51-73.
    6. Wenbin Hu & Junzi Zhou, 2017. "Backward simulation methods for pricing American options under the CIR process," Quantitative Finance, Taylor & Francis Journals, vol. 17(11), pages 1683-1695, November.

    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:eee:finlet:v:34:y:2020:i:c:s1544612319303320. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.