IDEAS home Printed from https://ideas.repec.org/a/wly/apsmbi/v29y2013i1p31-44.html
   My bibliography  Save this article

Pricing of mountain range derivatives under a principal component stochastic volatility model

Author

Listed:
  • Marcos Escobar
  • Pablo Olivares

Abstract

In this paper, a multidimensional stochastic volatility process is introduced. This process is simpler than existing ones in terms of number of parameters while keeping practical stylized facts like stochastic correlation and volatility. The pricing of two mountain range derivatives, Altavista and Everest, is analyzed under this framework, showing sensitivities to parameters, number of eigenvalues, and maturity time. Copyright © 2012 John Wiley & Sons, Ltd.

Suggested Citation

  • Marcos Escobar & Pablo Olivares, 2013. "Pricing of mountain range derivatives under a principal component stochastic volatility model," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 29(1), pages 31-44, January.
    • Handle: RePEc:wly:apsmbi:v:29:y:2013:i:1:p:31-44
    DOI: 10.1002/asmb.936
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asmb.936
    Download Restriction: no
    File URL: https://libkey.io/10.1002/asmb.936?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
    ---><---

    Citations

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


    Cited by:

    1. Marcos Escobar & Sebastian Ferrando & Alexey Rubtsov, 2017. "Optimal investment under multi-factor stochastic volatility," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 241-260, February.
    2. Daniela Neykova & Marcos Escobar & Rudi Zagst, 2015. "Optimal investment in multidimensional Markov-modulated affine models," Annals of Finance, Springer, vol. 11(3), pages 503-530, November.
    3. Marcos Escobar & Christoph Gschnaidtner, 2018. "A multivariate stochastic volatility model with applications in the foreign exchange market," Review of Derivatives Research, Springer, vol. 21(1), pages 1-43, April.
    4. Marcos Escobar & Daniel Krause & Rudi Zagst, 2016. "Stochastic covariance and dimension reduction in the pricing of basket options," Review of Derivatives Research, Springer, vol. 19(3), pages 165-200, October.
    5. Wang, Hang & Hu, Zhijun, 2020. "Optimal consumption and portfolio decision with stochastic covariance in incomplete markets," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    6. Marcos Escobar & Sven Panz, 2016. "A Note on the Impact of Parameter Uncertainty on Barrier Derivatives," Risks, MDPI, vol. 4(4), pages 1-25, September.

    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:apsmbi:v:29:y:2013:i:1:p:31-44. 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: https://doi.org/10.1002/(ISSN)1526-4025 .

    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.