IDEAS home Printed from https://ideas.repec.org/a/cup/anacsi/v16y2022i2p367-383_9.html
   My bibliography  Save this article

Optimal investment strategy for a DC pension fund plan in a finite horizon time: an optimal stochastic control approach

Author

Listed:
  • Vahabi, Saman
  • Payandeh Najafabadi, Amir T.

Abstract

This paper obtains an optimal strategy in a finite horizon time for a portfolio of a defined contribution (DC) pension fund for an investor with the CRRA utility function. It employs the optimal stochastic control method in a financial market with two different asset markets, one risk-free and another one risky asset in which its jump follows either by a finite or infinite activity Lévy process. Sensitivity of jump parameters in an uncertainty financial market has been studied.

Suggested Citation

  • Vahabi, Saman & Payandeh Najafabadi, Amir T., 2022. "Optimal investment strategy for a DC pension fund plan in a finite horizon time: an optimal stochastic control approach," Annals of Actuarial Science, Cambridge University Press, vol. 16(2), pages 367-383, July.
    • Handle: RePEc:cup:anacsi:v:16:y:2022:i:2:p:367-383_9
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S1748499521000270/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Pengyu Wei & Charles Yang, 2023. "Optimal investment for defined-contribution pension plans under money illusion," Review of Quantitative Finance and Accounting, Springer, vol. 61(2), pages 729-753, August.

    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:cup:anacsi:v:16:y:2022:i:2:p:367-383_9. 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: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/aas .

    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.