IDEAS home Printed from https://ideas.repec.org/a/taf/uaajxx/v21y2017i1p87-106.html
   My bibliography  Save this article

Mean-Variance Asset Liability Management with State-Dependent Risk Aversion

Author

Listed:
  • Yan Zhang
  • Yonghong Wu
  • Shuang Li
  • Benchawan Wiwatanapataphee

Abstract

This article investigates the asset liability management problem with state-dependent risk aversion under the mean-variance criterion. The investor allocates the wealth among multiple assets including a risk-free asset and multiple risky assets governed by a system of geometric Brownian motion stochastic differential equations, and the investor faces the risk of paying uncontrollable random liabilities. The state-dependent risk aversion is taken into account in our model, linking the risk aversion to the current wealth held by the investor. An extended Hamilton-Jacobi-Bellman system is established for the optimization of asset liability management, and by solving the extended Hamilton-Jacobi-Bellman system, the analytical closed-form expressions for the time-inconsistent optimal investment strategies and the optimal value function are derived. Finally, numerical examples are presented to illustrate our results.

Suggested Citation

  • Yan Zhang & Yonghong Wu & Shuang Li & Benchawan Wiwatanapataphee, 2017. "Mean-Variance Asset Liability Management with State-Dependent Risk Aversion," North American Actuarial Journal, Taylor & Francis Journals, vol. 21(1), pages 87-106, January.
  • Handle: RePEc:taf:uaajxx:v:21:y:2017:i:1:p:87-106
    DOI: 10.1080/10920277.2016.1247719
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10920277.2016.1247719
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/10920277.2016.1247719?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.

    Citations

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


    Cited by:

    1. Lautier, Jackson P. & Pozdnyakov, Vladimir & Yan, Jun, 2023. "Pricing time-to-event contingent cash flows: A discrete-time survival analysis approach," Insurance: Mathematics and Economics, Elsevier, vol. 110(C), pages 53-71.
    2. Esfandi, Elaheh & Mousavi, Mir Hossein & Moshrefi, Rassam & Farhang-Moghaddam, Babak, 2020. "Insurer Optimal Asset Allocation in a Small and Closed Economy: The Case of Iran’s Social Security Organization," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 15(4), pages 445-461, 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:taf:uaajxx:v:21:y:2017:i:1:p:87-106. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/uaaj .

    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.