IDEAS home Printed from https://ideas.repec.org/h/spr/dymchp/978-3-031-15286-3_6.html
   My bibliography  Save this book chapter

Black–Litterman Optimization Results

In: Advanced REIT Portfolio Optimization

Author

Listed:
  • W. Brent Lindquist

    (Texas Tech University)

  • Svetlozar T. Rachev

    (Texas Tech University)

  • Yuan Hu

    (University of California San Diego)

  • Abootaleb Shirvani

    (Kean University)

Abstract

The Black–Litterman model was designed to mitigate issues of input sensitivity and estimation error maximization by using a Bayesian approach to incorporate the returns of a market index. It also incorporates the ability to include subjective views based on investment analyst estimates. As subjective views are specific to the market day and the analyst, the exploration of this model in this chapter is restricted to incorporating market equilibrium returns. The performance of Black–Litterman optimized domestic and global REIT portfolios, under long-only investment strategies is compared to the corresponding mean variance optimized counterparts of Chaps. 4 and 5 . Reflecting its design, the performance of the Black–Litterman portfolios more closely tracks that of the selected market index than do optimizations that concentrate solely on maximizing the Sharpe ratio.

Suggested Citation

  • W. Brent Lindquist & Svetlozar T. Rachev & Yuan Hu & Abootaleb Shirvani, 2022. "Black–Litterman Optimization Results," Dynamic Modeling and Econometrics in Economics and Finance, in: Advanced REIT Portfolio Optimization, chapter 0, pages 87-92, Springer.
    • Handle: RePEc:spr:dymchp:978-3-031-15286-3_6
    DOI: 10.1007/978-3-031-15286-3_6
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:dymchp:978-3-031-15286-3_6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.