IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-031-84304-4_3.html
   My bibliography  Save this book chapter

Sample Based Methods

In: Advanced Portfolio Optimization

Author

Listed:
  • Dany Cajas

    (Orenji EIRL)

Abstract

This chapter explains several methods that allow readers to estimate the input parameters used by most portfolio optimization models: the expected returns vector and the covariance matrix. These methods mainly use the sample of asset returns as input and, depending on the method, some additional parameters. They are widely used by students, academics, and practitioners because they do not require assuming an explicit relationship with additional variables or the use of prior information like risk factor models and Black Litterman models, respectively. However, their main disadvantage is that the estimated parameters assume that the future performance of asset returns will be like the sample used to estimate them.

Suggested Citation

  • Dany Cajas, 2025. "Sample Based Methods," Springer Books, in: Advanced Portfolio Optimization, chapter 0, pages 15-55, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-84304-4_3
    DOI: 10.1007/978-3-031-84304-4_3
    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
    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:sprchp:978-3-031-84304-4_3. 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.