IDEAS home Printed from https://ideas.repec.org/h/spr/sptchp/978-3-030-37740-3_4.html
   My bibliography  Save this book chapter

Markowitz Without a Risk-Free Asset

In: Quantitative Portfolio Management

Author

Listed:
  • Pierre Brugière

    (University Paris Dauphine-PSL)

Abstract

In this chapter we solve the Markowitz problem Markowitz problem of finding the investment portfolios which, for a given level of expected return, present the minimum risk. The assumption is made that the returns of the assets (and consequently of the portfolios) follow a Gaussian distribution, and the risk is defined as the standard deviation of the returns. Except in the case where all the risky assets have the same returns, the solution portfolios ℱ $$\mathcal {F}$$ of this mean-variance optimisation problem define a hyperbola when representing in a plane the set ℱ ( σ , m ) $$\mathcal {F}(\sigma ,m)$$ of their standard deviations and expected returns. This hyperbola also determines the limit of all the investment portfolios that can be built. Its upper side ℱ + ( σ , m ) $$\mathcal {F}^+(\sigma ,m)$$ corresponds to the efficient portfolios and is called the efficient frontier Efficient frontier , while its lower side ℱ − ( σ , m ) $$\mathcal {F}^-(\sigma ,m)$$ is called the inefficient frontier Frontier inefficient . The two fund theorem Two fund theorem demonstrated here proves that, when taking any pair of distinct portfolios from ℱ $$\mathcal {F}$$ , any other portfolio from ℱ $$\mathcal {F}$$ can be constructed through an allocation between these two portfolios. As a consequence, when two optimal portfolios are found, the subsequent problem of finding other optimal portfolios is just a problem of allocation between these two funds.

Suggested Citation

  • Pierre Brugière, 2020. "Markowitz Without a Risk-Free Asset," Springer Texts in Business and Economics, in: Quantitative Portfolio Management, chapter 0, pages 51-59, Springer.
  • Handle: RePEc:spr:sptchp:978-3-030-37740-3_4
    DOI: 10.1007/978-3-030-37740-3_4
    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:sptchp:978-3-030-37740-3_4. 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.