IDEAS home Printed from https://ideas.repec.org/p/rza/wpaper/695.html
   My bibliography  Save this paper

Capturing the Black Swan: Scenario-Based Asset Allocation with Fat Tails and Non-Linear Correlations

Author

Listed:
  • Vsevolod I. Gorlach

Abstract

This paper highlights the shortfalls of Modern Portfolio Theory (MPT). Amongst other flaws, MPT assumes that returns are normally distributed; that correlations are linear; and that risks are symmetrical. We propose a dynamic and flexible scenario-based approach to portfolio selection that incorporates an investor’s economic forecast. Extreme Value Theory (EVT) is used to capture the […]

Suggested Citation

  • Vsevolod I. Gorlach, 2017. "Capturing the Black Swan: Scenario-Based Asset Allocation with Fat Tails and Non-Linear Correlations," Working Papers 695, Economic Research Southern Africa.
  • Handle: RePEc:rza:wpaper:695
    as

    Download full text from publisher

    File URL: https://econrsa.org/wp-content/uploads/2022/06/working_paper_695.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    investment; Quantitative Methods; Risk and Uncertainty;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:rza:wpaper:695. 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: Maggi Sigg (email available below). General contact details of provider: https://edirc.repec.org/data/ersacza.html .

    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.